The Statistical Evaluation of the NESSIE SubmissionCS-cipher NESDOCUIBWP30101

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the journal science is adding an extra round

the journal science is adding an extra round The Journal Science Introduces an Extra Round: Fostering Enhanced Scientific Rigor and ReproducibilityIn an exciting move towards improved scientific rigor and reproducibility, The Journal Science has made an important announcement: they are adding an extra round to their publication process. This additional step aims to further enhance the credibility and reliability of the research they publish. This decision comes at a time when concerns about the reproducibility crisis in science have been gaining attention across disciplines.So, what exactly does this extra round entail? Let's dive into the details to understand how it will impact the scientific community and contribute to the advancement of knowledge.The first step in Science's new double-round submission process starts with the initial submission, as before. Scientists will submit their research for consideration, adhering to the traditional standards of scientific rigor, data analysis, and interpretation. This initial round remains an essential part of ensuring the quality of research presented in the journal.Once the initial submission has been assessed for scientific merit and meets the general criteria for publication, the paper will proceed to the next step—an additional round of review. The purpose of this round is to focus on the rigor of the research methodology, the transparency of data and code availability, and the reproducibility of the findings.During this second round, two new sets of reviewers will be appointed. The first set will evaluate the experimental design, statistical analysis, and data integrity, closely examining the robustness of the research claims. This careful scrutiny aims to prevent the publication of studies that may lead to false conclusions due to methodological flaws or statistical uncertainties.The second set of reviewers will specifically assess the reproducibility aspects of the research. They will scrutinize the availability of raw data, code, and materials necessary for replication, ensuring the study's findings can withstand independent verification. This emphasis on reproducibility is a pivotal step towards building a strong scientific foundation andincreasing confidence in research outcomes.The introduction of the extra round aligns The Journal Science with the growing consensus on the importance of scientific transparency and reproducibility. By conducting an in-depth examination of research methodology and data availability, the journal is taking a proactive role in tackling the reproducibility crisis that has plagued the scientific community in recent years.Some might worry that this added evaluation process will increase the time taken to publish a paper. However, Science is committed to streamlining the review process, acknowledging the need for efficiency without sacrificing scientific rigor. They intend to maintain a fair and expedited review timeline for researchers, while still ensuring the highest standards of reliability and reproducibility.In addition to enhancing scientific rigor, the new double-round submission process also encourages open scientific dialogue. Authors will have the opportunity to address the reviewers' comments and suggestions from the first round before resubmitting their papers. This iterative engagement fosters constructive engagement and can lead to valuable improvementsin the final research product.Furthermore, The Journal Science plans to provide open access to the reviewers' comments and authors' responses during the second round. This transparency will allow the wider scientific community to learn from the review process and further facilitate discussion and collaboration.Overall, the decision by The Journal Science to introduce an extra round to its publication process is a monumental step in advancing scientific rigor, reproducibility, and open dialogue. By closely examining research methodology and emphasizing the availability of data for replication, the journal is leading the charge towards a more robust and reliable scientific landscape. This move sets a precedent for other prestigious journals to consider similar measures, ultimately driving significant improvements in the standards of scientific research and ensuring the dissemination of accurate knowledge.。

英文统计量

英文统计量Statistical measures are numerical values that summarize or describe the characteristics of a dataset. They are essential tools in data analysis and decision-making processes, providing valuable insights into the underlying patterns and trends within a given set of information. In this essay, we will explore various types of statistical measures, their applications, and the importance of understanding them in the context of data-driven decision making.One of the most fundamental statistical measures is the measure of central tendency. This measure aims to identify the central or typical value within a dataset. The three most common measures of central tendency are the mean, median, and mode. The mean is calculated by summing all the values in the dataset and dividing by the total number of observations. The median is the middle value when the data is arranged in numerical order, and the mode is the value that appears most frequently in the dataset. Each of these measures provides a different perspective on the central tendency of the data, and the choice of which to use depends on the specific characteristics of the dataset and the intended purpose of theanalysis.Another important set of statistical measures are measures of dispersion, which quantify the spread or variability within a dataset. The most commonly used measures of dispersion are the range, variance, and standard deviation. The range is the difference between the highest and lowest values in the dataset, providing a simple measure of the overall spread. The variance, on the other hand, is a more sophisticated measure that calculates the average squared deviation from the mean. The standard deviation is the square root of the variance and represents the average distance of each data point from the mean. These measures of dispersion are crucial in understanding the consistency or variability of the data, which can have significant implications for decision-making and risk assessment.In addition to measures of central tendency and dispersion, there are also statistical measures that provide insights into the shape and distribution of a dataset. The skewness and kurtosis are two such measures. Skewness describes the asymmetry of the data distribution, indicating whether the data is skewed to the left or right. Kurtosis, on the other hand, measures the peakedness or flatness of the distribution, providing information about the concentration of values around the central tendency. Understanding the shape and distribution of a dataset can help analysts identify unusual or outlierobservations, as well as inform the selection of appropriate statistical models and techniques for further analysis.The application of statistical measures extends across a wide range of disciplines, from business and finance to healthcare and social sciences. In the business context, statistical measures can be used to analyze financial data, evaluate the performance of marketing campaigns, and make informed decisions about resource allocation and strategic planning. In healthcare, statistical measures are crucial for epidemiological studies, clinical trials, and the evaluation of treatment outcomes. In the social sciences, statistical measures are essential for understanding human behavior, identifying socioeconomic trends, and informing policy decisions.One of the key advantages of using statistical measures is their ability to summarize large and complex datasets in a concise and meaningful way. This can be particularly useful when dealing with big data, where the sheer volume of information can be overwhelming. By calculating and interpreting statistical measures, analysts can identify patterns, trends, and anomalies that might otherwise be obscured by the vast amount of data. This, in turn, can lead to more informed decision-making and the development of more effective strategies and solutions.However, it is important to note that the interpretation andapplication of statistical measures must be done with caution and a deep understanding of the underlying assumptions and limitations. Misinterpreting or misusing statistical measures can lead to flawed conclusions and poor decision-making. It is, therefore, crucial for data analysts and decision-makers to have a strong grasp of statistical concepts and to be able to critically evaluate the appropriateness and validity of the statistical measures used in their analyses.In conclusion, statistical measures are powerful tools that play a crucial role in data analysis and decision-making across a wide range of domains. From measures of central tendency and dispersion to measures of shape and distribution, these numerical values provide valuable insights into the characteristics and patterns within a dataset. By understanding and correctly applying statistical measures, analysts and decision-makers can make more informed and data-driven choices, ultimately leading to better outcomes and more effective solutions. As the volume and complexity of data continue to grow, the importance of statistical measures in the modern world will only continue to increase.。

语音信号当中降噪算法的实现方法

语音信号当中降噪算法的实现方法1.语音信号的降噪算法可以通过滤波器来实现。

The noise reduction algorithm of speech signals can be implemented through filters.2.降噪算法可以利用数字信号处理技术进行实现。

The noise reduction algorithm can be implemented using digital signal processing techniques.3.常见的降噪算法包括中值滤波和小波变换。

Common noise reduction algorithms include median filtering and wavelet transforms.4.中值滤波是一种简单且有效的降噪技术。

Median filtering is a simple and effective noise reduction technique.5.小波变换可以将信号分解成不同频率的子信号进行处理。

Wavelet transform can decompose the signal into sub-signals of different frequencies for processing.6.降噪算法的实现需要考虑运算速度和处理效果的平衡。

The implementation of noise reduction algorithm needs to consider the balance between computational speed and processing effect.7.降噪算法的性能评价可以使用信噪比等指标进行量化。

The performance evaluation of noise reduction algorithm can be quantified using metrics such as signal-to-noise ratio.8.自适应滤波是一种根据信号特性进行动态调整的降噪技术。

微生物屏障试验 DIN 58953-6_2010 Test report

Interlaboratory T est …Microbial barrier testing of packa ging materials for medical devices which are tobe ster ili ze d“according to DIN 58953-6:2010Test re portJanuary 2013Author: Daniel ZahnISEGA Forschungs- und Untersuchungsgesellschaft mbHTest report Page 2 / 15Table of contentsSeite1.General information on the Interlaboratory Test (3)1.1 Organization (3)1.2 Occasion and Objective (3)1.3 Time Schedule (3)1.4 Participants (4)2.Sample material (4)2.1 Sample Description and Execution of the Test (4)2.1.1 Materials for the Analysis of the Germ Proofness under Humidityaccording to DIN 58953-6, section 3 (5)2.1.2 Materials for the Analysis of the Germ Proofness with Air Permeanceaccording to DIN 58953-6, section 4 (5)2.2 Sample Preparation and Despatch (5)2.3 Additional Sample and Re-examination (6)3.Results (6)3.1 Preliminary Remark (6)3.2 Note on the Record of Test Results (6)3.3 Comment on the Statistical Evaluation (6)3.4 Outlier tests (7)3.5 Record of Test Results (7)3.5.1 Record of Test Results Sample F1 (8)3.5.2 Record of Test Results Sample F2 (9)3.5.3 Record of Test Results Sample F3 (10)3.5.4 Record of Test Results Sample L1 (11)3.5.5 Record of Test Results Sample L2 (12)3.5.6 Record of Test Results Sample L3 (13)3.5.7 Record of Test Results Sample L4 (14)4.Overview and Summary (15)Test report Page 3 / 15 1. General Information on the Interlaboratory Test1.1 OrganizationOrganizer of the Interlaboratory Test:Sterile Barrier Association (SBA)Mr. David Harding (director.general@)Pennygate House, St WeonardsHerfordshire HR2 8PT / Great BritainRealization of the Interlaboratory Test:Verein zur Förderung der Forschung und Ausbildung fürFaserstoff- und Verpackungschemie e. V. (VFV)vfv@isega.dePostfach 10 11 0963707 Aschaffenburg / GermanyTechnical support:ISEGA Forschungs- u. Untersuchungsgesellschaft mbHDr. Julia Riedlinger / Mr. Daniel Zahn (info@isega.de)Zeppelinstraße 3 – 563741 Aschaffenburg / Germany1.2 Occasion and ObjectiveIn order to demonstrate compliance with the requirements of the ISO 11607-1:2006 …Packaging for terminally sterilized medical devices -- Part 1: Requirements for materials, sterile barrier systems and packaging systems“ validated test methods are to be preferably utilized.For the confirmation of the microbial barrier properties of porous materials demanded in the ISO 11607-1, the DIN 58953-6:2010 …Sterilization – Sterile supply – Part 6: Microbial barrier testing of packaging materials for medical devices which are to be sterilized“ represents a conclusive method which can be performed without the need for extensive equipment.However, since momentarily no validation data on DIN 58953-6 is at hand concerns emerged that the method may lose importance against validated methods in a revision of the ISO 11607-1 or may even not be considered at all.Within the framework of this interlaboratory test, data on the reproducibility of the results obtained by means of the analysis according to DIN 58953-6 shall be gathered.1.3 Time ScheduleSeptember 2010:The Sterile Barrier Association queried ISEGA Forschungs- und Unter-suchungsgesellschaft about the technical support for the interlaboratory test.For the realization, the Verein zur Förderung der Forschung und Ausbildungfür Faserstoff- und Verpackungschemie e. V. (VFV) was won over.November 2010: Preliminary announcement of the interlaboratory test / Seach for interested laboratoriesTest report Page 4 / 15 January toDecember 2011: Search for suitable sample material / Carrying out of numerous pre-trials on various materialsJanuary 2012:Renewed contact or search for additional interested laboratories, respectively February 2012: Sending out of registration forms / preparation of sample materialMarch 2012: Registration deadline / sample despatchMay / June 2012: Results come in / statistical evaluationJuly 2012: Despatch of samples for the re-examinationSeptember 2012: Results of the re-examination come in / statistical evaluationNovember 2012: Results are sent to the participantsDecember 2012/January 2013: Compilation of the test report1.4 ParticipantsFive different German laboratories participated in the interlaboratory test. In one laboratory, the analyses were performed by two testers working independently so that six valid results overall were received which can be taken into consideration in the evaluation.To ensure an anonymous evaluation of the results, each participant was assigned a laboratory number (laboratory 1 to laboratory 6) in random order, which was disclosed only to the laboratory in question. The complete laboratory number breakdown was known solely by the ISEGA staff supporting the proficiency test.2. Sample Material2.1 Sample Description and Execution of the TestUtmost care in the selection of suitable sample material was taken to include different materials used in the manufacture of packaging for terminally sterilized medical devices.With the help of numerous pre-trials the materials were chosen covering a wide range of results from mostly germ-proof samples to germ permeable materials.Test report Page 5 / 15 2.1.1 Materials for the Analysis of Germ Proofness under Humidity according to DIN 58953-6, section 3:The participants were advised to perform the analysis on the samples according to DIN 58953-6, section 3, and to protocol their findings on the provided result sheets.The only deviation from the norm was that in case of the growth of 1 -5 colony-forming units (in the following abbreviated as CFU) per sample, no re-examination 20 test pieces was performed.2.1.2 Materials for the Analysis of Germ Proofness with Air Permeance according to DIN 58953-6, section 4:The participants were advised to perform the analysis on the samples according to DIN 58953-6, section 4, and to protocol their findings on the provided result sheets.2.2 Sample Preparation and DespatchFor the analysis of the germ proofness under humidity, 10 test pieces in the size of 50 x 50 mm were cut out of each sample and heat-sealed into a sterilization pouch with the side to be tested up.Out of the 10 test pieces, 5 were intended for the testing and one each for the two controls according to DIN 58953-6, sections 3.6.2 and 3.6.3. The rest should remain as replacements (e.g. in case of the dropping of a test piece on the floor etc.).For the analysis of the germ proofness with air permeance, 15 circular test pieces with a diameter of 40 mm were punched out of each sample and heat-sealed into a sterilization pouch with the side to be tested up.Test report Page 6 / 15 Out of the 15 test pieces, 10 were intended for the testing and one each for the two controls according to DIN 58953-6, section 4.9. The rest should remain as replacements (e.g. in case of the dropping of a test piece on the floor etc.).The sterilization pouches with the test pieces were steam-sterilized in an autoclave for 15 minutes at 121 °C and stored in an climatic room at 23 °C and 50 % relative humidity until despatch.2.3 Additional Sample and Re-examinationFor the analysis of the germ proofness under humidity another test round was performed in July / August 2012. For this, an additional sample (sample L4) was sent to the laboratories and analysed (see 2.1.2). The results were considered in the evaluation.For validation or confirmation of non-plausible results, occasional samples for re-examination were sent out to the laboratories. The results of these re-examinations (July / August 2012) were not taken into consideration in the evaluation.3. Results3.1 Preliminary RemarkSince the analysis of germ proofness is designed to be a pass / fail – test, the statistical values and precision data were meant only to serve informative purposes.The evaluation of the materials according to DIN58953-6,sections 3.7and 4.7.6by the laboratories should be the most decisive criterion for the evaluation of reproducibility of the interlaboratory test results. Based on this, the classification of a sample as “sufficiently germ-proof” or “not sufficiently germ-proof” is carried out.3.2 Note on the Record of Test Results:The exact counting of individual CFUs is not possible with the required precision if the values turn out to be very high. Thus, an upper limit of 100 CFU per agar plate or per test pieces, respectively, was defined. Individual values above this limit and values which were stated with “> 100” by the laboratories, are listed as 100 CFU per agar plate or per test piece, respectively, in the evaluation.Test report Page 7 / 153.3 Comment on the Statistical EvaluationThe statistical evaluation was done based on the series of standards DIN ISO 5725-1ff.The arithmetic laboratory mean X i and the laboratory standard deviation s i were calculated from the individual measurement values obtained by the laboratories.The overall mean X of the laboratory means as well as the precision data of the method (reproducibility and repeatability) were determined for each sample3.4 Outlier testsThe Mandel's h-statistics test was utilised as outlier test for differences between the laboratory means of the participants.A laboratory was identified as a “statistical outlier” as soon as an exceedance of Mandel's h test statistic at the 1 % significance level was detected.The respective results of the laboratories identified as outliers were not considered in the statistical evaluation.3.5 Record of Test ResultsOn the following pages, the records of the test results for each interlaboratory test sample with the statistical evaluation and the evaluation according to DIN 58953-6 are compiled.Test report Page 8 / 153.5.1 Record of Test Results Sample F1Individual Measurement values:Statistical Evaluation:Comment:Laboratory 4, as an outlier, has not been taken into consideration in the statistical Evaluation.Outlier criterion: Mandel's h-statistics (1 % level of significance)Overall mean X:91.0CFU / agar plateRepeatability standard deviation s r:17.9CFU / agar plateReproducibility standard deviation s R:19.8CFU / agar plateRepeatability r:50.0CFU / agar plateRepeatability coefficient of variation:19.6%Reproducibility R:55.5CFU / agar plateReproducibility coefficient of variation:21.8%Evaluation according to DIN 58953-6, Section 3.7:Lab. 1 - 6:Number of CFU > 5, i.e. the material is classified as not sufficiently germ-proof.Conclusion:All of the participants, even the Laboratory 4 which was identified as an outlier, came to the same results and would classify the sample material as “not sufficiently germ-proof”Test report Page 9 / 153.5.2 Record of Test Results Sample F2Individual Measurement values:Statistical Evaluation:Comment:Laboratory 4, as an outlier, has not been taken into consideration in the statistical Evaluation.Outlier criterion: Mandel's h-statistics (1 % level of significance)Overall mean X:0CFU / agar plateRepeatability standard deviation s r:0CFU / agar plateReproducibility standard deviation s R:0CFU / agar plateRepeatability r:0CFU / agar plateRepeatability coefficient of variation:0%Reproducibility R:0CFU / agar plateReproducibility coefficient of variation:0%Evaluation according to DIN 58953-6, Section 3.7:Lab. 1 – 3:Number of CFU = 0, i.e. the material is classified as sufficiently germ-proofLab. 4:Number of CFU ≤ 5, i.e. a re-examination on 20 test pieces would have to be done Lab. 5 – 6:Number of CFU = 0, i.e. the material is classified as sufficiently germ-proofConclusion:All of the participants, except for the Laboratory 4 which was identified as an outlier, came to the same results and would classify the sample material as “sufficiently germ-proof”.Test report Page 10 / 153.5.3 Record of Test Results Sample F3Individual Measurement values:Statistical Evaluation:Overall mean X:30.1CFU / agar plateRepeatability standard deviation s r:17.2CFU / agar plateReproducibility standard deviation s R:30.9CFU / agar plateRepeatability r:48.2CFU / agar plateRepeatability coefficient of variation:57.1%Reproducibility R:86.5CFU / agar plateReproducibility coefficient of variation:103%Evaluation according to DIN 58953-6, Section 3.7:Lab. 1 - 4:Number of CFU > 5, i.e. the material is classified as not sufficiently germ-proof. Lab. 5:Number of CFU = 0, i.e. the material is classified as sufficiently germ-proof. Lab. 6:Number of CFU > 5, i.e. the material is classified as not sufficiently germ-proof.Conclusion:Five of the six participants came to the same result and would classify the sample as “not sufficiently germ-proof”. Only laboratory 5 would classify the sample material as “sufficiently germ-proof”.Test report Page 11 / 153.5.4 Record of Test Results Sample L1Individual Measurement values:Statistical Evaluation:Overall mean X:0.09CFU / test pieceRepeatability standard deviation s r:0.32CFU / test pieceReproducibility standard deviation s R:0.33CFU / test pieceRepeatability r:0.91CFU / test pieceRepeatability coefficient of variation:357%Reproducibility R:0.93CFU / test pieceReproducibility coefficient of variation:366%Evaluation according to DIN 58953-6, Section 4.7:Lab. 1 - 6:Number of CFU < 15, i.e. the material is classified as sufficiently germ-proof.Conclusion:All participants came to the same result and would classify the sample as “sufficiently germ-proof”.Test report Page 12 / 153.5.5 Record of Test Results Sample L2Individual Measurement values:Statistical Evaluation:Overall mean X:0.73CFU / test pieceRepeatability standard deviation s r: 1.10CFU / test pieceReproducibility standard deviation s R: 1.18CFU / test pieceRepeatability r: 3.07CFU / test pieceRepeatability coefficient of variation:151%Reproducibility R: 3.32CFU / test pieceReproducibility coefficient of variation:163%Evaluation according to DIN 58953-6, Section 4.7:Lab. 1:Number of CFU > 15, i.e. the material is classified as not sufficiently germ-proof. Lab. 2 - 6:Number of CFU < 15, i.e. the material is classified as sufficiently germ-proof.Conclusion:Five of the six participants came to the same result and would classify the sample as “sufficiently germ-proof”. Only laboratory 1 exceeds the limit value slightly by 1 CFU, so that the sample would be classified as “not sufficiently germ-proof”.Test report Page 13 / 153.5.6 Record of Test Results Sample L3Individual Measurement values:Statistical Evaluation:Overall mean X:0.36CFU / test pieceRepeatability standard deviation s r: 1.00CFU / test pieceReproducibility standard deviation s R: 1.06CFU / test pieceRepeatability r: 2.79CFU / test pieceRepeatability coefficient of variation:274%Reproducibility R: 2.98CFU / test pieceReproducibility coefficient of variation:293%Evaluation according to DIN 58953-6, Section 4.7:Lab. 1 - 6:Number of CFU < 15, i.e. the material is classified as sufficiently germ-proof.Conclusion:All participants came to the same result and would classify the sample as “sufficiently germ-proof”.Test report Page 14 / 153.5.7 Record of Test Results Sample L4Individual Measurement values:Statistical Evaluation:Overall mean X:35.1CFU / test pieceRepeatability standard deviation s r:18.8CFU / test pieceReproducibility standard deviation s R:42.6CFU / test pieceRepeatability r:52.7CFU / test pieceRepeatability coefficient of variation:53.7%Reproducibility R:119CFU / test pieceReproducibility coefficient of variation:122%Evaluation according to DIN 58953-6, Section 4.7:Lab. 1 - 3:Number of CFU > 15, i.e. the material is classified as not sufficiently germ-proof. Lab. 4:Number of CFU < 15, i.e. the material is classified as sufficiently germ-proof. Lab. 5 - 6:Number of CFU > 15, i.e. the material is classified as not sufficiently germ-proof.Conclusion:Five of the six participants came to the same result and would classify the sample as“not sufficiently germ-proof”.Test report Page 15 / 15 4. Overview and SummarySummary:In case of four of the overall seven tested materials, a 100 % consensus was reached regarding the evaluation as“sufficiently germ-proof”and“not sufficiently germ-proof”according to DIN 58 953-6.As for the other three tested materials, there were always 5 concurrent participants out of 6 (83 %). In each case, only one laboratory would have evaluated the sample differently.It is noteworthy that the materials about the evaluation of which a 100 % consensus was reached were the smooth sterilization papers. The differences with one deviating laboratory each occurred with the slightly less homogeneous materials, such as with the creped paper and the nonwoven materials.。

