2018IEEEEMCSIPI国际会议——提名文章(一)
ITMA_ASIA_+_CITME_2018_回顾
54 /机械/MACHINARY“2018中国国际纺织机械展览会暨ITMA 亚洲展览会（ITMA ASIA+CITME 2018）”，于10月15～19日在中国上海市举行。
由于明年将举行“ITMA 巴塞罗那”，因此与介绍新技术相比，应该更重视符合市场需求的提案。
本期回顾一下2018年展会的情况。
本届展会上尤其受到关注的是省人工化或节能等技术。
以各国纺织产业人工费用上涨及人手不足为背景，对省人工化的需求急剧增长，各工序都对自动化技术十分关注。
岛精机制作所公司展出“WHOLEGARMENT”（WG）横编机、3D 设计系统“SDS-ONE APEX3”、以物联网技术连结设备和基干系统的“SHIMA KNIT PLM”等。
推出了从市场营销到产品企划、生产、销售全流程“都节约不必要的损耗、以自动化进行”的提案。
例如通过APEX3提高样品制作的效率等都受到极大关注。
在实现省人工化同时追求高性能的需求也很高，WG 展示了2针床结构的“MACH2S”和4针床“MACH2XS”，性能更高的“XS”更具有人气。
福原产业贸易公司推出采用了自动化技术的电子提花圆编机。
自动化技术包括供纱装置的皮带马达化、只供给设定纱线的自动控制；用传感器探测供纱张力并保持一定张力；生产结束的面料自动运出、移向下一步生产等功能。
不仅是省人工化，保持稳定品质及缩短机械停滞时间等特点也受到关注。
“中国对自动化的需求增长”（福原正则专务），因此今后将在配合各用户需求的同时促进自动化技术的进化。
展会中床垫用的高性能机也受到关注。
是双面选针的高针距（28G）机型，以多路喂纱口可高速生产具有梭织面料般外观的圆编面料。
针对明年的ITMA 巴塞罗那，还在开发新型的床垫用圆编机。
STAUBLI 公司除了在安全气囊用途需求很高的大型电子提花（10240口）及多臂机外，还致力于推广制织准备工序的自动化技术。
自动穿经机“SAFIA”系列可应对12/16根穿综杆，标准型的穿经数为每分钟200根（以往型号为100根）。
ISPEMI2018国际会议情况简介
ISPEMI 2018国际会议情况简介第十届精密工程测量与仪器国际学术会议（ISPEMI 2018）将于2018年8月8日至10日在昆明举办（8号全天注册报到、9号至10号会议）。
此次会议由国际测量与仪器委员会(ICMI)、国家自然科学基金委员会、中国计量测试学会等发起，哈尔滨工业大学主办，昆明理工大学等协办。
目前会议筹备情况如下：1. 会议论文集出版本次会议前期已经与SPIE签订协议，会议论文集将由SPIE出版，并全部由Ei检索。
同时部分优秀论文可被推荐至国际权威期刊。
2. 会议大会报告邀请会议组委会已经邀请测量与仪器技术领域有重大影响的国际著名专家学者，如英国牛津大学的Tony Wilson院士等，到会做大会特邀报告/担任大会主席。
另已邀请来自10余个国家和地区的几十位有重要突破性研究成果的专家学者参会作分会邀请报告。
3. 会议征文会议第一轮通知已于2018年1月通过邮件发出，目前已着手准备第二轮会议通知。
4. 会议地点在昆明理工大学的大力支持下，会议举办地址已经确定为昆明理工大学国际学术交流中心（昆明文汇商务会议酒店），酒店软、硬件环境完全满足会议需要。
5. 会议组织单位发起单位：国际测量与仪器委员会(ICMI)国家自然科学基金委员会中国计量测试学会中国仪器仪表学会承办单位：国际测量与仪器委员会中国计量测试学会计量仪器专业委员会哈尔滨工业大学协办单位：SPIE (负责会议论文集出版)昆明理工大学北京信息科技大学合肥工业大学6. 大会主席谭久彬院士哈尔滨工业大学7. 拟参会单位（依据往届会议信息统计）国际：英国牛津大学，英国伯明翰大学，英国Warwick大学，英国帝国理工大学，英国伦敦大学，德国柏林工业大学，德国不莱梅大学，德国亚森工业，瑞典Lund大学，匈牙利布达佩斯理工学院，波兰罗兹工业大学，波兰华沙工业大学，澳大利亚Swinburne大学，美国威斯康辛大学，美国加州理工学院，美国华盛顿大学圣路易斯分校, 日本东北大学，日本东京工业大学，日本大阪大学，日本东京农工大学，新加坡国立大学，新加坡南洋理工大学，韩国浦项工业大学，俄罗斯圣彼得堡光机与信息大学，俄罗斯圣彼得堡大学，莫斯科大学，新加坡国立大学，俄罗斯科学院新西伯利亚分院,德国联邦物理研究院（PTB），英国国家物理实验室（NPL）,美国国家标准与技术研究院(NIST)，俄罗斯门捷列夫计量院，日本国家计量院，瑞士国家计量院，韩国国家计量院，韩国科学技术院，新加坡国家计量院等。
微电子机械系统研究领域的最新进展——IEEE MEMS 2018国际会议综述
微电子机械系统研究领域的最新进展—IEEE MEMS 2018国际会议综述宋宇，张海霞*(北京大学微米/纳米加工技术国家重点实验室，北京 100871)通讯作者：hxzhang@18年1月21日至25日在英国贝尔法斯特会展中心举行(见图1)，吸引了来自世界各国相关领域的600余位专家学者，共同探讨微纳传感工艺等领域的最新进展与科学前沿。
此次会议的大会主席由来自瑞士电子与微技术中心(CSEM)的Michel Despont教授与爱尔兰都柏林城市大学的Jens Ducrée教授共同担任，并设置了最佳口头报告奖与最佳张贴报告奖，得到了国际电气与电子工程协会（IEEE）与IEEE机器人与自动化学会等多个国际组织的大力支持。
图1 MEMS 2018会议开幕式1 MEMS 2018会议技术概述MEMS 2018国际会议从1月21日至25日，历时五天，包括大会特邀报告、分专题口头报告以及张贴报告等内容，会议主题分为6大类，包括生物医学微机电系统、材料工艺与封装技术、执行器与能量微机电系统、电磁应用器件、物理传感器与微/纳流体等领域，几乎涵盖了微机电系统领域的所有研究方向。
本次会议共接收到来自全世界28个国家和地区的摘要投稿874篇，采用双盲审机制，经过技术委员会38名专家认真细致的评审工作，共有347篇文章被会议收录，其中86篇文章被选为大会口头报告，261篇文章被选为海报张贴报告，会议整体录用率为40%。
值得一提的是，本次会议共收录来自中国大陆的文章63篇，占到会议总收录文章数的20%左右，充分体现了我国在微机电系统领域的迅猛发展[1]。
按照MEMS会议的传统，MEMS 2018同样只设置一个主会场，会议流程则包括4个大会特邀报告、15个分专题口头报告和3个海报展示环节。
在大会开始环节，大会主席首先对本届MEMS 2018会议进行了全面的介绍，值得一提的是，会议参会人员数量达到了历年在欧洲举办该会议的第二高值，论文接受量与投稿量也保持了稳步提升，一系列数据也显示了微机电领域迅猛发展的态势。
第十八届国际电磁领域计算会议-CEFC2018
第十八届国际电磁领域计算会议（2018年10月28—10月31日中国杭州）各位专家、学者：IEEE国际电磁领域计算会议是电磁领域内每两年举办一次的科技学术盛会。
第十八届国际电磁领域计算会议是由IEEE电磁学会、中国电工技术学会、中国电机工程学会联合主办，将于2018年10月28－31日在杭州举行。
本次会议旨在为电磁场与电磁波相互作用的分析建模与仿真方法提出最新的发展与应用，重点是针对低频和高频器件的计算机辅助设计、组件和系统。
在此我们诚邀相关从事电磁领域的专家、同行及在读研究生积极投稿并相聚杭州，以全面展示来自世界各地的专家在静态和准静态场波的传播、材料模型、耦合问题数值技术领域，优化设计，软件方法学，纳米磁性材料，纳米光子学，生物电场的计算和应用等方面取得的进步。
会议网址：一、会议召开时间及地点时间:2018年10月28—10月31日地点：杭州望湖宾馆二、会议注册费在8月20日之前注册汇款：IEEE会员代表：4300元/人（国内）；650美元/人（国外）非会员代表：5000元/人（国内）；750美元/人（国外）学生：2300元/人（国内）；350美元/人（国外）陪同人员：2000元/人（国内）；300美元/人（国外）额外论文提交费用（每篇）：1000元/人（国内）；150美元/人（国外）在8月20日之后注册汇款：IEEE会员代表：5000元/人（国内）；750美元/人（国外）非会员代表：5600元/人（国内）；850美元/人（国外）学生：3000元/人（国内）；450美元/人（国外）陪同人员：2000元/人（国内）；300美元/人（国外）额外论文提交费用（每篇）：1000元/人（国内）；150美元/人（国外）#会议注册费包含会议期间餐费、资料费、会议费等。
住宿费和差旅费自理。
三、汇款账户信息本次会议由杭州百步会展服务有限公司代理收费、发票及会务。
参会代表食宿、差旅费自理。
户名：杭州百步会展服务有限公司账号：385768371609开户行：中国银行杭州中晖支行CEFC秘书处杭州百步会展服务有限公司2018年8月1日。
The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communica
REPRESENTATION OF CLASSIC MAPS FOR MOBILE DEVICES. ANINTERACTIVE MOBILE MAP APPLICATIONJohn Garofalakis garofala@ceid.upatras.gr Pantelis Papapoulias papaoul@ceid.upatras.gr Athanasios Plessas plessas@ceid.upatras.grUniversity of Patras , Computer Engineering and Informatics Department Research Academic Computer Technology Institute University of Patras , Computer Engineering and Informatics Department University of Patras , Computer Engineering and Informatics Department Research Academic Computer Technology Institute Patras, Greece Patras, Greece Patras, GreeceA BSTRACT Nowadays, the rapid growth of mobile devices and mobileapplications has changed the way we live. Mobile devices arewidely used and they are providing people with neededinformation anytime and anywhere. People use mobileapplications in many ways, for business purposes, as anorganizer or even for entertainment. The development ofmobile applications needs to be adapted with the specialfeatures and limitations of these devices.Looking in this direction, we present a mobile map application that we have developed for Microsoft Windowsmobile users, which is using geographic data stored in the device’s memory and allows the user to navigate through the map of different cities. A special feature of our application is the simulation of a classic map by giving the user the opportunity to take notes