英语和汉语对比---抽象与具体

抽象与具体(Abstract vs．Concrete)英语的名词化往往导致表达的抽象化。

G．M．Young曾指出，“an excessive reliance on the noun at the expense of the verb will，in the end，detach the mind of the writer from the realities of here and now, from when and how and in what mood the thing was done．and insensibly induce a habit of abstraction, generalization and vagueness．”英语的抽象表达法(method of abstract diction)主要见于大量使用抽象名词。

这类名词涵义概括，指称笼统，覆盖面广，往往有一种“虚”、“泛”、“暗”、“曲”、“隐”的“魅力”，因而便于用来表达复杂的思想和微妙的情绪。

如：1)The signs of the times point to the necessity of the modification of the system of administration．(“Times”)( =It is becoming clear that the administrative system must be，modified)管理体制需要改革，这已越来越清楚了。

2)No year passes now without evidence of the truth of the statement that the work of government is becoming increasingly difficult．(“Spectator”)(=Every year shows again how true it is that…) 行政管理工作已变得越来越困难了，每年都证明确实如此。

The Statistical Evaluation of the NESSIE Submission Idea NESDOCUIBWP30121

The Statistical Evaluation of the NESSIE Submission Idea∗†NES/DOC/UIB/WP3/012/1H˚avard RaddumDepartment of Informatics,The University of Bergen,N-5020Bergen,NorwayFebruary18,2002AbstractThe purpose of this document is to give a statistical evaluation of the NESSIE submission Idea.For this evaluation,we follow the recommendations of the NESSIE statistical evaluationprocess for blockcipher submissions as described in[Sch01a].1OverviewThe NESSIE submission Idea is a64-bit blockcipher with key length of128bits,submitted by Me-diaCrypt AG.A cipher round uses three operations,XOR,addition modulo216and multiplication modulo216+1.The cipher has eight rounds.This document is organized as follows:The next two sections present the statistical evaluation of the full round version of Idea as well as some statistical evaluation of reduced round versions of the cipher.In the two remaining sections we give the results of the NESSIE streamcipher tests applied to Idea in OFB mode and in counter mode[Sch01b],respectively.2Statistical evaluation of the NESSIE blockcipher Idea with full roundsThe NESSIE evaluation tools for blockciphers consist of the dependence test and the linear factors test.For a detailed introduction to the dependence test and linear factors test,please refer to the documents[Bol90,Dic91].2.1The Dependence TestThe dependence test evaluates the dependence matrix and the distance matrix of the cipher. Furthermore,the degree of completeness,the degree of avalanche eﬀect and the degree of strict avalanche criterion of the cipher are computed.A cryptographic function is complete if each output bit depends on each input bit.For a function to exhibit the avalanche eﬀect,an average of one half of the output bits should change whenever a single input bit is complemented.A function satisﬁes the strict avalanche criterion if each output bit changes with a probability of one half whenever a single input bit is complemented.The exact deﬁnitions of the degree of completeness, the avalanche eﬀect and the strict avalanche criterion can be found in document[Ser00].Due to space constraints,only a fraction of the test output of the dependence test will be presented.∗The work described in this paper has been supported by the Commission of the European Communities through the IST program under contract IST-1999-12324.†The information in this document is provided as is,and no warranty is given or implied that the information isﬁt for any particular purpose.The user thereof uses the information at its sole risk and liability.DEPENDENCE TEST forNESSIE submission blockcipher ideaNumber of inputs:10000Average number of output bits changed:31.993530Degree of completeness: 1.000000Degree of avalanche effect:0.998950Degree of strict avalanche criterion:0.992065ANALYSIS OF THE DISTANCE MATRIXAverage fractions of inputs yielding distance j if one bit is complemented, and the expected fractions for a random functionj01234567 exp.0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000 av.0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000j89101112131415 exp.0.0000000.0000000.0000000.0000000.0000000.0000010.0000030.000009 av.0.0000000.0000000.0000000.0000000.0000000.0000020.0000050.000011j1617181920212223 exp.0.0000260.0000750.0001950.0004730.0010640.0022280.0043560.007954 av.0.0000340.0000770.0001860.0004230.0010380.0022440.0043480.007800 j2425262728293031 exp.0.0135880.0217400.0326110.0458960.0606490.0752880.0878360.096336 av.0.0132840.0217560.0327000.0462700.0610860.0759390.0880310.095506j3233343536373839 exp.0.0993470.0963360.0878360.0752880.0606490.0458960.0326110.021740 av.0.0992330.0966870.0874670.0758340.0606590.0458770.0324730.021459 j4041424344454647 exp.0.0135880.0079540.0043560.0022280.0010640.0004730.0001950.000075 av.0.0134660.0077440.0043560.0021700.0010470.0004950.0001700.000081j4849505152535455 exp.0.0000260.0000090.0000030.0000010.0000000.0000000.0000000.000000 av.0.0000300.0000050.0000030.0000020.0000000.0000000.0000000.000000 j5657585960616263 exp.0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000 av.0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000j64exp.0.000000av.0.000000Application of the Chi-square test to the rows of the distance matrix (%levels of significance)row%row%row%row%row% 189.6275.7390.648.659.8 665.1777.2810.5996.11057.1 1115.61231.81313.91481.01575.8 1622.41733.118 6.6199.22043.821 2.22293.72333.32464.82539.3 2617.12710.628 4.72916.6300.4 3132.33251.83368.23424.33558.9 3611.13779.03864.63973.74018.2 4169.94296.94376.84420.44536.1 4669.44760.14881.84948.25059.0 5113.65230.25353.154 6.85576.8 5617.25774.45833.95936.76028.4 6144.66278.76371.46464.1ANALYSIS OF THE DEPENDENCE MATRIXRow average of the dependence matrixi i i i10.50038620.49913430.50017340.50039250.50024560.49961470.49951180.49981290.499092100.500686110.499200120.500222 130.499200140.500241150.499047160.500705 170.499969180.499227190.498936200.500475 210.499184220.500055230.498967240.500155 250.498411260.500839270.500334280.499956 290.499475300.500164310.500548320.500925 330.500277340.498350350.500388360.499069 370.501498380.500266390.499825400.499513 410.499058420.500069430.499353440.499334 450.500717460.500095470.500420480.500253 490.499670500.499955510.500242520.500731 530.500361540.500266550.500000560.498634 570.499644580.500250590.500358600.499741 610.500831620.499570630.499656640.499855 Column average of the dep.matrixi i i i10.50010820.50010330.50028040.50009250.50022560.49963670.50020680.49938390.499419100.500194110.499975120.500163 130.500338140.500427150.501189160.499236 170.499869180.499919190.500538200.500802210.500433220.499263230.499881240.500298250.500059260.499517270.500103280.499002290.498656300.499923310.500386320.499173330.500933340.499833350.500161360.500106370.500050380.500055390.499581400.500081410.499214420.499869430.500270440.499198450.500303460.500673470.500722480.498398490.499244500.499572510.499267520.500030530.500313540.500114550.499053560.499441570.500248580.499739590.499545600.499705610.499814620.500123630.499622640.499458The test results do not indicate a deviation from random behaviour.2.2The Linear Factors TestThe linear factors test is used toﬁnd out whether there are any linear combinations of output bits which,for all keys and plaintexts,are independent of one or more key or plaintext bits.Such a linear combination is called a linear factor.It is practically impossible to check a potential linear factor for all keys and plaintexts.Therefore,we only consider for a suﬃciently large number of pairs of random keys and random plaintexts[Dic91].For the full round version of the cipher,no linear factors were found.3Statistical evaluation of the NESSIE blockcipher Idea with reduced roundsFor the reduced round tests of the cipher,we checked how many rounds were need for the cipher to be complete,to have a degree of strict avalanche criterion of0.98or higher,and to have no linear factors.We state that the blockcipher Idea•is complete after1round.•has a degree of strict avalanche criterion greater than0.98after4rounds.•reveals no linear factors after3rounds4Evaluation of the NESSIE blockcipher Idea in OFB mode 4.1The Frequency TestThe frequency test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the blocksize of the test.The frequencies of the occurrences of these m-tuples are counted and evaluated statistically.This test is performed for various values of m.Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:1sequencelength=10000000blocksize=1block:0count:5001384block:1count:4998616chisquare=0.766182nu=1Percentage Level of Acceptance:38.14We conclude,that the test results do not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:2sequencelength=10000000blocksize=2block:0count:1251020block:1count:1250308block:2count:1249483block:3count:1249189chisquare= 1.648219nu=3Percentage Level of Acceptance:64.85The test result does not indicate a deviation from random behaviour.Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:3sequencelength=10000000blocksize=3block:0count:417137block:1count:415578block:2count:416696block:3count:416996block:4count:416723block:5count:416345block:6count:416120block:7count:417738chisquare=7.365533nu=7Percentage Level of Acceptance:39.18The test result does not indicate a deviation from random behaviour.Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:4sequencelength=10000000blocksize=4block:0count:156904block:1count:156228block:2count:156621block:3count:155904block:4count:156674block:5count:155964block:6count:156196block:7count:156139block:8count:155731block:9count:156325block:10count:155790block:11count:155944block:12count:156359block:13count:156321block:14count:156605block:15count:156295chisquare=10.800384nu=15Percentage Level of Acceptance:76.66The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:5sequencelength=10000000blocksize=5chisquare=43.657856nu=31Percentage Level of Acceptance: 6.53The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:6sequencelength=10000000blocksize=6chisquare=47.469962nu=63Percentage Level of Acceptance:92.73The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:7sequencelength=10000000blocksize=7chisquare=119.664447nu=127Percentage Level of Acceptance:66.55The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:8sequencelength=10000000blocksize=8chisquare=250.695066nu=255Percentage Level of Acceptance:56.44The test result does not indicate a deviation from random behaviour.Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:12sequencelength=10000000blocksize=12chisquare=4063.937839nu=4095Percentage Level of Acceptance:63.18The test result does not indicate a deviation from random behaviour.Frequency Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:16sequencelength=10000000blocksize=16chisquare=64978.317210nu=65535Percentage Level of Acceptance:93.82The test result does not indicate a deviation from random behaviour.4.2The Collision TestThe collision test splits up the bit sequence into subsequent,disjoint m-tuples of bits.The test evaluates statistically how often such m-tuples occur more than once.Collision Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:24#of blocks:416666blocksize:24collisions:5110For an ideal random number generator,the probability to obtain5110collisions or less is 38.40%.So the test result does not indicate a deviation from random behaviour.4.3The Overlapping m-tuple TestThe overlapping m-tuple test splits up the bit sequence into m-tuples of words.Each word contains aﬁxed number of bits.In the overlapping m-tuple test,the m-tuples are not disjoint;to take the next m-tuple,an m-word-window on the original sequence is shifted by one word.So the next m-tuple consists of m−1shifted words of the previous m-tuple and one new word.Since subsequent m-tuples are not independent,the statistical evaluation is more involved than in the case of the frequency test,but this is handled by the test program.This test is also applied to cyclic shifts of the original sequence.OVERLAPPING M-TUPLE TEST forNESSIE submission blockcipher ideaSequencelength=10000000bits Wordlength=5bitsm=2Shift p--------------013.87%119.37%241.12%376.23%412.55%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.The test result does not indicate a deviation from random behaviour.4.4The Gap TestThe gap test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the word length of the test.The m-tuples are interpreted as binary representations of numbers,and the lengths of gaps,where the numbers are not within a numerical range given as a parameter of the test,are registered and evaluated statistically.The gap test is also applied to cyclic shifts of the original sequence.GAP TEST forNESSIE submission blockcipher ideaSequencelength=10000000bits Wordlength=10bitsLength of gaps between occurences in the range256-768Ideal distribution:mean variance1.0002.000Real distribution:Shift:0123456789--------------------------------------------------------------------------------mean: 1.001 1.001 1.001 1.002 1.000 1.001 1.0010.998 1.002 1.000error:0.14%0.13%0.06%0.19%0.04%0.07%0.14%-0.20%0.18%-0.03%variance: 1.996 2.000 2.007 2.001 2.002 2.006 2.006 2.006 2.006 2.004error:-0.18%-0.01%0.37%0.07%0.10%0.29%0.32%0.28%0.32%0.20% p=65.46%55.82%25.45%13.23%39.97%47.79%91.68%41.26% 2.61%85.03%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.We conclude that the test results do not indicate a deviation from random behaviour.4.5The Run TestThe run test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the word length of the test.The m-tuples are interpreted as binary representations of numbers.The lengths of subsequences of consecutive,strictly increasing numbers are evaluated statistically.Run Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:16Maximal run length registered individually:5Total of230266runs115763runs of length1expected:115134.876305runs of length2expected:76755.328636runs of length3expected:28782.47692runs of length4expected:7674.91576runs of length5expected:1598.8294runs of length6or more expected:319.7chisquare=9.251292nu=5Percentage level of acceptance9.95The test result does not indicate a deviation from random behaviour.4.6The Coupon Collector’s TestThe coupon collector’s test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the word length of the test.In the test,the number of subsequent m-tuples it takes until all possible2m m-tuples have appeared,is evaluated statistically.The coupon collector’s test is also applied to cyclic shifts of the original sequence.COUPON COLLECTOR’S TEST forNESSIE submission blockcipher ideaSequencelength=10000000bits Wordlength=8bitsIdeal distribution:mean variance1567.8323105979.0660Real distribution:The results are for cyclic shiftsShift:01234567------------------------------------------------------------------------mean:1555.1711580.5621565.8631562.7721586.9291577.6291562.6271568.697error:-0.81%0.81%-0.13%-0.32% 1.22%0.62%-0.33%0.06%variance:9809210662210234710200710397810958491124103763error:-7.44%0.61%-3.43%-3.75%-1.89% 3.40%-14.02%-2.09% p= 3.32%80.16%19.33%94.48%18.36%82.01%35.29%73.38%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.The result for shift0is too low,so the test has been repeated.COUPON COLLECTOR’S TEST forNESSIE submission blockcipher ideaSequencelength=10000000bits Wordlength=8bitsIdeal distribution:mean variance1567.8323105979.0660Real distribution:The results are for cyclic shiftsShift:01234567 ------------------------------------------------------------------------mean:1581.7131575.0211569.0441570.1781581.6441566.4861575.9991555.494 error:0.89%0.46%0.08%0.15%0.88%-0.09%0.52%-0.79% variance:1000941006951030189968010558398648101081102500 error:-5.55%-4.99%-2.79%-5.94%-0.37%-6.92%-4.62%-3.28% p=56.76%78.11%39.95%75.84%24.50%26.47%63.36%92.25%This time the test result does not indicate a deviation from random behaviour.4.7The Universal Maurer TestThe universal Maurer test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the blocksize of the test.The test evaluates statistically how many m-tuples later anm-tuple re-appears in the sequence.The test result of the Maurer test is closely related to the entropy of the bit sequence.Maurer Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:1000000Block size:8Initial Blocks=10000blocks tested(including initial blocks):125000Maurer Test Value:7.188279For an ideal random number generator,the probability to obtain a Maurer test value of7.188279or less is92.54%.So the test result does not indicate a deviation from random behaviour.4.8The Poker TestThe poker test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called theword length of the test.The sequence of m-tuples is split up into subsequent,disjoint k-tuples ofm-tuples.The poker test evaluates statistically how many of the m-tuples in a k-tuple are equal.The poker test is also applied to cyclic shifts of the original sequence.POKER TEST forNESSIE submission blockcipher ideaSequencelength=9999360bits Wordlength=8bitsElements in a k-tuple:128Ideal distribution:mean variance100.880113.9923Real distribution:Shift:01234567----------------------------------------------------------------mean:100.962100.888100.916100.871100.903100.876100.899100.915error:0.08%0.01%0.04%-0.01%0.02%-0.00%0.02%0.03%variance:14.15314.17313.66713.83914.22114.34514.18213.758error: 1.15% 1.29%-2.33%-1.10% 1.63% 2.52% 1.36%-1.67% p=15.50%19.83%84.24%88.68%31.35%58.95%78.68%79.78%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.We conclude that the test results do not indicate a deviation from random behaviour.4.9The Fast Spectral TestThe fast spectral test applies the fast Walsh transform to the given sequence.It uses two values derived from the transform to assess the randomness of the sequence.Fast Spectral Test forNESSIE submission blockcipher ideaThe results are:The statistic D(4)=-1.438072E+00;percentage level of significance:7.5%The statistic D(6)=-1.478060E+00;percentage level of significance:7.0% The test result does not indicate a deviation from random behaviour.4.10The Correlation TestThe correlation test determines in how many places the original sequence and the sequence shifted by n bits have the same value.This is done for all shifts n up to the length of the original sequence.To support the interpretation of the results,for each shift the probability for a sequence of random,independent,and uniformly distributed bits to have this number or less coincidences with its shifted copy is determined.Only values where these probabilities are close to0or1are printed.The print level is the maximal deviation from0or1for these probabilities in order to be printed.Correlation Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:1000000Printlevel:0.000010shift:0equal:1000000probability: 1.00000000e+00shift:41843equal:502144probability:0.99999109e-06shift:111456equal:502184probability:0.99999386e-06shift:114853equal:497837probability:0.00000768e-06shift:171487equal:502289probability:0.99999772e-06shift:240139equal:497741probability:0.00000313e-06shift:272650equal:497794probability:0.00000515e-06shift:370432equal:497584probability:0.00000077e-07shift:445581equal:502192probability:0.99999426e-06shift:446724equal:502244probability:0.99999644e-06shift:467054equal:497586probability:0.00000077e-07shift:504584equal:497813probability:0.00000616e-06shift:594135equal:497858probability:0.00000929e-06shift:605247equal:502149probability:0.99999149e-06shift:763214equal:497840probability:0.00000788e-06shift:802925equal:502144probability:0.99999109e-06shift:846351equal:502233probability:0.99999604e-06shift:870403equal:502146probability:0.99999129e-06shift:876408equal:497811probability:0.00000606e-06The test result does not indicate a deviation from random behaviour.4.11The Rank TestIn the rank test,the bits of the sequence to test are used toﬁll square matrices.The bits are treated as elements of theﬁeld GF(2),and the ranks of the matrices are evaluated statistically. Rank test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Order of the matrix:16Number of ranks counted individually:311275matrices with rank16,expected:11280.822490matrices with rank15,expected:22561.35080matrices with rank14,expected:5013.5217matrices with rank13or less,expected:206.4chisquare= 1.651262nu=3Percentage level of acceptance64.78The test result does not indicate a deviation from random behaviour.4.12The Linear Complexity TestThe linear complexity test uses the Berlekamp Massey algorithm to determine the length of the shortest linear feedback shift register which can produce the given bit sequence.For the linear complexity proﬁle,this is done for theﬁrst1,2,3,...bits of the sequence.Some properties of this proﬁle are evaluated.Linear Complexity Test forNESSIE submission blockcipher idea--------------------Final results------------------N=100000L=49999X=5N is the number of input bits.L is the linear complexity.X-1is the number of bits which has been treated sincethe last change of linear complexity.-------------------------End-----------------------The linear complexity profile:Jumps in the linear complexity profile:ssl=99999.000ssqsl=500531.000msl= 3.989varsl= 4.054ssh=49999.000ssqsh=150131.000msh= 1.994varsh= 2.011ssl is the sum of the sl’sssqsl is the sum of the squares of the sl’smsl is the mean of the sl’svarsl is the variance of the sl’sThe number of jumps used in the calculation of msl and varsl is:25069The first sl is not counted because it is0ssh is the sum of the sh’sssqsh is the sum of the squares of the sh’smsh is the mean of the sh’svarsh is the variance of the sh’sThe number of jumps used in the calculation of msh and varsh is:25069maximal step-height17.000000sl is the steplengthsh is the stepheigthnj is the number of jumpsThe test result does not indicate a deviation from random behaviour.4.13The Maximum Order Complexity TestThe maximum order complexity test determines the length of the shortest possibly non-linear feedback shift register which can produce the given bit sequence.For the MOC proﬁle,this is done for theﬁrst1,2,3,...bits of the sequence.The changes in this proﬁle are studied. Maximum Order Complexity(MOC)Test forNESSIE submission blockcipher ideaThe changes in the MOC profile:21( 2.00)75( 5.61)207(8.64)3910(10.57)7111(12.30)13612(14.17)14820(14.42)294826(23.05)1643628(28.01)3476030(30.17)4809734(31.11)20999835(35.36)29411936(36.33)58946637(38.34)72207038(38.92)89286739(39.54)The number of inputcharacters:1000000The number of nodes:1999958The number of edges:2754624The MOC is:39For an ideal random number generator,the probability to obtain a MOC of39or less is63.42%. So the test result does not indicate a deviation from random behaviour.4.14The Ziv Lempel Complexity TestThe Ziv Lempel complexity test measures how well a bit sequence can be reconstructed from earlier parts of the bit sequence.NESSIE submission blockcipher idea1000000input bits of the input file have been handled.The Ziv Lempel complexity equals50749.((1000000/log2(1000000))=50171.665944)A sequence of length n is considered to be a good pseudo-randomsequence if its Ziv Lempel complexity is greater than n/log2(n).The maximum length of a component in the history equals36.(log2(1000000)=19.931569)For an ideal random number generator,the probability to have a Ziv Lempel complexity of 50749or lower is6.87%.So the test result does not indicate a deviation from random behaviour.4.15The Dyadic Complexity TestThe NESSIE dyadic complexity test is an implemenation of the complexity measure suggested by Goretzky and Klapper([KG97])for sequences of bits.This measure is cryptologically relevant because feedback shift registers with carry,also described in[KG97],have low dyadic complexity. The tool is documented in the NESSIE document[Dic01].2-adic Complexity Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000sequencelength=100002-adic complexity=4999.63179For an ideal random number generator,the probability to obtain a dyadic complexity of 4999.63179or less is49.65%.We conclude that the test results do not indicate a deviation from random behaviour.4.16The Percolation TestThe NESSIE percolation test is the simulation of a forestﬁre.The bit sequence to be tested determines where trees are standing in the simulated forest.The test evaluates statistically how fast aﬁre propagates in the simulated forest.The documentation of the test can be found in the NESSIE document[Sch00].PERCOLATION TEST forNESSIE submission blockcipher ideaDimensions of the forest lattice:3Size in dimension1:100Size in dimension2:100Size in dimension3:100Forest fire executed in a triangular lattice.Probability for lighting the reachable neighbours(in percent):100Result(s)of the single fitting in of1forest fire(s):Percentage level(s)of acceptance:34.21%The test result does not indicate a deviation from random behaviour.4.17The Constant Runs TestFor the constant runs test,the sequence of bits is subdivided into maximal subsequences of consec-utive bits with the same value.The frequencies of these runs of the various lengths are evaluated statistically.The tool is documented in the NESSIE document[Ser01].Constant Runs Test forNESSIE submission blockcipher ideaNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Maximal run length registered individually:15Total of25000500-runs12513700-runs of length1expected:1250025.06237840-runs of length2expected:625012.53127130-runs of length3expected:312506.21557260-runs of length4expected:156253.1781730-runs of length5expected:78126.6392650-runs of length6expected:39063.3192830-runs of length7expected:19531.699500-runs of length8expected:9765.848910-runs of length9expected:4882.924810-runs of length10expected:2441.511920-runs of length11expected:1220.75950-runs of length12expected:610.43240-runs of length13expected:305.21660-runs of length14expected:152.6630-runs of length15expected:76.3740-runs of length>=16expected:76.3Total of25000491-runs12496621-runs of length1expected:1250024.5。

英语学术写作核心词汇

英语学术写作核心词汇Academic Writing Core Vocabulary in EnglishIntroductionAcademic writing plays a crucial role in the realm of education, research, and professional communication. To excel in this area, it is essential to develop a solid understanding of the core vocabulary used in English academic writing. This article aims to explore and provide an extensive list of key terms that are frequently used in various academic disciplines.1. AbstractThe abstract is a concise summary of a research paper or article. It provides a brief overview of the study's objective, methodology, findings, and conclusions. An abstract typically ranges from 100 to 250 words and serves as a preview for readers to decide whether the full paper is worth reading.2. IntroductionThe introduction serves to set the context, explain the significance of the study, and state the research question or objective. It provides readers with background information and an understanding of the subject matter under investigation. The introduction should also include a clear thesis statement that outlines the main argument or purpose of the paper.3. Literature ReviewThe literature review critically analyzes and evaluates existing published research and scholarly articles related to the topic of study. It demonstratesthe researcher's familiarity with the current state of knowledge and identifies gaps or areas requiring further investigation. The literature review helps establish the research's novelty, relevance, and importance.4. MethodologyThe methodology section describes the research design, data collection methods, and analytical techniques employed in a study. It provides a detailed account of how the research was conducted to allow for replication and verification by others. Common methodologies include experiments, surveys, interviews, case studies, and archival research.5. ResultsThe results section presents the findings of the study in a clear and organized manner. It often employs tables, graphs, and charts to display data and statistical analysis. The results should be presented objectively and without interpretation, allowing readers to draw their own conclusions.6. DiscussionThe discussion section interprets and analyzes the results, relating them to the research question or objective. It provides an opportunity to delve into the implications, limitations, and practical significance of the findings. The discussion should connect the study with existing literature and propose future research directions.7. ConclusionThe conclusion summarizes the main findings, restates the thesis statement, and highlights the implications of the research. It offers closure tothe paper and suggests avenues for further exploration. The conclusion should be concise, logical, and leave a lasting impression on the reader.8. ReferencesThe references section lists all the sources cited in the paper following a specific citation style such as APA, MLA, or Chicago. It is crucial to accurately cite and provide proper credit to the original authors. This section helps readers locate and verify the information, and also demonstrates the breadth of research undertaken.9. Academic JournalsAcademic journals are scholarly publications that disseminate original research findings in various academic disciplines. They undergo rigorous peer-review processes to ensure the quality and validity of the research presented. Examples of renowned academic journals include Nature, Science, The Journal of Finance, and The Lancet.10. Peer ReviewPeer review is a critical evaluation process in which experts in the field assess the quality and rigor of a manuscript before it is published. It ensures that academic research meets established standards and contributes to the existing body of knowledge. The peer review process helps maintain the integrity and credibility of academic publishing.ConclusionMastering the core vocabulary of English academic writing is essential for effective communication and success in the academic world. This articlehas presented a comprehensive overview of key terms and concepts used in academic writing, ranging from the abstract to the peer review process. By familiarizing oneself with these terms and utilizing them correctly, researchers and scholars can enhance the clarity, precision, and impact of their written work.。

NCCLS_EP6-A定量测量方法的线性评价_中文翻译

EP6-AISBN 1-56238-498-8 Volume 23 Number 16 ISSN 0273-3099Evaluation of the Linearity of Quantitative Measurement Procedures:A Statistical Approach;ApprovedGuidelineEP6-A：定量测量方法的线性评价：一种统计学方法，批准指南NCCLS…通过自愿一致化的方式为世界医学科学团体服务NCCLS是医疗领域一个非赢利性的，不同学科之间，自愿参与的促进标准化和建立指南的教育组织。

NCCLS创建于1968年并获得美国国家标准研究院的认可。

NCCLS所依据的原则是，对病人高质量服务所需的临床实验室检测，自愿一致的标准是必不可少的。

NCCLS通过各临床实验室、检验团体学会、工厂和政府机构的参与而代表临床检验界。

叙述了文件叙述了实验室的程序、常规和参考方法以及评估方案可应用于所有检验学科。

文件审核的一致化过程由一些正式的步骤组成，叙述了NCCLS文件和规范的编制如何发展到被接受为临床实验室标准。

出版物NCCLS文件以标准、指南、委员会报告出版。

标准：通过一致化过程形成的文件，并对材料、方法、或实践以不能修改方式明确规定其特定的基本要求。

此外，标准也可以包含明确规定的选定要素。

指南：通过一致化过程形成的文件，叙述了用于临床检验界的一般实验操作、方法或材料的规范。

使用者可以使用成文文件或修改指南以适应特定的需要。

报告：没有经过一致化审定过程的文件，由理事会颁布。

“标准”一词，除了有特定含义外，还常用来指有关的NCCLS文件。

一致化过程NCCLS的自愿一致化审定程序是一个为以下方面建立正式规范的方案：1.标准项目的权威性2文件的编制和公开评审3根据实验室使用者反馈的评论修改文件4文件被接受为临床实验室标准大多数NCCLS文件必须有“建议”和“批准”两种层次的一致化文件，根据特定的一致化过程，文件也可以有一个中间（“试行”）一致化的水平层次。

英汉语言对比抽象与具体

•
这类名词含义概括，指称笼统，覆盖面广，往往有一种“虚、泛、隐、暗、曲”的魅力，因而便于用来表达复杂的思想和微妙的情绪。
• 1). 管理体制需要改革，这已越来越清楚了。 • It is becoming clear that the administrative system must be modified • The signs of the times point to the necessity of the modification of the system of administration.
• 4) 如果这次买卖可以赚到钱，我打算凑一份。 • in on • If there’s any profit to be got out of the deal, I’m going to be in on it.
• 5)因为乔治向老师报告鲍勃考试作弊，鲍勃就对乔治怀恨在心。 • have it in for somebody • Bob has it in for George because George told the teacher that Bob cheated in the exam.
•
Abstract English
• Main Characteristics: • 1 Norminalization • 2 Preparation
• 1 Norminalization
• 1.1 prefix and suffix • 1.2 lexicalization
• 1）读写能力 • literacy • 2）把---从其所处的环境（语境）中分离出来 • decontextualization • 3）冒险把危急局势推到局限，玩弄边缘政策的手法 • brinkmanship

生态风险评价方法述评_张思锋

基金项目 :国家自然科学基金资助项目 (40771083) 收稿日期 :2009-07-15; 修订日期 :2010-02-25 ＊通讯作者 Correspondingauthor.E-mail:zhangf@

2736
生态学报 2010, 30(10):2735— 2744
A张思锋＊ , 刘晗梦
(西安交通大学公共政策与管理学院 , 西安 710049)
摘要 :生态风险是由环境的自然变化或人类活动引起的生态系统组成、结构的改变而导致系统功能损失的可能性。生态风险评价是定量预测各种风险源对生态系统产生风险的或然性以及评估该风险可接受程度的方法体系 , 因而是生态环境风险管理与决策的定量依据。在介绍了生态风险概念的基础上 , 按照风险源性质的分类标准将生态风险划分为化学污染类风险源、生态事件类风险源、复合类风险源 3类 , 并分别论述了 3类生态风险对应评价方法的特点与发展的方向。另外 , 针对生态风险评价研究的现状 , 讨论了我国生态风险研究的优先领域 , 包括建立急性、慢性毒理数据库 , 构建外来生物入侵风险评价标准等 , 同时 , 建议将综合概率统计学、复杂系统理论与遥感技术等手段引入生态风险评价方法中 , 以进一步提高风险评价结果在生态风险管理中的有效性。关键词 :生态风险评价 ;生态风险评价方法
《露天煤矿区生态风险评价方法》 [ 11]
风险源数量 Thenumberoftherisksources 单一风险源
多风险源
风险受体数量与空间尺度 Thenumberofthe riskreceptorsandspatialscales
单一物种受体、小范围
多物种受体、区域范围

临床检验方法学评价

03
还有一类委员会报告，则是尚未通过一致化过程的文件，编号为R。
04
评价临床方法的文件
美国的国家临床实验室标准委员会（NCCLS）多年来一直致力于制定一系列评价临床方法的文件。 NCCLS是一个全球性、多学科、非营利性的标准化和教育性的团体，旨在促进医疗卫生领域中的标准化进程和应用。它在发展相关的标准和指南时采取了特有的一致化过程（consensus process）。 NCCLS的自愿一致化过程是一个建立正式标准的过程，包括：方案的认可；建立和公开对有关文件的评论；根据使用者的意见修改文件。
EP15-A：精密度和准确度性能的应用核准指南（User Demonstration of Performance for Precision and Accuracy ;Approved Guideline）。
1
2
方法学评价文件（5）
EP17-P：检测单位使用的质量管理提议指南（Quality Management for Unit – Use Testing; Proposed Guideline）。
02
方法学评价文件（2）
EP10-A：定量实验室方法的初步评价核准指南（Preliminary Evaluation of Quantitative Clinical Laboratory Methods; Approved Guideline），提供了用于分析方法和设备操作的初步评价的实验设计和数据分析。
分析方法的选择
我国实验室中使用的分析仪器和试剂，应具有国家药品监督管理局核发的相应文号。
实验室制定的或采用的方法如能满足实验室的预期用途并经过验证，也可以使用。实验室应用自己制定的检测方法的过程应是有计划的活动，应指定足够的、有资格的人员进行。