and marks on the map by clicking on the device’s screen. These data are stored in the device and based on them we propose some ways to make navigation in mobile map applications faster and easier. I. I NTRODUCTION The term mobile devices, refers to devices that have beenspecially designed to be used while their user is moving. Thiscategory includes mobile phones, PDAs (personal digitalassistant), smartphones and Tablet PCs. A laptop is designedto be portable, but its user needs to sit down in order to use iteffectively, therefore it is not considered to be a mobiledevice. Tablet PCs overcame this limitation by replacing thekeyboard with a special interface that allows the interaction ofa pen with a touch screen; however, they still remain muchbigger than the other handheld devices.In our days, we observe a rapid growth of mobile devices.This evolution came with the user’s need for accessing digitalinformation anywhere and anytime. Therefore, manyconstraints of mobile devices that in the past posed severeproblems to the mobile applications’ development are nowsuccessfully overcame. Technologically advanced trendydevices provide also new benefits. Limitations of processingpower, memory and screen size are reduced. So, there arenew capabilities to develop mobile applications that can beexecuted in the device.In this paper we present a Windows Mobile [7] applicationthat allows the users of mobile devices to interact with mapsthe same way they do with a classic paper map. Thisapplication uses geographic data in digital form stored in thedevice’s memory to generate maps for different cities andalso allows the user to take marks and notes on the map. Laterin this paper we outline why these notes can be very useful indeveloping mobile applications.We organize the rest of the paper in the following way. Insection 2, we present related work on this field. In section 3,we refer to the constraints that mobile devices face. In section4, we describe the application and its design principles. Insection 5 we outline the feature of taking notes and creatingmarks on the map. Finally, in section 6, we give ourconclusions and the direction for future research.II. R ELATED WORKA large number of map applications for handheld devices has been developed following different approaches. One interesting approach is the m-CHARTIS [2] system developed at the University of Patras. The m-CHARTIS system is a device independent mobile map application that enables mobile users to access map information from their device. This application uses geographic data to create webmaps that can be accessed by any mobile device.Another approach is msn mobile maps [8], which is a webbased application for mobile users. The user can navigatethrough web maps that are accessed by mobile devices. Theusers access the maps by using the web browser of the device.Another application is also Google maps for mobile [3],which is a mobile application that uses internet connection toaccess geographic data and navigate through the maps.Google maps for mobile is a downloadable application thatlets the user view maps and satellite imagery, find localbusinesses, and get driving directions on the mobile device.Another mobile application which also uses internetconnection to access geographic data is Zoom a Map [11].This application uses vector graphics to create the maps thatprovides the users with spatial data.As we can see, all related applications fail in one point;they need an internet connection to access the data from themobile device. Some disadvantages of this method are thehigh cost for mobile internet connection, connection delaysand problems of adaptation in different devices. To overcomethese problems we developed a mobile device for WindowsMobile operating system to make good use of thetechnologically advanced capabilities of the devices thatsupport this technology. In this direction, our applicationstores the geographic data at the device’s memory to avoidaccessing data through the web. Therefore, the applicationdoes not need internet connection.1-4244-1144-0/07/$25.00 ©2007 IEEE.III. C ONSTRAINTS OF MOBILE DEVICESIn the past few years a rapid growth of mobile applications was observed and many performance limitations of mobile devices compared to personal computers have been surpassed. Nevertheless, mobile devices still face important constraints [4] [9] that influence software development for these devices. The most important limitations are summarized as follows:• Restrictions of screen size – The capabilities of thesetypes of screens for mobile devices are lower than others for desktop computers. Screen resolution is lower and therefore the pictures are not displayed well. Our application reduces this limitation thatmakes map navigation more difficult. Also, we propose a solution for easier navigation on these types of screens by using an interactive method of navigation in our mobile application.• Processing power – Mobile devices cannot use the same hardware as desktop computers because of their small size. Consequently, we lose processing power because of the need for the small size of these devices. At the same time, an important limitation tothis direction is also energy, because handhelddevices are using portable batteries. These limitations of processing power do not restrict us to develop graphics applications that use spatial data.• Storage space – Mobile devices also have limited temporal and permanent storage space, but the geographic data that we are using in our application can be stored in the memory of the device since their size is small.Apart from the above limitations there are also some others that we would not mention because they do not concern our implementation. The mobile application developer must take into consideration the above mentioned constraints. Later in this paper we propose some ways to reduce some of these limitations when using mobile map applications.IV. T HE INTERACTIVE MOBILE APPLICATIONA. Overview The application we present is a system that displays and manages geographic data of cities on handheld devices. The application requires a handheld device with Microsoft Windows operating system. The digital map of our systemrepresents the use of classic maps in the way people interact with them.The user of this mobile application is able to navigate through the map and also get useful information about selected places such as museums and theatres. It is obvious that this application can be useful as a tourist guide, professional guide etc. Moreover, a very important fact is thatthis mobile application provides the user with geographic information in any place even if he is changing his location. The most important feature of our system is the ability to interact with the users and collect useful information about their navigation habits.B. Technical detailsFor the development of this mobile application we have used Microsoft Visual Studio .NET [6] and the programming language C# (C Sharp). For the drawing of the geographic data we have used the methods of the class System.Drawing.Graphics [1] of the .NET Compact Framework, which is a programming framework specially designed for mobile devices and it is based on their particular requirements and limitations.Table 1. System.Drawing.Graphics methods for vector drawing Method FunctionDrawLineDraws a line using a pen DrawPolygon Draws the outline of a polygon using a pen DrawRectangle Drawsthe outline of a rectangle using a pen FillEllipseFills the interior of an ellipse using a brush FillPolygonFills the interior of a polygon using a brush FillRectangle Fills the interior of a rectangle using abrush We have chosen the vector graphics model by using the System.Drawing.Graphics methods. There are many reasons[10] that led us to this choice between raster and vector models and mainly the fact that this application targets mobileusers. We have decided to follow the vector model because this model allows the user to navigate through the map and zoom in and out without losing the quality of the image.Drawing the map on this application is based on the shapes that are specified in the files that contain the geographic data and also the use of the methods described in table 1 was easier and simpler without time-consuming processes. Furthermore, the vector model does not have high requirements of memory in contrast with the raster model,because there is no need to store every single pixel of an image but the characteristics of the shapes described by the geographic data. The constraints of low memory of handheld devices justify the adoption of the vector model for the development of our application. On the other side, vectorgraphics require more processing power to be processed and displayed. Thus, taking into account the pros and cons of the model we have chosen the vector model to develop the graphics of this mobile application.The geographic data that we had in our disposal were in the form of digital data, stored in shapefiles in the server.Shapefiles are binary files, which are used by the GIS (Geographic Information System) packages of the ESRI company. In order to develop C# code that would read these files we should follow the guidelines of the shapefile technical paper published by ESRI.Since, however, data are in binary form and as a result not directly human readable, the relation between time cost and benefit would be disproportional if we decided to develop code that would parse the shapefiles and draw their data in the map image. Therefore, we had to transform our files toanother file type, human understandable, for example as simple text. For this purpose, we have used MapInfoUniversal Translator, a tool which is used to transform geographic data files in different formats.There are two popular file types that meet our demands: MIF (MapInfo Data Interchange Format) files, supported by MapInfo and E00 (Arc Export File Format) files, supported by ESRI. After studying the technical reports published for these two file types and opening the same file in these two different formats with a text editor, it is definitely clear that MIF files [5] are more understandable. Therefore, it is more effective to use them for the development of the file parser. For this reason, we have decided MapInfo files to be the input of our application for map drawing.C.Functionalities of the interactive mobile applicationThe basic feature