FDA,GMP,ICH临床实验专业英语词汇互译

FDA,GMP,ICH临床实验专业英语词汇互译FDA,GMP,ICH临床实验专业英语词汇互译FDA常用词中英对照FDA(food and drug adminisration)美国)食品药品监督管理局NDA(new drug application):新药申请ANDA(abbreviated new drug application):简化新药申请EP(export application):出口药申请(申请出口不被批准在美国销售的药品)treatment IND:研究中的新药用于治疗abbreviated(new)drug:简化申请的新药DMF(drug master file):药物主文件(持有者为谨慎起见而准备的保密资料,可以包括一个或多个人用药物在制备,加工,包装和贮存过程中所涉及的设备,生产过程或物品.只有在DMF 持有者或授权代表以授权书的形式授权给FDA,FDA在审查IND, NDA,ANDA时才能参考其内容)holderMF持有者CFR(code of federal regulation)美国)联邦法规PANEL:专家小组batch production:批量生产;分批生产batch production records:生产批号记录post or pre-market surveillance:销售前或销售后监督informed consent:知情同意(患者对治疗或受试者对医疗试验了解后表示同意接受治疗或试验)prescription drug:处方药OTC drug(over—the—counter drug):非处方药U.S. public health service:美国卫生福利部NIH(national institute of health)美国)全国卫生研究所animal trail:动物试验accelerated approval:加速批准standard drug:标准药物investigator :研究人员;调研人员preparing and submitting:起草和申报submission:申报;递交benefit(s):受益risk(s):受害drug product:药物产品drug substance:原料药established name:确定的名称generic name:非专利名称proprietary name:专有名称;INN(international nonproprietary name):国际非专有名称narrative summary: 记叙体概要adverse effect:副作用adverse reaction:不良反应protocol:方案archival copy:存档用副本review copy:审查用副本official compendium:法定药典(主要指USP, NF).USP(the united state pharmacopeia):美国药典(现已和NF合并一起出版)NF(national formulary)美国)国家药品集official=pharmacopeial = compendial:药典的;法定的;官方的agency:审理部门(指FDA)sponsor:主办者(指负责并着手临床研究者)identity:真伪;鉴别;特性strength:规格;规格含量(每一剂量单位所含有效成分的量)labeled amount:标示量regulatory specification:质量管理规格标准(NDA提供)regulatory methodology:质量管理方法(FDA用于考核原料药或药物产品是否符合批准了的质量管理规格标准的整套步骤)regulatory methods validation:管理用分析方法的验证(FDA对NDA提供的方法进行验证)Dietary supplement:食用补充品ICH(International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use)人用药物注册技术要求国际协调会议ICHuality-质量Q1A(R2): Stability Testing of New Drug Substances and Products (Second Revision)新原料药和制剂的稳定性试验(第二版)Q1B: Photostability Testing of New Drug Substances and Products新原料药和制剂的光稳定性试验Q1C: Stability Testing for New Dosage Forms新制剂的稳定性试验Q1D: Bracketing and Matrixing Designs for Stability Testing of Drug Substances and Drug Products原料药和制剂稳定性试验的交叉和矩阵设计Q1E: Evaluation of Stability Data对稳定性数据的评估处理Q1F: Stability Data Package for Registration Applications in Climatic Zones III and IV在气候带III和IV,药物注册申请所提供的稳定性数据Q2A: Text on Validation of Analytical Procedures分析程序的验证Q2B: Validation of Analytical Procedures: Methodology分析程序的验证:方法学Q3A(R): Impurities in New Drug Substances (Revised Guideline)新原料药中的杂质(修订版)Q3B(R): Impurities in New Drug Products (Revised Guideline)新制剂中的杂质(修订版)Q3C: Impurities: Guideline for Residual Solvents杂质:残留溶剂指南Q3C(M): Impurities: Guideline for Residual Solvents (Maintenance)杂质:残留溶剂指南(修改内容)Q4: Pharmacopoeias药典Q4A: Pharmacopoeial Harmonisation 药典的协调Q4B: Regulatory Acceptance of Pharmacopoeial Interchangeability药典互替在法规上的可接受性Q5A: Viral Safety Evaluation of Biotechnology Products Derived from Cell Lines of Human or Animal Origin来源于人或者动物细胞系的生物技术产品的病毒安全性评估Q5B: Quality of Biotechnological Products: Analysis of the Expression Construct in Cells Used for Production of r-DNA Derived Protein Products生物技术产品的质量:源于重组DNA的蛋白质产品的生产中所用的细胞中的表达构建分析Q5C: Quality of Biotechnological Products: Stability Testing of Biotechnological/Biological Products生物技术产品的质量:生物技术/生物产品的稳定性试验Q5D: Derivation and Characterisation of Cell Substrates Used for Production of Biotechnological/Biological Products用于生产生物技术/生物产品的细胞底物的起源和特征描述Q5E: Comparability of Biotechnological/Biological Products Subject to Changes in Their Manufacturing Process基于不同生产工艺的生物技术产品/生物产品的可比较性Q6: Specifications for New Drug Substances and Products新原料药和制剂的质量规格Q6A: Specifications: Test Procedures and Acceptance Criteria for New Drug Substances and New Drug Products: Chemical Substances质量规格:新原料药和新制剂的检验程序和可接收标准:化学物质Q6B: Specifications: Test Procedures and Acceptance Criteria for Biotechnological/Biological Products质量规格:生物技术/生物产品的检验程序和可接收标准-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:34:00--Q7: Good Manufacturing Practices for Pharmaceutical Ingredients活性药物成份的GMPQ7A: Good Manufacturing Practice Guide for Active Pharmaceutical Ingredients活性药物成份的GMP指南Q8: Pharmaceutical Development药物研发Q9: Quality Risk Management质量风险管理ICH:Safety-安全S1A: Guideline on the Need for Carcinogenicity Studies of Pharmaceuticals药物致癌性研究需要的指南S1B: Testing for Carcinogenicity of Pharmaceuticals药物致癌性的检验S1C: Dose Selection for Carcinogenicity Studies of Pharmaceuticals药物致癌性研究之剂量选择S1C(R): Addendum: Addition of a Limit Dose and Related Notes附录:极限剂量和有关注释的的补充S2A: Guidance on Specific Aspects of Regulatory Genotoxicity Tests for Pharmaceuticals受法规管辖的药物基因毒性检验的特定方面的指南S2B: Genotoxicity: A Standard Battery for Genotoxicity Testing for Pharmaceuticals 基因毒性:药物基因毒性检验的标准S3A: Note for Guidance on Toxicokinetics: The Assessment of Systemic Exposure in Toxicity Studies毒物代谢动力学指南的注释:毒性研究中的全身性暴露量的评估S3B: Pharmacokinetics: Guidance for Repeated Dose Tissue Distribution Studies药物代谢动力学:重复剂量的组织分布研究指南S4: Single Dose Toxicity Tests单剂量毒性检验S4A: Duration of Chronic Toxicity Testing in Animals (Rodent and Non-Rodent Toxicity Testing)动物体内慢性毒性持续时间的检验(啮齿动物和非啮齿动物毒性检验)S5A: Detection of Toxicity to Reproduction for Medicinal Products药物对生殖发育的毒性的检验S5B(M): Maintenance of the ICH Guideline on Toxicity to Male Fertility: An Addendum to the Guideline on Detection of Toxicity to Reproduction for Medicinal Products 对男性生殖能力的毒性的指南的变动:药物对生殖发育的毒性的检验指南增加了一个附录S6: Preclinical Safety Evaluation of Biotechnology-Derived Pharmaceuticals生物技术生产的药物的临床前安全评价S7A: Safety Pharmacology Studies for Human Pharmaceuticals人用药的安全药理学研究S7B: The Nonclinical Evaluation of the Potential for Delayed Ventricular Repolarization(QT Interval Prolongation) By Human Pharmaceuticals药物延迟心室复极化(QT间期)潜在作用的非临床评价S8: Immunotoxicology Studies for Human Pharmaceuticals人用药免疫毒理学研究M3(M): Maintenance of the ICH Guideline on Non-Clinical Safety Studies for the Conduct of Human Clinical Trials for Pharmaceuticals药物的对人临床试验的非临床安全研究指南的变动E-Efficacy(有效)E1: The Extent of Population Exposure to Assess Clinical Safety for Drugs Intended for Long-Term Treatment of Non-Life-Threatening Conditions对用于无生命危险情况下长期治疗的药物进行临床安全评估的族群暴露量范围E2A: Clinical Safety Data Management: Definitions and Standards for Expedited Reporting临床安全数据管理:速报制度的定义和标准E2B(R): Revision of the E2B(M) ICH Guideline on Clinical Safety Data Management Data Elements for Transmission of Individual Case Safety Reports个案安全报告送交的临床安全数据管理的数据要素指南(E2B(M))的修订版E2B (M): Maintenance of the Clinical Safety Data Management including: Data Elements for Transmission of Individual Case Safety Reports临床安全数据管理的变动包括:个案安全报告送交的数据要素E2B(M): Maintenance of the Clinical Safety Data Management including Questions and Answers临床安全数据管理的变动,包括问答E2C: Clinical Safety Data Management: Periodic Safety Update Reports for Marketed Drugs临床安全数据管理:已上市药品的周期性安全数据更新报告Addendum to E2C: Periodic Safety Update Reports for Marketed DrugsE2C的附录:已上市药品的周期性安全数据更新报告E2D: Post-Approval Safety Data Management: Definitions and Standards for Expedited Reporting批准后的安全数据管理:速报制度的定义和标准E2E: Pharmacovigilance Planning药物警戒计划E3: Structure and Content of Clinical Study Reports临床研究报告的结构和内容E4: Dose-Response Information to Support Drug Registration支持药品注册的剂量-效应资料E5: Ethnic Factors in the Acceptability of Foreign Clinical Data引入海外临床数据时要考虑的人种因素E6: Good Clinical Practice: Consolidated GuidelineGCP:良好的临床规范:统一的指南E7: Studies in Support of Special Populations: Geriatrics对特定族群的支持的研究:老人病学E8: General Considerations for Clinical Trials对临床试验的总的考虑E9: Statistical Principles for Clinical Trials临床试验的统计原则E10: Choice of Control Group and Related Issues in Clinical Trials临床试验中控制组和有关课题的选择E11: Clinical Investigation of Medicinal Products in the Pediatric Population小儿科药物的临床调查E12A: Principles for Clinical Evaluation of New Antihypertensive Drugs新抗高血压药物的临床评价原则E14: The Clinical Evaluation of QT/QTc Interval Prolongation and Proarrhythmic Potential for Non-Antiarrhythmic Drugs非抗心率失常药物的QT/QTc 间期和致心率失常潜在作用的临床评价Multidisciplinary Guidelines 多学科兼容的指南M1: Medical Terminology医学术语M2: Electronic Standards for Transmission of Regulatory Information (ESTRI)药政信息传递之电子标准M3: Timing of Pre-clinical Studies in Relation to Clinical Trials (See Safety Topics)有关临床试验的临床前研究的时间安排M4: The Common Technical Document (See CTD section for complete Status of the guidelines)通用技术文件(见有关CTD章节)M5: Data Elements and Standards for Drug Dictionaries药物词典的数据要素和标准临床试验常用的英文缩略语TTP: time-to-progression 疾病进展时间SAE: severity Adverse Event 严重不良事件AE: Adverse Event 不良事件-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:34:00--SOP: Standard Operating Procedure 标准操作规程CRF: Case Report form 病例报告表DLT: 剂量限制毒性MTD: 最大耐受剂量KPS: Karnofsky Performance Status行为状态评分CR: complete response完全缓解PR: partial response部分缓解SD: 病情稳定PD: progressive disease病情进展CTC: 常用药物毒性标准IEC: independent ethics committee 独立伦理委员会IRB : institutional review board 伦理委员会CRA: 临床研究助理CRO: Contract Research Organization 合同研究组织DFS: Disease Free Survival 无病生存期OS: (Overall Survival) 总生存时间IC: Informed consent 知情同意ADR: Adverse Drug Reaction 不良反应GAP:Good Agricultural Practice 中药材种植管理规范GCP:Good Clinical Practice 药物临床试验质量管理规范GLP:Good Laboratory Practice 药品实验室管理规范GMP:Good Manufacturing Practice 药品生产质量管理规范GSP:Good Supply Practice 药品经营质量管理规范GUP:Good Use Practice 药品使用质量管理规范PI rincipal investigator 主要研究者CI: Co-inveatigator 合作研究者SI :Sub-investigator 助理研究者COI :Coordinating investigtor 协调研究者DGMP: 医疗器械生产质量管理规范ICF: Informed consent form 知情同意书RCT : randomized controlled trial, 随机对照试验NRCCT: non-randomized concurrent controlled trial, 非随机同期对照试验EBM: evidence-based medicine 循证医学RCD: randomized cross-over disgn 随机交叉对照试验HCT: historial control trial, 历史对照研究RECIST: Response Evaluation Criteria In Solid Tumors. 实体瘤疗效反应的评价标准QC: Quality Control质量控制UADR: Unexpected Adverse Drug Reaction,非预期药物不良反应-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:34:00--GMP英语PIC/S的全称为harmaceutical Inspection Convention/Pharmaceutical Inspection Cooperation Scheme, PIC/S(制药检查草案), 药品检查协会(PIC/S) ,也有人称PIC/S为医药审查会议/合作计划(PIC/S)PIC的权威翻译:药品生产检查相互承认公约API(Active Pharmaceutical Ingrediet) 原料药又称:活性药物组分AirLock 气闸Authorized Person 授权人Batch/Lot 批次Batch Number/Lot-Number 批号;Batch Numbering System 批次编码系统;Batch Records 批记录;Bulk Product 待包装品;Calibration 校正;Clean area洁净区;Consignmecnt(Delivery)托销药品.ABPI Association of the British Pharmaceutical IndustryADR Adverse Drug ReactionAE Adverse EventAIM Active Ingredient ManufacturerANDA Abbreviated New Drug ApplicationANOVA Analysis of VarianceASM: Active Substance ManufacturerATC Anatomical Therapeutic ChemicalATX Animal Test Exemption CertificateBANBritish Approved NameBIRABritish Institute of Regulatory AffairsBNF British National FormularyBP British PharmacopoeiaC of A Certificate of AnalysisC of S Certificate of SuitabilityCENTRE FOR DRUG EVALUATION (CDE)Centre for Pharmaceutical Administration (CPA)CMS Concerned Member StateCMS每个成员国COS Certificate of SuitabilityCPMP Committee for Proprietary Medicinal ProductsCRA Clinical Research AssociateCRF Case Report FormCRO Contract Research OrganisationCTA Clinical Trial ApplicationCTC Clinical Trial CertificateCTD Common Technical DocumentCTX Clinical Trials ExemptionDDD Defined Daily DoseDGC Daily Global ComparisonDIA Drug Information AssociationDMF Drug Master FileDrug Registration Branch (DR, Product Evaluation & Registration Division, CPA EDQM (European Directorate for the Quality of Medicines) 欧洲联盟药品质量指导委员会EEA 欧洲经济地区EGMA European Generics Medicine AssociationELA Established Licence ApplicationEMEA European Medicines Evaluation AgencyEMEA (European Agency for the Evaluation of Medicinal Products) 欧洲联盟药品评价机构EP European PharmacopoeiaEPAR European Public Assessment ReportsESRA European Society of Regulatory AffairsEuropean Pharmacopoeia Commission 欧洲药典委员会FDA Food and Drug Administrationfinal evaluation report (FER)free sale certificates (FSCs)Health Sciences Authority (HSA)HSA's Medicines Advisory Committee (MAC)IB Investigators BrochureICH International Conference for HarmonisationIDMC Independent Data-Monitoring CommitteeIEC Independent Ethics CommitteeIND Investigational New DrugINN International Non-proprietary NameInternational Conference on Harmonisation (ICH)IPC In Process ControlIRB Institutional Review BoardLICENCE HOLDERMA Marketing AuthorisationMAA Marketing Authorisation ApplicationMAA上市申请MAH Marketing Authorisation HolderMAH 销售许可持有者MCA Medicines Control AgencyMHW Ministry of Health and Welfare (Japan)MR Mutual RecognitionMRA 美国与欧盟的互认协议MRAs (Mutual Recognition Agreements) 互相认证同意MRFG Mutual Recognition Facilitation Group MRPMutual Recognition ProcedureNASNew Active SubstanceNCENew Chemical EntityNDANew Drug Applicationnew chemical entities (NCEs)new drug applications (NDAs)NSAID Non Steroidal Anti Inflammatory DrugNTA Notice To ApplicantsOOS Out of SpecificationOTC Over The CounterPAGB Proprietary Association of Great BritainPh Eur European PharmacopoeiaPIL Patient Information LeafletPL Product LicencePOM Prescription Only MedicinePRODUCT OWNERPSU Periodic Safety UpdatesQA Quality AssuranceQC Quality ControlRAJ Regulatory Affairs JournalRMS Reference Member StateRMS相互认可另一成员国RSD Relative Standard DeviationRx Prescription OnlySAE Serious Adverse EventSMF Site Master FileSOP Standard Operating ProcedureSOP (STANDARD OPERATION PROCEDURE) 标准运作程序SPC/SmPC Summary of Product Characteristics summary of product characteristics(SPC)Therapeutic Goods Administration (TGA)USP US PharmacopoeiaVMF Veterinary Master FileVPC Veterinary Products CommitteeA.A.A Addition and Amendments 增补和修订AC Air Conditioner 空调器ADR Adverse Drug Reaction 药物不良反应AFDO Association of Food and Drug Officials 食品与药品官员协会(美国) ACC Accept 接受AQL Acceptable Quality Level 合格质量标准ADNA Abbreviated New Drug Application 简化的新药申请BOM Bill of Material 物料清单BPC Bulk pharmaceutical Chemiclls 原料药CBER Center for Biologics Evaluation Research 生物制品评价与研究中心CFU Colony Forming Unet 菌落形成单位DMF Drug Master File 药品管理档案CDER Cemter for Drug Evaluation amd Research 药物评价与研究中心CI Corporate Identity (Image) 企业识别(形象)CIP Cleaning in Place 在线清洗CSI Consumer Safety Insepctor 消费者安全调查员CLP Cleaning Line Procedure 在线清洗程序DAL Defect Action Level 缺陷作用水平DEA Drug Enforcement Adminestration 管制药品管理DS Documentation Systim 文件系统FDA Food and Drug Administration 食品与药品管理局(美国)GATT General Agreemernt on Tariffs and Trade 关贸总协会GMP Good Manufacturing Practice Gvp 药品生质量管理规范GCP Good Clinical Practice 药品临床实验管理规范GLP Good Laboratory Practice 实验室管理规范GSP Good Supply Practice 药品商业质量规范GRP Gook RaTAIL Practice 药品零业质量管理规范GAP Good Agriculture Practice 药材生产管理规范GVP Gook Validation Prctice 验证管理规范GUP Gook Use Practice 药品重用规范HVAC Heating Ventilation Air Conditioning 空调净化系统ISO Intematonal Organization for Standardization 车际标准化组织MOU Memorandum of Understanding 谅解备忘录PF Porduction File 生产记录用表格OTC Over the Counter (Drug) 非处方药品PLA Product License Application 产品许可申请QA Quality Assurance 质量保证QC Quality Control 质量控制QMP Quality Management Procedure 质量管理程序SDA State Drug Administration 国家药品监督管理局SMP Standard Managmert Procedure 标准管理程序SOP Standard Operating Procedure 标准操作程序TQC Tatal Quality Control 全面质量管理USA Uneted States Pharmacopeia 美国药典-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:35:00--ICH 安全性领域常用专业术语中英文对照表Dead offspring at birth 出生时死亡的子代Degradation 降解 Delay of parturition 分娩延迟Deletion 缺失 Descriptive statistics 描述性统计 Distribution 分布Detection of bacterial mutagen 细菌诱变剂检测 Detection of clastogen 染色体断裂剂检测Determination of metabolites 测定代谢产物 Development of the offspring 子代发育Developmental toxicity 发育毒性 Diminution of the background lawn 背景减少Direct genetic damage 直接遗传损伤DNA adduct DNA加合物 DNA damage DNA损伤DNA repair DNA修复 DNA strand breaks DNA链断裂Dose escalation 剂量递增 Dose dependence 剂量依赖关系 Dose level 剂量水平Dose-limiting toxicity 剂量限制性毒性 Dose-raging studies 剂量范围研究Dose-relatived mutagenicity 剂量相关性诱变性 Dose-related 剂量相关Dose-relatived cytotoxicity 剂量相关性细胞毒性Dose-relatived genotoxic activity 剂量相关性遗传毒性Dose-response curve 剂量-反应曲线 Dosing route 给药途径Duration 周期 Duration of pregnancy 妊娠周期Eaning 断奶 Earlier physical malformation 早期躯体畸形Early embryonic development 早期胚胎发育Early embryonic development to implantation 着床早期的胚胎发育Electro ejaculation 电射精Elimination 清除Embryofetal deaths 胚胎和胎仔死亡 Embryo-fetal development 胚胎-胎仔发育Embryo-fetal toxicity 胚胎-胎仔毒性 Embryonic death 胚胎死亡Embryonic development 胚胎发育 Embryonic period 胚胎期Embryos 胚胎 Embryotoxicity 胚胎毒性Enantiomer 对映异构体End of pregnancy 怀孕终止 Endocytic 内吞噬(胞饮)Endocytic activity 内吞噬活性 Endogenous proteins 内源性蛋白Endogenous components 内源性物质 Endogenous gene 内源性基因Endonuclease 核酸内切酶 Emdpmiclease release from lysosomes 溶酶体释放核酸内切酶End-point 终点Epididymal sperm maturation 附睾精子成熟性 Epitope 抗原决定部位Error prone repair 易错性修复 Escalation 递增Escherichia coli strain 大肠杆菌菌株 Escherichia coli 大肠杆菌Evaluation of test result 试验结果评价Exaggerated pharmacological response 超常增强的药理作用Excretion 排泄(清除) Exposure assessment 接触剂量评价Exposure period 接解期 External metabolizing system 体外代谢系统F1-animals 子一代动物False positive result 假阳性结果Fecundity 多产 Feed-back 反馈 Fertilisation 受精 Fertility 生育力Fertility studies 生育力研究 Fetal abnormalities 胎仔异常Fetal and neonatal parameters 胎仔和仔鼠的生长发育参数Fetal development and growth 肿仔发育和生长 Fetal period 胎仔期 Fetotoxicity 胎仔毒性False negative result 假阴性结果First pass testing 一期试验Fluorescence in situ hybridization(FISH) 原位荧光分子杂交-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:35:00--average deviation 平均差Bbar chart 直条图,条图bias 偏性binomial distribution 二项分布biometrics 生物统计学bivariate normal population 双变量正态总体Ccartogram 统计图case fatality rate(or case mortality) 病死率census 普查chi-sguare(X2) test 卡方检验central tendency 集中趋势class interval 组距classification 分组,分类cluster sampling 整群抽样coefficient of correlation 相关系数coefficient of regression 回归系数coefficient of variability(or coefficieut of variation) 变异系数collection of data 收集资料column 列(栏)combinative table 组合表combined standard deviation 合并标准差combined variance(or poolled variance) 合并方差complete survey 全面调查completely correlation 完全相关completely random design 完全随机设计confidence level 可信水平,置信水平confidence limit 可信限,置信限constituent ratio 构成比,结构相对数continuity 连续性control 对照control group 对照组coordinate 坐标correction for continuity 连续性校正correction for grouping 归组校正correction number 校正数correction value 校正值correlation 相关,联系correlation analysis 相关分析correlation coefficient 相关系数critical value 临界值cumulative frequency 累积频率Ddata 资料degree of dispersion 离散程度degree of freedom 自由度degree of variation 变异度dependent variable 应变量design of experiment 实验设计deviation from the mean 离均差diagnose accordance rate 诊断符合率difference with significance 差别不显著difference with significance 差别显著discrete variable 离散变量dispersion tendency 离中趋势distribution 分布,分配-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:35:00--Eeffective rate 有效率eigenvalue 特征值enumeration data 计数资料equation of linear regression 线性回归方程error 误差error of replication 重复误差estimate value 估计值event 事件experiment design 实验设计experiment error 实验误差experimental group 实验组extreme value 极值Ffatality rate 病死率field survey 现场调查fourfold table 四格表freguency 频数freguency distribution 频数分布GGaussian curve 高斯曲线geometric mean 几何均数grouped data 分组资料Hhistogram 直方图homogeneity of variance 方差齐性homogeneity test of variances 方差齐性检验hypothesis test 假设检验hypothetical universe 假设总体Iincidence rate 发病率incomplete survey 非全面调检indepindent variable 自变量indivedual difference 个体差异infection rate 感染率inferior limit 下限initial data 原始数据inspection of data 检查资料intercept 截距interpolation method 内插法interval estimation 区间估计inverse correlation 负相关Kkurtosis coefficient 峰度系数Llatin sguare design 拉丁方设计least significant difference 最小显著差数least square method 最小平方法,最小乘法leptokurtic distribution 尖峭态分布leptokurtosis 峰态,峭度linear chart 线图linear correlation 直线相关linear regression 直线回归linear regression eguation 直线回归方程link relative 环比logarithmic normal distribution 对数正态分布logarithmic scale 对数尺度lognormal distribution 对数正态分布lower limit 下限Mmatched pair design 配对设计mathematical statistics 数理统计(学) maximum value 极大值mean 均值mean of population 总体均数mean square 均方mean variance 均方,方差measurement data 讲量资料median 中位数medical statistics 医学统计学mesokurtosis 正态峰method of least squares 最小平方法,最小乘法method of grouping 分组法method of percentiles 百分位数法mid-value of class 组中值minimum value 极小值mode 众数moment 动差,矩morbidity 患病率mortality 死亡率Nnatality 出生率natural logarithm 自然对数negative correlation 负相关negative skewness 负偏志no correlation 无相关non-linear correlation 非线性相关non-parametric statistics 非参数统计normal curve 正态曲线normal deviate 正态离差normal distribution 正态分布normal population 正态总体normal probability curve 正态概率曲线normal range 正常范围normal value 正常值normal kurtosis 正态峰normality test 正态性检验nosometry 患病率-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:35:00--Oobserved unit 观察单位observed value 观察值one-sided test 单测检验one-tailed test 单尾检验order statistic 顺序统计量ordinal number 秩号ordinate 纵坐标Ppairing data 配对资料parameter 参数percent 百分率percentage 百分数,百分率percentage bar chart 百分条图percentile 百分位数pie diagram 园图placebo 安慰剂planning of survey 调查计划point estimation 点估计population 总体,人口population mean 总体均数population rate 总体率population variance 总体方差positive correlation 正相关positive skewness 正偏态prevalence rate 患病率probability 概率,机率probability error 偶然误差proportion 比,比率prospective study 前瞻研究prospective survey 前瞻调查public health statistics 卫生统计学Qquality eontrol 质量控制quartile 四分位数Rrandom 随机random digits 随机数字random numbers table 随机数目表random sample 随机样本random sampling 随机抽样random variable 随机变量randomization 随机化randomized blocks 随机区组,随机单位组randomized blocks analysis of variance 随机单位组方差分析randomized blocks design 随机单位组设计randomness 随机性range 极差,全距range of normal values 正常值范围rank 秩,秩次,等级rank correlation 等级相关rank correlation coefficent 等级相关系数rank-sum test 秩和检验ranked data 等级资料rate 率ratio 比recovery rate 治愈率registration 登记regression 回归regression analysis 回归分析regression coefficient 回归系数regression eguation 回归方程relative number 相对数relative ratio 比较相对数relative ratio with fixed base 定基比remainder error 剩余误差replication 重复retrospective survey 回顾调查Ridit analysis 参照单位分析Ridit value 参照单位值Ssample 样本sample average 样本均数sample size 样本含量sampling 抽样sampling error 抽样误差sampling statistics 样本统计量sampling survay 抽样调查scaller diagram 散点图schedule of survey 调查表semi-logarithmic chart 半对数线图semi-measursement data 半计量资料semi-guartile range 四分位数间距sensitivity 灵敏度sex ratio 性比例sign test 符号检验significance 显著性,意义significance level 显著性水平significance test 显著性检验significant difference 差别显著simple random sampling 单纯随机抽样simple table 简单表size of sample 样本含量skewness 偏态slope 斜率sorting data 整理资料sorting table 整理表sources of variation 变异来源square deviation 方差standard deviation(SD) 标准差standard error (SE) 标准误standard error of estimate 标准估计误差standard error of the mean 均数的标准误standardization 标准化standardized rate 标化率standardized normal distribution 标准正态分布statistic 统计量statistics 统计学statistical induction 统计图statistical inference 统计归纳statistical map 统计推断statistical method 统计地图statistical survey 统计方法statistical table 统计调查statistical test 统计表statistical treatment 统计检验stratified sampling 统计处理stochastic variable 分层抽样sum of cross products of 随机变量deviation from mean 离均差积和sum of ranks 秩和sum of sguares of deviation from mean 离均差平方和superior limit 上限survival rate 生存率symmetry 对称(性)systematic error 系统误差systematic sampling 机械抽样-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:35:00--Tt-distribution t分布t-test t检验tabulation method 划记法test of normality 正态性检验test of one-sided 单侧检验test of one-tailed 单尾检验test of significance 显著性检验test of two-sided 双侧检验test of two-tailed 双尾检验theoretical frequency 理论频数theoretical number 理论数treatment 处理treatment factor 处理因素treatment of date 数据处理two-factor analysis of variance 双因素方差分析two-sided test 双侧检验two-tailed test 双尾检验type I error 第一类误差type II error 第二类误差typical survey 典型调查Uu test u检验universe 总体,全域ungrouped data 未分组资料upper limit 上限Vvariable 变量variance 方差,均方variance analysis 方差分析variance ratio 方差比variate 变量variation coefficient 变异系数velocity of development 发展速度velocity of increase 增长速度Wweight 权数weighted mean 加权均数Zzero correlation 零相关-- 作者:月萝兰魂-- 发布时间:2006-12-22 13:36:00--世界500强制药企业名称中英对照排名公司名称中文名称总部收入百万美元77 Pfizer 辉瑞美国 45950.092 Johnson & Johnson 强生美国 41862.0114 GlaxoSmithKline 葛兰素史克英国 35050.9193 Novartis 诺华瑞士 24864.0205 Roche Group 罗氏瑞士 23212.9222 Merck 默克美国 22485.9239 Bristol-Myers Squibb 百时美施贵宝美国 20894.0 248 Aventis 安万特法国 20162.4254 Abbott Laboratories 雅培美国 19680.6269 AstraZeneca 阿斯利康英国 18849.0330 Wyeth 惠氏美国 15850.6433 Eli Lilly 礼来大药厂美国 12582.5100 BASF 巴斯夫德国 37757.0125 Dow Chemical 道化学美国 32632.0129 Bayer 拜耳德国 32331.1365 Akzo Nobel 阿克苏诺贝尔荷兰 14770.7。