of our application is the navigation though the map of different cities. As we can see in figure 1, the user can navigate through the map, search for a specific street using the street name in the form and get useful information about museums, theatres etc. This application was developed to provide the users with any kind of useful data they need in a user friendly interactive environment.Figure 1. In the left side is shown the basic tools of the application and in the left the user is searching for a streetname.To navigate through the map the user must use the hardware buttons of the mobile device and also use the zoom in/out buttons of the application. Our mobile map application displays the graphics without quality loss in any zoom level. Geographic data are loaded in the device’s memory once at the beginning when the user starts the application and in every step on the navigation process a small number of arithmetic transformations are executed. In this way the application becomes faster because there is no need to repeat the time-consuming transformations we describe in section D. There are also some extra options such as a help menu, map initialization etc. The user can also search for the location of a street by filling the form with the street’s name. When the user types the street name, the selected street appears with a different colour so that he can easily locate it in the map.If the user selects one of the existing categories such as the museum or the theatre category, the application displays the selected points in the map. By clicking near these points (an area of 10 pixels width) a short description of the selected item is displayed in a new window. The selected items have different colour in the map in order to be easily located as shown in figure 2.Figure 2. Displaying the points of the selected category The user is also able to choose geographic data of a different city by selecting the appropriate files that are stored in the device’s memory.The geographic data are stored in the memory of the mobile device in digital format (MIF files) and so the application does not need a wireless connection to access these files. Users can transfer these data from a personal computer to the device by using Bluetooth to avoid the high cost of GPRS connection and network problems. The mobile application uses as input the geographic data and generates the map of the city. The device’s processing power is enough to execute the application without delays.The user of the application can click on any point of the map in order to select some places of the city that he wants to remember their location. In this way, our application represents the way people use classic maps by drawing on the map some points that we are interested in. To select and mark a point of the map we just need to click on the map. Each user can select different points of the map and the application stores these points of interest so that it can be used in any way in the future by the user or the application. The user can also delete these points. We will also explain in a following section why this information is very useful.D.Data transformations and map drawingThe application, at first parses the geographic data from the files and then a number of transformations are applied in order to draw the map and display the data. The first transformation is a transfer of the axis in order to transform the coordinates from the original coordinate system to the reference system that corresponds to the image displayed in the screen. In figure 3, the shadowed part corresponds to theregion that the geographic data cover in the original coordinate system. By finding the minimum abscissa and the minimum ordinate of this part and subtracting them from each abscissa and ordinate of the shadowed part we transform the axis. If x and y are the coordinates of a point of the shadowed part of figure 3, the new coordinates after the transformation are:x’ = x – xminy’ = y – yminFigure 3. The transfer of the axisFollowing, a new transformation has to be applied, so that the coordinates of the points are transformed to coordinates in the image, that is to say coordinates-pixels. An important point is that for computer screens and for digital images, as start of the axis is considered the upper left corner and not the down left corner. If the maximum abscissa of the shadowed part of figure 3 is xmax and the maximum ordinate is ymax, our map will have xmax – xmin width and ymax – ymin height. The new coordinates after these transformations will be:x ΄΄ = x ΄ = x – xminy ΄΄ = (y max – y min ) – y ΄ = y max – y min – (y – y min ) = y max – y min –y + y min = y max – y When the user selects a point by clicking on the map, a reverse transformation of the data is executed. If the user selects a point on the device’s screen we only know the exact location of the selected pixel and so we have to transform this location on the screen to geographic data of the map so that it can be stored in the device’s memory. This transformation depends on the zoom level and any previous navigation through the map.V. C LASSIC MAP REPRESENTATION AND DATA STORAGE The mobile application that we present can