基于不同年龄女性体型差异的东华原型修正

基于不同年龄女性体型差异的东华原型修正王朝晖;任双佳【摘要】东华原型是基于年轻女性测体数据建立的女装基础纸样.为进一步完善东华原型,扩大其适用范围,对华东地区310名18 ～40岁的女性进行了三维人体测量,根据年龄将被测者分为18～24岁、25～30岁、31～35岁以及36 ～40岁4组,并对4组人群23个部位的测体数据进行统计分析,经单因素方差分析揭示了不同年龄段女性体型的差异及变化规律.通过回归分析,调整了东华原型的制图公式以反映不同年龄体型的差异.样衣评价结果显示修正后的原型改善效果良好.%As the basic pattern of female garment, Donghua's basic pattern has been developed based on the data base established according to the body measurements from young women. For the purposes of perfecting the basic pattern and widening its scope of application, this survey carried out a 3-D body scanning of 310 female subjects aged from 18 to 40 from East China, and they were divided into 4 age groups: 18-24, 25-30, 31-35, and 36-40. The statistical analysis of the data of measurements from 23 body parts of these subjects was performed, and single element ANOVA was conducted to reveal the difference in types of body of females from different ages and their change rule. Then, the regression equations were revised by adjusting regression constants for different age groups. The evaluation results showed that the sample produced by revised basic pattern has a good fit.【期刊名称】《纺织学报》【年(卷),期】2011(032)009【总页数】5页(P95-99)【关键词】体型;三维人体测量;服装原型;线性回归;服装结构【作者】王朝晖;任双佳【作者单位】东华大学服装·艺术设计学院,上海200051;东华大学服装·艺术设计学院,上海200051【正文语种】中文【中图分类】TS941.2女性在不同年龄段体型特征有明显差异。

产品质量检验英语

产品质量检验英语English:In product quality inspection, it's crucial to establish a comprehensive and systematic approach to ensure the consistency and reliability of the evaluation process. This begins with defining clear quality standards and criteria tailored to the specific product and industry requirements. Utilizing various inspection techniques such as visual inspection, dimensional measurement, functional testing, and destructive testing helps in uncovering defects and deviations from the set standards. Moreover, implementing statistical sampling methods like random sampling or stratified sampling allows for efficient and representative evaluation of large batches of products. Alongside, incorporating quality control checkpoints at different stages of production aids in identifying and rectifying issues promptly, preventing them from escalating further down the manufacturing process. Additionally, fostering a culture of quality consciousness among all stakeholders, including manufacturers, suppliers, and employees, is indispensable for sustaining high-quality standards consistently. Regular training programs and continuous improvement initiatives further reinforce this commitment to qualityexcellence. Ultimately, effective product quality inspection not only safeguards customer satisfaction and brand reputation but also contributes to overall business success by reducing rework, minimizing defects, and enhancing operational efficiency.中文翻译:在产品质量检验中，建立全面系统的方法至关重要，以确保评估过程的一致性和可靠性。

资产评估的英语词汇

资产评估的英语词汇1、liabilities evaluation 负债评估2、restore replacement cost 复原重置成本3、renewal replacement cost 更新重置成本4、non—patent technique and know—how 非专利技术和秘诀5、rate of risk return on investment 风险报酬率6、personal estate 动产7、equal expedient method 对等权宜法8、adjustment coefficient of road condition 车辆行驶路况调整系数purchase cost of vehicle 车辆购置费9、long term investment evaluation 长期投资评估10、newness rate 成新率11、real estate 不动产12、product and store goods evaluation 产成品和库存商品的评估transfer of property right 产权转让13、change of property right 产权变动14、principle of property right interests subject alteration 产权利益主体变动原则 reference object 参照物15、material evaluation 材料评估16、earning ratio of capital 本金化率17、quote 报价18、variable factor adjustment method 变动因素调整法19、key—point evaluation method 重点评估法20、engineering process method with recomposed budge 重编预算工程进度法 replacement cost calculation method 重置核算法21、replacement cost method 重置成本法22、tangible assets 有形资产23、physical wear 有形损耗24、Sino—foreign cooperative business operation 中外合作经营25、Sino—foreign joint venture 中外合资经营26、intellectual property right 知识产权27、expected service life 估计使用年限(有效使用寿命)28、evaluation of construction engineering in process 在建工程评估29、construction engineering in process 在建工程30、evaluation of products in process 在产品评估31、conversion rate 折现率32、discount to present value 折现33、enterprise total assets evaluation 整体企业资产评估34、total assets of enterprise 整体企业资产35、duties of increase in value 增值税36、travelled distance 已行驶里程37、inquiry 询价38、intangible asset evaluation 无形资产评估39、earnings of intangible assets 无形资产收益额40、intangible assets 无形资产41、moral wear 无形损耗42、special privilege evaluation 特许权评估43、special privilege 特许权益44、inflation rate 通货膨胀率45、consumption tax 消费税46、current market price method 现行市价法47、current market price 现行市价48、shop survey 现场勘查49、price index method 物价指数法(指数调整法)50、price index 物价指数51、evaluation of right of use land 土地使用权评估52、right of use land 土地使用权53、land ownership 土地所有权54、practical serviced life 实际已使用年限55、claim 索赔56、present earning value method 收益现值法57、present value of earning 收益现值58、evaluation of trade mark right 商标权评估59、trade mark 商标60、trade credit evaluation 商誉评估61、trade credit 商誉62、market of equipment transfer 设备调剂市场63、equipment sublet out 设备租出64、equipment sublet in 设备租入65、adjustment coefficient of equipment work condition 设备工作状态调整系数 sale of equipment 设备出售66、equipment purchasing 设备采购67、installation and test cost of equipment 设备安装调试费68、transportation cost of equipment 设备运杂费69、equipment leasing with circulating funds 设备融资租赁70、life of equipment 设备寿命71、disposal cost of facilities 设备清理费72、adjustment coefficient of equipment utilization 设备利用调系数73、liquidation price method 清算价格法74、liquidation price 清算价格75、circulating assets 流动资产76、nominal serviced life 名义已使用年限77、book value method 历史成本法78、(FOB) free on board 离岸价79、system of land price 地产友情链接80、verification and affirmation of assets evaluation 资产评估的验证确认 inassignable assets 不可确指的`资产81、devaluation by real degradation 实体性陈旧贬值82、engineering process method 工程进度法83、function and cost method 功能成本法84、devaluation by functional degradation 功能性陈旧贬值85、fair price 公允价格86、scale economical profit index analysis method 规模经济效益指数分析法 contract 合同87、rights and interests of contract 合同权益88、insurance of ocean transportation 海运保险费89、ocean transportation cost 海运费90、exchange rate 汇率91、time value of money 货币时间价值92、machine equipment evaluation 机器设备评估93、simple age limit method 简单年限法94、price adjustment factor 价格调整系数95、acceptance 接受96、building 建造物97、replacement cost of building 建造物重置价98、functional devaluation of building 建造物功能性贬值99、economical devaluation of building 建造物经济性贬值100、building evaluation 建造物评估101、import duties 进口关税102、economic devaluation 经济性贬值103、assignable assets 可确指的资产104、item request of assets evaluation 评估立项申请105、effective period of assets evaluation 评估有效期106、base date of assets evaluation 评估基准日107、links of evaluation 评估环节108、joint operation of enterprises 企业联营109、liquidation of enterprise 企业清算110、sale of enterprise 企业出售111、joint—stock system operation of enterprise 企业股分制经营112、annexation of enterprise 企业兼并113、resources assets 资源性资产114、resources assets evaluation 资源性资产评估115、original book value of assets 资产原值116、net book value assets 资产净值117、purpose of assets evaluation 资产评估目的118、salient features of assets evaluation 资产评估特点119、basis of assets evaluation 资产评估依据120、subject of assets evaluation 资产评估主体121、operating procedure of assets evaluation 资产评估[操作]程序(法定程序) work principle of assets evaluation 资产评估[工作]原则122、written report of assets evaluation 资产评估报告书123、statutes system of assets evaluation 资产评估法规体系124、method of assets evaluation 资产评估方法125、assets evaluation management 资产评估管理126、assets evaluation organization 资产评估机构127、hypothesis of assets evaluation 资产评估假设128、operation principle of assets evaluation 资产评估经济性(操作性)原则 object of assets evaluation 资产评估客体(对象) 129、check and arbitration of assets evaluation 资产评估的复核仲裁130、function of assets evaluation 资产评估的功能131、assets evaluation files 资产评估档案132、integrated age limit method 综合年限法133、integrated remainder life 综合剩余寿命134、integrated service life 综合服役年限135、certified public assets estimator 注册资产评估师136、patent 专利137、evaluation of patent right 专利权评估138、assignment of the patent right 专利权转让139、know—how evaluation 专用技术(诀窍)评估140、statistical analysis method 点面推算法141、single assets 单项资产142、(CIF) cost insurance and freight 到岸价资产评估的英语例句1. The courts will be asked to place a monetary value on his unfinished career.将要求法院对他未竟的事业进行资产评估。

202201浙江英语高考续写高手下水作文

Joseph：University of British Columbia 博士，专业外教Paragraph 1：We started to meet regularly to draw up our plans. Whenever we met, I would try desperately to get him to take me seriously as a teammate. While I am usually more laid back, for this project I worked hard to be useful to the partnership. I conducted thorough research on the topic and actively discussed with him my ideas on the matter. After some time, I began to see him loosening his aloof demeanor. He used to disregard my presence; Now, he listens intently when I share with him my thoughts and insights on the project. It looked like this new partnership is going well.Paragraph 2：One day I got word that he was admitted to hospital for a serious disease. When Dr. Gullickson first let me know about the situation, I felt a general concern for my teammate who I have grown to respect for his tireless work ethic. I was asked to finish the project on my own, was ready to prove to my partner that I will not let him down. I conducted the statistical analysis of the results we got from the experiments we did together and presented our findings to the class, all on my own, with a standard for perfection that even my teammate would be impressed with. For my hard work, the team was awarded a perfect mark. In the end, I earned not only respect from my teammate, but also the satisfaction of delivering good results when he was forced to rely on me.Jay：加拿大中学教师，丰富的语言教学经验Paragraph 1：We started to meet regularly to draw up our plans. Since my teammate was a serious person, we initially shared nothing about ourselves other than grades and research findings every time we met up. Nevertheless, our discussions quickly transformed into teenage gossip the minute I brought up my dissatisfaction with Dr. Gullickson’s need to over-explain his lectures. Little did I know, even high performing students can also have dissatisfactions with their teachers, and this realization bonded us more than ever. Our friendship was strengthening.Paragraph 2:One day I got word that he was admitted to hospital for a serious disease. This news came like a sudden landing of a hurricane with a tornado spiralling through the center of one’s hometown without any sign or warning. I felt extremely conflicted as I question both sympathetically as I watched him in distress and selfishly while worrying about being unable to complete Dr. Gullickson’s project. It was the day that I learned about how guilty tears tasted. It was the day, I learned of letting go of my childish obsessions with getting exactly what I want.Coco：中国留学生，初三留学加拿大，UBC大学优秀毕业生Paragraph 1：We started to meet regularly to draw up our plans. The group work was carried out more amicably than his serious appearance has permitted. We even developed a tacit agreement of some sort, with his quiet but reliable execution of the trials and my diligent recording of the results. When I self-consciously interject questions or new ideas, he received them with respectful interest and acknowledgment. We were making steady progress with the experiment. Although sometimes I could not help but sometimes felt insecure about my academic inferiority.Paragraph 2：One day I got word that he was admitted to hospital for a serious disease. I was apprehensive, not of having to finish the project by myself, but of letting my teammate down. When I visited him in the hospital, I reassured him that I will do my best to finish the project, he told me he was confident that I would do a great job at the final presentation and that he was sorry if he had been a hard person to work with at times. His words made me determined to put all my efforts into this project. In the end, I earned a good grade for our shared work, he recovered from his illness, and we became good friendsWe started to meet regularly to draw up our plans. The more we met, the more I resented his intelligence and his ability to cut through to the core issues. I, on the other hand, must have seemed naive, with little to offer. He finished almost all of the part of the experiment, and I just assisted him in calculating and sorting data. It seemed that he could do the whole project better if he did it alone. However, situation changed when something occurred accidentally.One day I got word that he was admitted to hospital for a serious disease. Entering the ward, I saw him in white, his skin pale and his cheeks sunken. It was as if by taking off his usual dark clothes, he had also thrown off the camouflage of aloofness. He looked quite surprised when he saw me. "Hi... What are you doing here?" He asked, conf used, "anything wrong with the project?" "No. It's been going well. It's just that I'm concerned about your health. Is everything okay?" For an instant he looked in credulous. The n there were tears in his eyes. Holding his hand, I reassured him I'd manage the project and wished him a quick recovery. Back to campus, I became fully dedicated to our research, and finally, efforts did pay off- we got an A. When we saw the result, we hugged each other, crying in excitement, and I knew we would be friends forever.。

ASTM E1245-03利用图像自动分析确定金属的夹杂物或者第二相组成的标准做法

Standard Practice for Determining the Inclusion or Second-Phase Constituent Content of Metals by Automatic Image Analysis利用自动图像分析确定金属的夹杂物或第二相组成内容的标准做法This standard is issued under the fixed designation E1245; the number immediately following the designation indicates the year of original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A superscript epsilon (e) indicates an editorial change since the last revision or reapproval.本标准发布指定E1245,该号码立即指定显示原始,如出现修订的情况,指定为今年的最后修订版本。