store the selected points for any further use. Our application represents the use of a classic map but also gives the user the ability to delete these points and initialize the map. The selected pointscan make the navigation through the map easier and can be useful for many reasons that we describe below.Our application allows the user to mark any point of the map and store this point. If he clicks on a point, then a red spot is drawn on the map for this location. The user is able to store a comment for this point. This is a common action that we perform when we use classic maps, to write a comment for a place that we want to remember on a map. The mobile application represents this action but also provides the user with the advantages of a digital map.Figure 4. Points of interestEvery point of the map represents an exact location of the real world and therefore any selected point is a point of interest for the user and this might be his home, school etc. If a user selects many points in one specific area of a city that means that he is interested more for this area than others and he might be familiar with the selected area.Therefore, in the future, the areas that are more frequently selected by a user can become the starting part of the map when the application starts. Only a small part of the map can be displayed on the mobile device because of its small resolution and screen size and so if the navigation starts from the most frequently selected area of the city, the navigation process becomes shorter and easier. In this way the user spends less time to navigate through the map and get all the information he needs.In addition, the user is more familiar with the most frequently selected areas of a city and the whole navigation process becomes easier because he knows in which direction to navigate and get the information he is searching for. In this way we can avoid a very time-consuming part of the navigation process.The navigation through the map apart from being a time-consuming process also requires processing power to perform all the transformations and draw the graphics while navigating. Therefore, by using the data of the selected points in the map it is possible to gain double benefit.VI.C ONCLUSIONS AND FUTURE WORKIn this paper we presented an interactive mobile map application which simulates the use of a classic map and we propose solutions for easier and faster navigation through the map for mobile applications. This application is specially designed for mobile devices taking into consideration the limitations of this type of devices.In the future we intend to add more features in our application. We are planning to implement the features that we have presented in section 5 by using as we have described the stored data of the selected points in the map to make the navigation easier and faster. Furthermore, we are planning to implement the feature of storing multiple users. The data from the selected points of each user can be stored in a database so that we are able to use them by enriching the areas of the map with more information that seems to attract more interest from the users.R EFERENCES[1] D. Durant, P. Yao. ".NET Compact Framework Graphics",/articles/article.asp?p=336257&rl=1 [2] J. Garofalakis, T.-A. Michail, A. Plessas. "Web Based DeviceIndependent Mobile Map Applications. The m-CHARTIS system", in proceedings of IW3C2 2006 in Edinburgh, UK[3] Google mobile maps, /gmm/index.html[4] A. Kaikkonen, V. Roto. "Navigating in a Mobile XHTML Application",in proceedings of SIGCHI 2003, pp.329-336.[5] MapInfo Corporation. "Appendix J: MapInfo Data Interchange Format,MapInfo Professional User’s Guide v.7.0", pp.683-705Microsoft Visual Studio, /en-[6]us/library/fx6bk1f4(VS.80).aspx[7] Microsoft Windows Mobile, /windowsmobile[8] Msn mobile maps, /maps/maps.aspx[9] V. Paelke, C. Reimann, W. Rosenbach. "A Visualization DesignRepository for Mobile Devices", in proceedings of the 2nd International Conference on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa, 2003, pp.57-62[10] R. Rosenbaum, C. Tominski. "Pixels vs. Vectors: Presentation of largeimages on mobile devices", in proceedings of IMC 2003.[11] Zoom a map, /。
2018年第18届IEEE通信技术国际会议
2018年第18届IEEE通信技术国际会议（ICCT 2018）2018年10月8日-11日, 重庆，中国大会组委会诚挚的邀请来自全球的作者，专家学者注册参与本次大会！请填写如下注册表格，并将填好的注册表，论文终稿（doc.+pdf.），汇款凭证以及版权的扫描件，发回会议邮箱:基本信息1. 有文本输入框的单元格，请在文本输入框内填写信息，请不要删除填写框，或在框外填写注册费用明细****以学生价注册文章，该学生须为该论文的第一作者，请注册时附上学生证等证明文件的扫描件。
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A Fuzzy-Based Dynamic Load-Balancing AlgorithmKun-Ming V. Yu*, and Chih-Hsun Chou**Department of Computer Science and Information Engineering,Chung-Hua UniversityHsin-Chu, Taiwan 300R.O.C.Yao-Tien Wang††Department of Computer Science and Information EngineeringNational Central UniversityChungli, Taiwan 320R.O.C.ABSTRACTMany dynamic load-balancing algorithms have been proposed for parallel and discrete simulations. But the actual performances of these algorithms have been far from ideal, especially in the heterogeneous environment. In this paper, we design and implement a load-balancing system based on fuzzy logic control. The fuzzy algorithm has been implemented in a loosely coupled distributed system. On-line of workload measure has been addressed herein as being the load information policy, negotiation policy, and migration policy. The experimental results indicate that the fuzzy-based load- balancing algorithm not only effectively reduces the amount of communication messages but also provides considerable improvement in overall performance such as short response times, high throughputs, and short turnaround times.Key words: Fuzzy Logic Control, Dynamic Load Balancing, Distributed Computing System.1. IntroductionLoad balancing in a distributed system is a process of sharing computational resources by transparently distributing system workload. With the advent of high-speed communication links, it has become beneficial to connect stand-alone computers in distributed manner through a high-speed link. The primary advantages of these systems are high performance, availability, and extensibility at low cost. Therefore, distributed computing has gained increasing importance in the recent as a preferred mode of computing over centralized computing. Many researches have proposed different kinds of approaches for the load-balancing problem [1, 6, 7, 8, 9, 10, 11]. A distributed computing system comprises of software programs and data resources dispersed across independent computers and connected through a communication network. A workstation user may not use the machine all the time, but may require more than it can provide while actively working. Some hosts may be heavily loaded, while other remains idle. Performanceenhancement is one of the most important issues in distributed systems. The performance of the system can often be improved to an acceptable level simply by redistributing the load among the hosts.The load balancing schemes conceptually can be categorized into two types: static and dynamic. We say a scheme is static, if it applies load-balancing technique while dispatching tasks into computing hosts. However it does not satisfy the real case that the workload is fluctuant in the computing cluster. The dynamic load-balancing scheme reallocates the computing tasks according to the current workload of each host. Therefore, it has better performance comparing with static scheme. A load balancing system is composed of three design issues: the information gathering policy, the negotiation policy and the migration policy [1]. Traditional strategies of the load balancing systems usually take advantage of some fix values to distinguish workload (e.g. over-loaded or under-loaded). Many load-balancing approaches based on this conjecture have been introduced in the past [1, 6, 7, 8, 9, 10, 11]. In conventional load balancing systems, resource indexes are necessary to be the input training data, and the output (threshold of workload) can be decided impersonally. But the output values are fixed; it cannot indicate the degree of the workload. Moreover, there exists a sharp distinction between members and non-members; the tasks reallocation action will be made frequently around the threshold. This will result in an unstable system and cause unnecessary overhead. Moreover, the workload estimation of each host is very difficult and time-consuming.To resolve these problems, we propose a Fuzzy-based dynamic load balancing scheme for evaluating the workload of each host as well as determining a suitable destination host to receive (send) jobs. In the scheme, we adopt run-queue length and CPU utilization as the input variables for fuzzy sets and define a set of membership function. It has been shown that our proposed load balancing algorithm not only effectively reduced the amount of communication messages but also provides considerable improvement in overall performance such as short response times, high throughput, and short turnaround times.The remainder of this paper is organized as follows. Section 2 describes the proposed fuzzy-based load balancing algorithm in detail and the system structure, respectively. Section 3 presents the experimental results. Finally, the conclusion is given in Section 4.2. Distributed Load Balancing ModelsIn distributed model, every host has a local monitor associated. Each monitor collects and updates the information about the state of the local host. The primary advantages of this model are high performance, availability, and extensibility at low cost. Conventional algorithms of distributed load balancing including Random [1], S ender-Initiated [1], Receiver-Initiated [1] and Symmetric Algorithm [3].2.1 Random AlgorithmAmong the algorithms, the Random Algorithm is the simplest one [1]. In this algorithm, each node checks the local workload during a fixed time period. When a node becomes over loaded after a time period, it sends the newly arrived job to a node randomly no matter the load of target node is heavily or not. Only the local information is used to make the decision. The Random Algorithm has the lowest overhead because of its simplicity and without negotiation with other hosts. However, it can’t reallocate the system load balancing very well.2.2 Sender AlgorithmThe Sender algorithm is based on the Sender policy [3]. When a node becomes over-loaded after a period of time, it selects the