一个数字括号内表示,去年reapproval。

上标ε(e)的一篇社论指出改变自上次修订或reapproval。

INTRODUCTIONThis practice may be used to produce stereological measurements that describe the amount, number,size, and spacing of the indigenous inclusions (sulfides and oxides) in steels. The method may also be applied to assess inclusions in other metals or to assess any discrete second-phase constituent in any material.1. Scope1.1 This practice describes a procedure for obtaining stereological measurements that describe basic characteristics of the morphology of indigenous inclusions in steels and other metals using automatic image analysis. The practice can be applied to provide such data for any discrete second phase.NOTE 1—Stereological measurement methods are used in this practiceto assess the average characteristics of inclusions or other second-phase particles on a longitudinal plane-of-polish. This information, by itself, does not produce a three-dimensional description of these constituents inspace as deformation processes cause rotation and alignment of these constituents in a preferred manner. Development of such information requires measurements on three orthogonal planes and is beyond the scope of this practice.1.2 This practice specifically addresses the problem of producing stereological data when the features of the constituents to be measured make attainment of statistically reliable data difficult.1.3 This practice deals only with the recommended test methods and nothing in it should be construed as defining or establishing limits of acceptability.1.4 The measured values are stated in SI units, which are tobe regarded as standard. Equivalent inch-pound values are in parentheses and may be approximate.1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.2. Referenced Documents2.1 ASTM Standards:E 3 Methods of Preparation of Metallographic SpecimensE 7 Terminology Relating to MetallographyE 45 Test Methods for Determining the Inclusion Contentof SteelE 768 Practice for Preparing and Evaluating Specimens for Automatic Inclusion Assessment of Steel23. Terminology3.1 Definitions:3.1.1 For definitions of terms used in this practice, see Terminology E 7.3.2 Symbols:A¯=the average area of inclusions or particles, μm2.AA = the area fraction of the inclusion or constituent.Ai = the area of the detected feature.AT = the measurement area (field area, mm2).H T = the total projected length in the hot-working direction of the inclusion or constituent in the field, μm.L¯= the average length in the hot-working direction of the inclusion or constituent, μm.LT = the true length of scan lines, pixel lines, or grid lines (number of lines times the length of the lines divided by the magnification), mm.n = the number of fields measured.N A = the number of inclusions or constituents of a given type per unit area, mm2.Ni = the number of inclusions or constituent particles or the number of feature interceptions, inthe field.NL = the number of interceptions of inclusions or constituent particles per unit length (mm) ofscan lines, pixel lines, or grid lines.PPi = the number of detected picture points.PPT = the total number of picture points in the field area.s = the standard deviation.t = a multiplier related to the number of fields examined and used in conjunction with thestandard deviation of the measurements to determine the 95 % CIVV = the volume fraction.X¯= the mean of a measurement.Xi = an individual measurement.λ= the mean free path (μm) of the inclusion or constituent type perpendicular to the hotworking direction.ΣX = the sum of all of a particular measurement over n fields.ΣX2 = the sum of all of the squares of a particular measurement over n fields.95 % CI = the 95 % confidence interval.% RA = the relative accuracy, %.4. Summary of Practice4.1 The indigenous inclusions or second-phase constituents in steels and other metals are viewed with a light microscope or a scanning electron microscope using a suitably prepared metallographic specimen. The image is detected using a television-type scanner tube (solid-state or tube camera) and displayed on a high resolution video monitor. Inclusions are detected and discriminated based on their gray-level intensity differences compared to each other and the unetched matrix. Measurements are made based on the nature of the discriminated picture point elements in the image.3 These measurementsare made on each field of view selected. Statistical evaluation of the measurement data is based on the field-tofield or feature-to-feature variability of the measurements.5. Significance and Use5.1 This practice is used to assess the indigenous inclusions or second-phase constituents of metals using basic stereological procedures performed by automatic image analyzers.5.2 This practice is not suitable for assessing the exogenous inclusions in steels and other metals. Because of the sporadic, unpredictable nature of the distribution of exogenous inclusions,other methods involving complete inspection, for example, ultrasonics, must be used to locate their presence. The exact nature of the exogenous material can then be determined by sectioning into the suspect region followed by serial, step-wise grinding to expose the exogenous matter for identification and individual measurement. Direct size measurement rather than application of stereological methods is employed.5.3 Because the characteristics of the indigenous inclusion population vary within a given lot of material due to the influence of compositional fluctuations, solidification conditions and processing, the lot must be sampled statistically to assess its inclusion content. The largest lot sampled is the heat lot but smaller lots, for example, the product of an ingot, within the heat may be sampled as a separate lot. The sampling of a given lot must be adequate for the lot size and characteristics.5.4 The practice is suitable for assessment of the indigenous inclusions in any steel (or other metal) product regardless of its size or shape as long as enough different fields can be measured to obtain reasonable statistical confidence in the data. Because the specifics of the manufacture of the product do influence the morphological characteristics of the inclusions, the report should state the relevant manufacturing details, that is, data regarding the deformation history of the product.5.5 To compare the inclusion measurement results from different lots of the same or similar types of steels, or other metals, a standard sampling scheme should be adopted such as described in Practice E45.5.6 The test measurement procedures are based on the statistically exact mathematical relationships of stereology4 for planar surfaces through a three-dimensional object examined using reflected light (see Note 1).5.7 The orientation of the sectioning plane relative to the hot-working axis of the product will influence test results. In general, a longitudinally oriented test specimen surface is employed in order to assess the degree of elongation of the malleable (that is, deformable) inclusions.5.8 Oxide inclusion measurements for cast metals, or for wrought sections that are not fully onsolidated, may be biased by partial or complete detection of fine porosity or micro-shrinkage cavities and are not recommended. Sulfides can be discriminated from such voids in most instances and such measurements may be performed.5.9 Results of such measurements may be used to qualify material for shipment according to agreed upon guidelines between purchaser and manufacturer, for comparison of different manufacturing processes or process variations, or to provide data for structure-property-behavior studies.6. Interferences6.1 Voids in the metal due to solidification, limited hot ductility, or improper hot working practices may be detected as oxides because their gray level range is similar to that of oxides.6.2 Exogenous inclusions, if present on the plane-of-polish, will be detected as oxides and will bias the measurements of the indigenous oxides. Procedures for handling this situation are given in 12.5.9.6.3 Improper polishing techniques that leave excessively large scratches on the surface, or create voids in or around inclusions, or remove part or all of the inclusions, or dissolve water-soluble inclusions, or create excessive relief will bias the measurement results.6.4 Dust, pieces of tissue paper, oil or water stains, or other foreign debris on the surface to be xamined will bias the measurement results.6.5 If the programming of the movement of the automatic stage is improper so that the specimen movesout from under the objective causing detection of the mount or air (un-mounted specimen),easurements will be biased.6.6 Vibrations must be eliminated if they cause motion in the image.6.7 Dust in the microscope or camera system may produce spurious indications that may be detected as inclusions. Consequently, the imaging system must be kept clean.7. Apparatus7.1 A reflected light microscope equipped with bright-field objectives of suitable magnifications is used to image the microstructure. The use of upright-type microscope allows for easier stage control when selecting field areas; however, the specimens will require leveling which can create artifacts, such as scratches, dust remnants and staining, on the polished surface (see 12.2.1). The use of inverted microscopes usually result in a more consistent focus between fields, thereby, requiring less focussing between fields and a more rapid completion of the procedure. A scanning electron microscopealso may be used to image the structure.7.2 A programmable automatic stage to control movement in the x and y directions without operator attention is recommended (but not mandatory) to prevent bias in field selection and to minimize operator fatigue.7.3 An automatic focus device may also be employed if found to be reliable. Such devices may be unreliable when testing steels or metals with very low inclusion contents.7.4 An automatic image analyzer with a camera of adequate sensitivity is employed to detect the inclusions, perform discrimination, and make measurements.7.5 A computer is used to store and analyze the measurement data.7.6 A printer is used to output the data and relevant identification/background information in a convenient format.7.7 This equipment must be housed in a location relatively free of airborne dust. High humidity must be avoided as staining may occur; very low humidity must also be avoided as static electricity may damage electronic components. Vibrations, if excessive, must be isolated.8. Sampling8.1 In general, sampling procedures for heat lots or for product lots representing material from a portion of a heat lot are the same as described in Practice E 45 (Microscopical Methods) or as defined by agreements between manufacturers and users.8.2 Characterization of the inclusions in a given heat lot, or a subunit of the heat lot, improves as the number of specimens tested increases. Testing of billet samples from the extreme top and bottom of the ingots (after discards are taken) will define worst conditions of oxides and sulfides. Specimens taken from interior billet locations will be more representative of the bulk of the material. Additionally, the inclusion content will vary with the ingot pouring sequence and sampling should test at least the first, middle and last ingot teemed. The same trends are observed in continuously cast steels. Sampling schemes must be guided by sound engineering judgment, the specific processing parameters, and producer-purchaser agreements.9. Test Specimens9.1 In general, test specimen orientation within the test lot is the same as described in Practice E 45 (Microscopical Methods). The plane-of-polish should be parallel to the hot-working axis and, most commonly, taken at the quarter-thickness location. Other test locations may also be sampled, for example, subsurface and center locations, as desired or required.9.2 The surface to be polished should be large enough in area to permit measurement of at least 100fields at the necessary magnification. Larger surface areas are beneficial whenever the product form permits. A minimum polished surface area of 160 mm2 (0.25 in.2) is preferred.9.3 Thin product forms can be sampled by placing a number of longitudinally oriented pieces in the mount so that the sampling area is sufficient.9.4 Practice E 768 lists two accepted methods for preparing steel samples for the examination of inclusion content using image analysis. The standard also lists a procedure to test the quality of the preparation using differential interference contrast (DIC).10. Specimen Preparation10.1 Metallographic specimen preparation must be carefully controlled to produce acceptable quality surfaces for image analysis. Guidelines and recommended practices are given in Methods E 3, and Practices E 45 and E 768.10.2 The polishing procedure must not alter the true appearance of the inclusions on the plane-of-polish by producing excessive relief, pitting, cracking or pullout. Minor fine scratches, such as from a 1-μm diamond abrasive, do not usually interfere with inclusion detection but heavier scratches are to be avoided. Proper cleaning of the specimen is necessary. Use of automatic grinding and polishing devices is recommended.10.3 Establishment of polishing practices should be guided by Practice E 768.10.4 Inclusion retention is generally easier to accomplish if specimens are hardened. If inclusion retention is inadequate with annealed, normalized, or low hardness as-rolled specimens, they should be subjected to a standard heat treatment (hardening) cycle, appropriate for the grade. Because inclusion retention and cracking at carbides may be a problem for certain steels in the as-quenched condition, tempering is recommended; generally, a low tempering temperature, for example, 200–260°C(400–500°F), is adequate.10.5 Mounting of specimens is not always required depending on their size and shape and the available equipment; or, if hand polishing is utilized for bulk specimens of convenient size and shape.10.6 The polished surface area for mounted specimens should be somewhat greater than the area required for measurement to avoid edge interferences. Unmounted specimens generally should have a surface area much greater than required for measurement to facilitate leveling using the procedure described in 12.1.1.10.7 Etching of specimens is not desired for inclusion assessment.。

关于熵焓的书籍

熵（entropy）和焓（enthalpy）是热力学领域中的重要概念，它们用于描述热力学系统的状态和性质。

以下是一些建议的关于熵和焓的书籍，这些书籍涵盖了这两个概念以及它们在物理、化学等领域中的应用：1.《热力学与统计物理学》（Thermodynamics and Statistical Mechanics）作者：RichardFitzpatrick•这本书是一本面向研究生水平的教材，涵盖了热力学和统计物理学的基本原理，包括对熵和焓的详细讲解。

2.《热力学与热工学》（Thermodynamics: An Engineering Approach）作者：Yunus A.Cengel, Michael A. Boles•这是一本广泛用于工程热力学课程的教材，介绍了熵、焓以及它们在工程应用中的重要性。

3.《化学工程热力学》（Introduction to Chemical Engineering Thermodynamics）作者：Joseph M. Smith, Hendrick C. Van Ness, Michael M. Abbott•这本书专注于化学工程中的热力学，对熵和焓进行了深入的讲解，并提供了实际应用的例子。

4.《现代工程热力学》（Modern Engineering Thermodynamics）作者：Robert T. Balmer•这本书介绍了现代工程热力学的基本概念，包括对熵和焓的理解，以及它们在工程应用中的使用。

5.《热力学和统计物理学的奇迹》（The Miracles of Reversible Entropy）作者：DilipKondepudi•本书提供了关于熵和可逆过程的更深入的理论讨论，适合那些对热力学基础和统计物理学感兴趣的读者。

6.《化学热力学基础》（Physical Chemistry: A Molecular Approach）作者：Donald A.McQuarrie, John D. Simon•这本化学热力学教材包含了关于熵和焓等热力学概念的详细讲解，适用于学习化学热力学的学生。

认知偏见总结

认知偏见总结在6.3日的科研项目理论学习中，我们主要就“决策、信仰和行为偏差”、“社会偏见”和“记忆错误和偏见”这三个方面的多种认知偏差进行了学习和理解。

一、决策、信仰和行为偏差1、Ambiguity effect (歧义效应)– the tendency to avoid options for which missing information makes the probability seem "unknown."(倾向于避免选择可能性未知的缺失的信息)2、Anchoring or focalism（锚定或聚焦）– the tendency to rely too heavily, or "anchor," on one trait or piece of information when making decisions（在做决策时过度依赖或“锚定”一个特点或信息的倾向）3、Attentional bias（注意偏向）– the tendency to pay attention to emotionally dominant stimuli（占主导地位的刺激）in one's environment and to neglect relevant data when making judgments of a correlation or association. （对于一个相关事物或联想作出判断时，忽视相关数据而感性地重视他们环境中占主导地位的刺激,是一个人集中更多他的注意力引向一种特定的刺激或感觉。

这将导致一个贫穷的判断力还是一个不完整的回忆某个事件或内存。

）4、Availability heuristic(可得性启发法) – the tendency to overestimate the likelihood of events with greater "availability" in memory, which can be influenced by how recent the memories are or how unusual or emotionally charged they may be (倾向于根据记忆来高估事件的可能性,它是受到最近的记忆的影响或者多么不寻常的或充满感情他们可能是,就是说在进行判断时，人们往往会依赖最先想到的经验和信息，并认定这些容易知觉到或回想起的事件更常出现，以此作为判断的依据，这种判断方法称为可得性启发法。