target node randomly and looking for its load status which is under-loaded or not. If it is under-loaded, an ACCEPT message is feedback to original host, otherwise it replies a REJECT message. If the requesting node is still over-loaded when the ACCEPT reply arrives, the newly arrived task is transferred to the probed node; otherwise the task keeps executing locally. This mechanism seals to push a task from the requesting node to the probed node after a period of time checking.2.3 Receiver AlgorithmThe Receiver Algorithm is designed according to the Receiver policy [3]. Once if a host becomes under-loaded, the node will poll the information form any other node to check if it is over-loaded. When an overloaded nodes was found, an ACCEPT message is feedback, otherwise it replies a REJECT message. The migration of a task from the probed node is still under-loaded.2.4 Symmetric AlgorithmIn comparison with the Sender Algorithm and the Receiver Algorithm, the Symmetric Algorithm shows two-side effects: when a node becomes over-loaded, Sender algorithm enabled; when it is under-loaded, the Receiver algorithm is active. This algorithm is combination version of the Sender and Receiver algorithm. In other words, this model is adjusted based on the current load-level of the node by allowing the algorithm to switch automatically between Sender and Receiver algorithm. When the load status is over-loaded, it plays the role of the Sender algorithm; in contrast, it plays the role of Receiver algorithm.3. Fuzzy Logic Control-based Load Balancing SystemThe design of Fuzzy Logic Control consists of four modules: a fuzzy rule base, a fuzzy inference engine, fuzzification, and defuzzification. The linguistic approach of system modeling can be formulated in three distinguishing features: the use of linguistic variables in place of or in addition to numerical variables; the characterization of simple relations between variables by IF-THEN fuzzy rules; the formulation of complex relations by fuzzy reasoning algorithm.The structure of a load balancing system is composed of three design phases: the information policy, the negotiation policy and the migration policy [7]. By applying fuzzy logic control to these three design phases, we can effectively raise the overall performance in a distributed system. We can construct different run queue length membership function, CPU utilization membership function, and center value for linguistic labels around through fuzzy c-means clustering algorithm according to various platform characteristics capacity.The migration policy pertains to managing the migration of tasks form one host to another. The numbers of migrated tasks are according to the value calculated by MAX-MIN composition from the CPU utilization and queue length. Measurements of input variables of a fuzzy controller must be properly combined with relevant fuzzy information rules. The purpose of defuzzification is to convert each result obtained from the inference engine, which is expressed in terms of fuzzy sets, to a single real number. We used centroid method because it supports software real time fuzzy controls to distinct the difference of workload on two machines.3.1 Information PolicyThe information policy indicates the significance of various information regarding the system. From which, information gathering fuzzy rules is used to determine the system workload is heavy or not. Many researchers use CPU queue length as the single load index for a host in distributed system. Although CPU queue length is the obvious factors impacting on the system load, there are other factors also influencing the computing load, such as CPU utilization, disk I/O, memory paging, network, etc. For the accuracy of evaluating the load status of a host, we employ the CPU queue length and CPU utilization as the input variables for fuzzy sets. Fuzzification function is introduced for each input variable to express the associated measurement uncertainty. The information gathering process can be started periodically or in dependence on significant changes of system states.3.1.1 Membership FunctionA fuzzy set can be defined mathematically by assigning to each possible individual in the universe of discourse a value representing its grade of membership in the fuzzy set. These membership grades are represented by real-number values ranging between 0 and 1 and fuzzy implication, T, is a function of form T:[0,1] × [0,1] → [0,1]. The support of a fuzzy set A contains all element of x that has a nonzero membership grade. Support(A) = {x ∈ X | u A(x) > 0 }. We assume that the range of CPU queue length and CPU utilization fuzzy sets represent linguistic concepts system load as Light, Medium, and Heavy. Fuzzification function is introduced for each input variable to express the associated measurement uncertainty. Figure 1 and 2 shows the 3-level linguistic concepts system load of CPU queue length membership function and CPU utilization membership function respectively.Figure 1: CPU queue length membership Figure 2: CPU utilization membership function function3.1.2 Inference engineMeasurements of input variables of a fuzzy controller must be properly combined with relevant fuzzy