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The Statistical Evaluation of the NESSIESubmission CS-cipher∗†NES/DOC/UIB/WP3/010/1H˚avard RaddumDepartment of Informatics,The University of Bergen,N-5020Bergen,NorwayFebruary18,2002AbstractThe purpose of this document is to give a statistical evaluation of the NESSIE submission CS-cipher.For this evaluation,we follow the recommendations of the NESSIE statisticalevaluation process for blockcipher submissions as described in[Sch01a].1OverviewThe NESSIE submission CS-cipher is a64-bit blockcipher with key length up to128bits,submitted by Jacques Stern and Serge Vaudenay.This document is organized as follows:The next two sections present the statistical evaluation of the full round version of CS-cipher as well as the statistical evaluation of reduced round versions of the cipher.In the two remaining sections we give the results of the NESSIE streamcipher tests applied to CS-cipher in OFB mode and in counter mode[Sch01b],respectively.2Statistical evaluation of the NESSIE blockcipher CS-cipher with full roundsThe NESSIE evaluation tools for blockciphers consist of the dependence test and the linear factors test.For a detailed introduction to the dependence test and linear factors test,please refer to the documents[Bol90,Dic91].2.1The Dependence TestThe dependence test evaluates the dependence matrix and the distance matrix of the cipher. Furthermore,the degree of completeness,the degree of avalanche eﬀect and the degree of strict avalanche criterion of the cipher are computed.A cryptographic function is complete if each output bit depends on each input bit.For a function to exhibit the avalanche eﬀect,an average of one half of the output bits should change whenever a single input bit is complemented.A function satisﬁes the strict avalanche criterion if each output bit changes with a probability of one half whenever a single input bit is complemented.The exact deﬁnitions of the degree of completeness, the avalanche eﬀect and the strict avalanche criterion can be found in document[Ser00].∗The work described in this paper has been supported by the Commission of the European Communities through the IST program under contract IST-1999-12324.†The information in this document is provided as is,and no warranty is given or implied that the information isﬁt for any particular purpose.The user thereof uses the information at its sole risk and liability.Due to space constraints,only a fraction of the test output of the dependence test will be presented.DEPENDENCE TEST forNESSIE submission blockcipher csNumber of inputs:10000Average number of output bits changed:31.999205Degree of completeness: 1.000000Degree of avalanche effect:0.999025Degree of strict avalanche criterion:0.991960ANALYSIS OF THE DISTANCE MATRIXAverage fractions of inputs yielding distance j if one bit is complemented,and the expected fractions for a random functionj01234567 exp.0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000 av.0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000j89101112131415 exp.0.0000000.0000000.0000000.0000000.0000000.0000010.0000030.000009 av.0.0000000.0000000.0000000.0000000.0000000.0000000.0000050.000009j1617181920212223 exp.0.0000260.0000750.0001950.0004730.0010640.0022280.0043560.007954 av.0.0000280.0000670.0002030.0004690.0010690.0023470.0044810.007934j2425262728293031 exp.0.0135880.0217400.0326110.0458960.0606490.0752880.0878360.096336 av.0.0135280.0214660.0321360.0460800.0609280.0756750.0877390.096047j3233343536373839 exp.0.0993470.0963360.0878360.0752880.0606490.0458960.0326110.021740 av.0.0999770.0961480.0876530.0754000.0605580.0456270.0325950.021708j4041424344454647 exp.0.0135880.0079540.0043560.0022280.0010640.0004730.0001950.000075 av.0.0137170.0079000.0042890.0023770.0011340.0004080.0001920.000070j4849505152535455 exp.0.0000260.0000090.0000030.0000010.0000000.0000000.0000000.000000 av.0.0000220.0000110.0000030.0000000.0000000.0000000.0000000.000000j5657585960616263 exp.0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000 av.0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000j64exp.0.000000av.0.000000Application of the Chi-square test to the rows of the distance matrix (%levels of significance)row%row%row%row%row% 190.0287.8395.3421.0515.8 661.8789.2848.3981.81072.3 1162.21225.21349.11491.41516.6 1618.71727.61876.51910.02017.4 2126.02251.22371.22426.82573.8 2668.92792.22859.52976.23042.8 3132.73217.03359.23475.63561.4 3611.33751.63826.53946.14061.4 4187.24291.54339.44465.94591.1 4637.34725.848 4.84931.45037.9 5136.65267.55390.65432.45555.1 5649.85779.45898.65914.56041.1 6190.56269.96351.66417.8ANALYSIS OF THE DEPENDENCE MATRIXRow average of the dependence matrixi i i i10.49949720.49912730.50002240.50001150.49885060.50074570.50023380.50045690.499772100.500759110.500558120.499512 130.498998140.500520150.499567160.499808 170.499075180.500794190.500413200.500075 210.500878220.499398230.499539240.500341 250.499077260.500006270.500800280.500364 290.500248300.500069310.499889320.500656 330.500153340.501328350.499322360.499741 370.498795380.499258390.500377400.500158 410.500383420.499708430.499772440.499603 450.500428460.501136470.498639480.501522 490.499823500.499513510.500425520.500073 530.499392540.500117550.500352560.499912 570.500008580.500333590.499556600.500398 610.499714620.500002630.499148640.500058 Column average of the dep.matrixi i i i10.50011620.50033430.50090940.50115850.49931660.49936670.49979780.49913190.500258100.499331110.500167120.499903130.500830140.500470150.499920160.500242170.500797180.499559190.499766200.500647210.499455220.500203230.500102240.498719250.499189260.501009270.500108280.499111290.501437300.499961310.500998320.500127330.500078340.500244350.500180360.499325370.499862380.499280390.499009400.500631410.500066420.498044430.499841440.500898450.499386460.500136470.499852480.499581490.500223500.498947510.500539520.499938530.500023540.500227550.499648560.500748570.499070580.499953590.500359600.500206610.500105620.499341630.500625640.500403The test results do not indicate a deviation from random behaviour.2.2The Linear Factors TestThe linear factors test is used toﬁnd out whether there are any linear combinations of output bits which,for all keys and plaintexts,are independent of one or more key or plaintext bits.Such a linear combination is called a linear factor.It is practically impossible to check a potential linear factor for all keys and plaintexts.Therefore,we only consider for a suﬃciently large number of pairs of random keys and random plaintexts[Dic91].For the full round version of the cipher,no linear factors were found.3Statistical evaluation of the NESSIE blockcipher CS-cipher with reduced roundsThe blockcipher CS-cipher with128bit key is a cipher with eight rounds plus aﬁnal key addition. For the reduced round tests of the cipher,we always performed theﬁnal key addition.As in document[Ser00],we examined(1)the degree of completeness(2)linear factors(3)the degree of strict avalanche criterionWe found that the blockcipher CS-cipher•is complete after1round.•has a degree of strict avalanche criterion greater than0.98after2rounds.•reveals no linear factors after1round.4Evaluation of the NESSIE blockcipher CS-cipher in OFB mode4.1The Frequency TestThe frequency test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the blocksize of the test.The frequencies of the occurrences of these m-tuples are counted and evaluated statistically.This test is performed for various values of m.Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:1sequencelength=10000000blocksize=1block:0count:5001160block:1count:4998840chisquare=0.538240nu=1Percentage Level of Acceptance:46.32The test results do not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:2sequencelength=10000000blocksize=2block:0count:1252080block:1count:1248844block:2count:1249367block:3count:1249709chisquare= 4.918485nu=3Percentage Level of Acceptance:17.79The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:3sequencelength=10000000blocksize=3block:0count:416369block:1count:417338block:2count:418090block:3count:415799block:4count:416266block:5count:417034block:6count:416669block:7count:415768chisquare=10.610622nu=7Percentage Level of Acceptance:15.65The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:4sequencelength=10000000blocksize=4block:0count:156075block:1count:155593block:2count:156557block:3count:156702block:4count:156265block:5count:155874block:6count:156161block:7count:156615block:8count:156060block:9count:156061block:10count:155945block:11count:156279block:12count:156608block:13count:156373block:14count:156437block:15count:156395chisquare=9.014707nu=15Percentage Level of Acceptance:87.67The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:5sequencelength=10000000blocksize=5chisquare=24.670368nu=31Percentage Level of Acceptance:78.23The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:6sequencelength=10000000blocksize=6chisquare=63.155370nu=63Percentage Level of Acceptance:47.08The test result does not indicate a deviation from random behaviour. Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0 Number of bits used for testing:10000000Block size:7sequencelength=10000000blocksize=7chisquare=113.157872nu=127Percentage Level of Acceptance:80.51The test result does not indicate a deviation from random behaviour.Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:8sequencelength=10000000blocksize=8chisquare=276.390912nu=255Percentage Level of Acceptance:17.07The test result does not indicate a deviation from random behaviour.Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:12sequencelength=10000000blocksize=12chisquare=4143.338011nu=4095Percentage Level of Acceptance:29.48The test result does not indicate a deviation from random behaviour.Frequency Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:16sequencelength=10000000blocksize=16chisquare=66052.688179nu=65535Percentage Level of Acceptance:7.66The test result does not indicate a deviation from random behaviour.4.2The Collision TestThe collision test splits up the bit sequence into subsequent,disjoint m-tuples of bits.The test evaluates statistically how often such m-tuples occur more than once.Collision Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:24#of blocks:416666blocksize:24collisions:5078For an ideal random number generator,the probability to obtain5078collisions or less is 22.66%.So the test result does not indicate a deviation from random behaviour.4.3The Overlapping m-tuple TestThe overlapping m-tuple test splits up the bit sequence into m-tuples of words.Each word contains aﬁxed number of bits.In the overlapping m-tuple test,the m-tuples are not disjoint;to take the next m-tuple,an m-word-window on the original sequence is shifted by one word.So the next m-tuple consists of m−1shifted words of the previous m-tuple and one new word.Since subsequent m-tuples are not independent,the statistical evaluation is more involved than in the case of the frequency test,but this is handled by the test program.This test is also applied to cyclic shifts of the original sequence.OVERLAPPING M-TUPLE TEST forNESSIE submission blockcipher CS-cipher in OFB modeSequencelength=10000000bits Wordlength=5bitsm=2Shift p--------------08.20%113.82%267.06%361.86%477.76%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.The test result does not indicate a deviation from random behaviour.4.4The Gap TestThe gap test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the word length of the test.The m-tuples are interpreted as binary representations of numbers,and the lengths of gaps,where the numbers are not within a numerical range given as a parameter of the test,are registered and evaluated statistically.The gap test is also applied to cyclic shifts of the original sequence.GAP TEST forNESSIE submission blockcipher CS-cipher in OFB modeSequencelength=10000000bits Wordlength=10bitsLength of gaps between occurences in the range256-768Ideal distribution:mean variance1.0002.000Real distribution:Shift:0123456789--------------------------------------------------------------------------------mean:0.997 1.000 1.0020.9970.999 1.0010.999 1.002 1.002 1.000error:-0.27%-0.00%0.18%-0.27%-0.13%0.13%-0.11%0.25%0.20%-0.01%variance: 1.984 2.007 2.002 1.993 1.997 1.999 2.004 2.007 2.004 1.992error:-0.82%0.34%0.09%-0.37%-0.17%-0.06%0.22%0.34%0.22%-0.40% p=7.64%12.86%65.29%80.11%79.17%99.23%79.39% 6.81%97.90%88.54%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.The results for the shifts5and8are too high,so the test has been repeated.GAP TEST forNESSIE submission blockcipher csSequencelength=10000000bits Wordlength=10bitsLength of gaps between occurences in the range256-768Ideal distribution:mean variance1.0002.000Real distribution:Shift:0123456789--------------------------------------------------------------------------------mean:0.998 1.0010.9990.999 1.0010.9990.998 1.001 1.004 1.002error:-0.16%0.14%-0.13%-0.10%0.14%-0.14%-0.16%0.10%0.42%0.17%variance: 1.997 2.007 1.990 2.001 2.003 1.993 1.997 2.002 2.013 2.002error:-0.16%0.37%-0.50%0.04%0.14%-0.36%-0.17%0.12%0.66%0.12% p=66.40%30.74%26.01%72.55%99.33% 6.52%61.96%79.40%40.22%45.80%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.This time the results for shift5and8are acceptable,so we conclude that the test results do not indicate a deviation from random behaviour.4.5The Run TestThe run test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the word length of the test.The m-tuples are interpreted as binary representations of numbers.The lengths of subsequences of consecutive,strictly increasing numbers are evaluated statistically. Run Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Block size:16Maximal run length registered individually:5Total of230140runs115500runs of length1expected:115071.876355runs of length2expected:76713.328727runs of length3expected:28766.67673runs of length4expected:7670.71582runs of length5expected:1598.0303runs of length6or more expected:319.6chisquare= 4.341204nu=5Percentage level of acceptance50.14The test result does not indicate a deviation from random behaviour.4.6The Coupon Collector’s TestThe coupon collector’s test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the word length of the test.In the test,the number of subsequent m-tuples it takes until all possible2m m-tuples have appeared,is evaluated statistically.The coupon collector’s test is also applied to cyclic shifts of the original sequence.COUPON COLLECTOR’S TEST forNESSIE submission blockcipher CS-cipher in OFB modeSequencelength=10000000bits Wordlength=8bitsIdeal distribution:mean variance1567.8323105979.0660Real distribution:The results are for cyclic shiftsShift:01234567------------------------------------------------------------------------mean:1549.0211564.0281584.1651577.7561564.6181566.8031585.8411571.507error:-1.20%-0.24% 1.04%0.63%-0.21%-0.07% 1.15%0.23%variance:106238111013112457102965113765108663110537109748error:0.24% 4.75% 6.11%-2.84%7.35% 2.53% 4.30% 3.56% p=7.10%77.94%57.72%59.01%71.48%61.76%91.04%95.96%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.The result for shift7is too high,so the test has been repeated.COUPON COLLECTOR’S TEST forNESSIE submission blockcipher csSequencelength=10000000bits Wordlength=8bitsIdeal distribution:mean variance1567.8323105979.0660Real distribution:The results are for cyclic shiftsShift:01234567------------------------------------------------------------------------mean:1595.5401564.3171574.9281580.6571589.2861563.5241561.6581584.044error: 1.77%-0.22%0.45%0.82% 1.37%-0.27%-0.39% 1.03%variance:1264831060851132099932511287499884103358108065error:19.35%0.10% 6.82%-6.28% 6.51%-5.75%-2.47% 1.97% p=43.32%22.14%26.73%27.42% 2.69%54.56%93.01%28.19%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.This time the result is acceptable,so we conclude that the test does not indicate a deviation from random behaviour.4.7The Universal Maurer TestThe universal Maurer test splits up the bit sequence into subsequent,disjoint m-tuples of bits. m is called the blocksize of the test.The test evaluates statistically how many m-tuples later an m-tuple re-appears in the sequence.The test result of the Maurer test is closely related to the entropy of the bit sequence.Maurer Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0Number of bits used for testing:1000000Block size:8Initial Blocks=10000blocks tested(including initial blocks):125000Maurer Test Value:7.186490For an ideal random number generator,the probability to obtain a Maurer test value of7.186490 or less is80.96%.So the test result does not indicate a deviation from random behaviour.4.8The Poker TestThe poker test splits up the bit sequence into subsequent,disjoint m-tuples of bits.m is called the word length of the test.The sequence of m-tuples is split up into subsequent,disjoint k-tuples of m-tuples.The poker test evaluates statistically how many of the m-tuples in a k-tuple are equal. The poker test is also applied to cyclic shifts of the original sequence.POKER TEST forNESSIE submission blockcipher CS-cipher in OFB modeSequencelength=9999360bits Wordlength=8bitsElements in a k-tuple:128Ideal distribution:mean variance100.880113.9923Real distribution:Shift:01234567----------------------------------------------------------------mean:100.913100.938100.892100.923100.950100.850100.842100.862error:0.03%0.06%0.01%0.04%0.07%-0.03%-0.04%-0.02%variance:14.26613.83213.94113.89913.91413.73613.85913.998error: 1.95%-1.14%-0.36%-0.67%-0.56%-1.83%-0.95%0.04% p=13.98%33.84%84.34%17.57%87.77%56.16%19.56%73.77%p gives the percentage level of acceptance of the chi-square testThis percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.We conclude that the test results do not indicate a deviation from random behaviour.4.9The Fast Spectral TestThe fast spectral test applies the fast Walsh transform to the given sequence.It uses two values derived from the transform to assess the randomness of the sequence.Fast Spectral Test forNESSIE submission blockcipher CS-cipher in OFB modeThe results are:The statistic D(4)=-1.540292E+00;percentage level of significance: 6.2%The statistic D(6)=-1.783974E+00;percentage level of significance: 3.7%This percentage level gives the probability that a truly randomsequence has a chi-square value greater than the chi-square valueobserved in this execution of the test.The result for D(6)is too low,so the test has been repeated.Fast Spectral Test forNESSIE submission blockcipher csThe results are:The statistic D(4)=8.395709E-01;percentage level of significance:79.9%The statistic D(6)= 3.057602E-01;percentage level of significance:62.0% This time the result is acceptable,so the test does not indicate a deviation from random behaviour.4.10The Correlation TestThe correlation test determines in how many places the original sequence and the sequence shifted by n bits have the same value.This is done for all shifts n up to the length of the original sequence.To support the interpretation of the results,for each shift the probability for a sequence of random,independent,and uniformly distributed bits to have this number or less coincidences with its shifted copy is determined.Only values where these probabilities are close to0or1are printed.The print level is the maximal deviation from0or1for these probabilities in order to be printed.Correlation Test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0Number of bits used for testing:1000000Printlevel:0.000010shift:0equal:1000000probability: 1.00000000e+00shift:67188equal:497861probability:0.00000959e-06shift:68185equal:502413probability:0.99999937e-07shift:177464equal:497807probability:0.00000586e-06shift:200501equal:497769probability:0.00000414e-06shift:236623equal:497797probability:0.00000535e-06shift:238424equal:502133probability:0.99999011e-05shift:257096equal:497704probability:0.00000222e-06shift:259575equal:502149probability:0.99999149e-06shift:348391equal:502249probability:0.99999663e-06shift:350047equal:502255probability:0.99999683e-06shift:352848equal:502163probability:0.99999248e-06shift:387343equal:497700probability:0.00000212e-06shift:486597equal:497849probability:0.00000859e-06shift:488043equal:497527probability:0.00000044e-07shift:495279equal:502163probability:0.99999248e-06shift:565132equal:502172probability:0.99999307e-06shift:597176equal:502260probability:0.99999693e-06shift:614475equal:497780probability:0.00000455e-06shift:618799equal:502371probability:0.99999891e-06shift:654070equal:502192probability:0.99999426e-06shift:688670equal:497709probability:0.00000232e-06shift:757203equal:497679probability:0.00000172e-06shift:817748equal:502293probability:0.99999772e-06shift:906552equal:497855probability:0.00000909e-06shift:962364equal:502274probability:0.99999733e-06shift:986442equal:502413probability:0.99999937e-07shift:996908equal:502172probability:0.99999307e-06The test result does not indicate a deviation from random behaviour.4.11The Rank TestIn the rank test,the bits of the sequence to test are used toﬁll square matrices.The bits are treated as elements of theﬁeld GF(2),and the ranks of the matrices are evaluated statistically. Rank test forNESSIE submission blockcipher CS-cipher in OFB modeNumber of bits generated and ignored before starting to test:0Number of bits used for testing:10000000Order of the matrix:16Number of ranks counted individually:311264matrices with rank16,expected:11280.822538matrices with rank15,expected:22561.35050matrices with rank14,expected:5013.5210matrices with rank13or less,expected:206.4chisquare=0.376677nu=3Percentage level of acceptance94.50The test result does not indicate a deviation from random behaviour.4.12The Linear Complexity TestThe linear complexity test uses the Berlekamp Massey algorithm to determine the length of the shortest linear feedback shift register which can produce the given bit sequence.For the linear complexity proﬁle,this is done for theﬁrst1,2,3,...bits of the sequence.Some properties of this proﬁle are evaluated.Linear Complexity Test forNESSIE submission blockcipher CS-cipher in OFB mode--------------------Final results------------------N=100000L=50000X=3N is the number of input bits.L is the linear complexity.X-1is the number of bits which has been treated sincethe last change of linear complexity.-------------------------End-----------------------The linear complexity profile:Jumps in the linear complexity profile:ssl=99999.000ssqsl=500157.000msl= 4.009varsl= 3.980ssh=50000.000ssqsh=150266.000msh= 2.004varsh= 2.006ssl is the sum of the sl’sssqsl is the sum of the squares of the sl’smsl is the mean of the sl’svarsl is the variance of the sl’sThe number of jumps used in the calculation of msl and varsl is:24945ssh is the sum of the sh’sssqsh is the sum of the squares of the sh’smsh is the mean of the sh’svarsh is the variance of the sh’sThe number of jumps used in the calculation of msh and varsh is:24944maximal step-height16.000000sl is the steplengthsh is the stepheigthnj is the number of jumpsThe test result does not indicate a deviation from random behaviour.4.13The Maximum Order Complexity TestThe maximum order complexity test determines the length of the shortest possibly non-linear feedback shift register which can produce the given bit sequence.For the MOC proﬁle,this is done for theﬁrst1,2,3,...bits of the sequence.The changes in this proﬁle are studied. Maximum Order Complexity(MOC)Test forNESSIE submission blockcipher CS-cipher in OFB modeThe changes in the MOC profile:21( 2.00)42( 4.00)63( 5.17)84( 6.00)135(7.40)209(8.64)7212(12.34)11114(13.59)32515(16.69)75222(19.11)735023(25.69)763127(25.80)1269829(27.26)3648130(30.31)4132336(30.67)33035042(36.67)The number of inputcharacters:1000000The number of nodes:1999963。