information rules to make inferences regarding the system Load State. In our system with variables CPU queue length, CPU utilization, we may proceed as follows. The purpose of the fuzzification function is to interpret measurements of input variables, as an example, a fuzzification fCPU queue length applied to variable CPU queue length. Then, the fuzzification function has the form fCPU queue length:[0,n] →R, where R denotes the set of all fuzzy numbers, and fCPU queue length (X0) is a fuzzy number chosen by fCPU queue length as a fuzzy approximation of the measurement CPU queue length = X0. It is obvious that, if desirable, other shapes of membership function may be used to represent the fuzzy numbers fCPU queue length (X0). For each measurement CPU queue length = X0, the fuzzy fCPU queue length(X0) enters into the fuzzy inference process. We convert the given fuzzy inference rules of the form CPU queue length membership and CPU utilization membership function intoequivalent simple fuzzy conditional propositions of the form:Rule 1: IF (CPU queue length, CPU utilization) is A 1 x B 1, then system load is C 1ORRule 2: IF (CPU queue length, CPU utilization) is A 2 x B 2, then system load is C 2OR……………………………………………………………………….ORRule n: IF (CPU queue length, CPU utilization) is A n x B n , then system load is C nFact: (CPU queue length, CPU utilization) is fcpu queue length (x 0) x fcpu utilization (y 0) Conclusion: System load is C.3.2 Negotiation PolicyThe negotiation policy selects the host to or form which tasks will be migrated when the load reallocation event takes place. The knowledge pertaining to the given control problem is formulated in terms of a set of fuzzy inference rule. We use three load actions, which are send-state (heavy), stabilize-state (moderate), and receive-state (light).3.3 Migration PolicyThe migration policy pertains to handle the migration of tasks form one host to another. The numbers of migrated tasks are according to the value calculated by MAX-MIN composition from the CPU utilization and run queue length. Measurements of input variables of a fuzzy controller must be properly combined with relevant fuzzy information rules. The purpose of defuzzification is to convert each result obtained from the inference engine, which is expressed in terms of fuzzy sets, to a single real number. We used centroid method because it supports software real time fuzzy controls to distinct the difference of workload on two machines. This value is calculated by the formula:Y 0 =∑=1i n W i * B i / ∑=1i nW i. (1)Where Y 0 = output of fuzzy control,W i = the antecedent degree of i th control rule andB i = the consequent center value of i th control ruleFigure 3 depicts the architecture of the Fuzzy-based dynamic load-balancing algorithm.The typical architecture of a FLC, which is composed of four principal components: a Fuzzifier , a Fuzzy Rule Base , an Inference Engine , and a Defuzzifer . In the information policy, the fuzzifier has the effect of transforming crisp measured data into suitable linguistic values. Then the fuzzy rule base stores the empirical knowledge of the operation of the process of the domain experts. Moreover, the inference engine is the kernel of FLC, and it has the capability of simulating human decision making by performing approximated reasoning to achieve a desired control strategy. After these steps, the workload would be decided. According to the host is over-loaded or under-loaded, negotiation policy would initiate to find the suitable host to make the task migration. Finally, if the target node was found, the migration policy will take advantage of defuzzification to calculate the number of migrated tasks.Figure 3: The overall structure of Fuzzy-based load balancing algorithm.4. Experimental ResultsIn order to show that our FLC-based load balancing algorithm will accomplish a high system performance, we use Java programming language to construct a distributed load balancing computing environment. Since Java language is suitable to support heterogeneous distributed computing system. We use six workstations running different UNIX Operating System to build a heterogeneous computing environment. These workstations are located on different NFS and connected by communication network.The experimental results reveal that the proposed load balancing system yields better performance as compared with others conventional algorithm. Figure 4 shows the response time of different load balancing schemes in the cases of different work sizes. We found that our proposed load balancing scheme has the shortest response. Figure 5 presents the turnaround time of different load balancing schemes in the cases of different work sizes. From the figure, we found that our proposed load balancing scheme has the shortest turnaround time. Especially, our proposed scheme performs well when the number of jobs is large. The throughput is also discussed in our experiments. Figure 6 shows that our proposed scheme has the highest throughput. For the reducing of unnecessary communication message, Figure 7 indicates that our algorithm has the smallest number of request message among all load balancing approaches.Figure 4: The response time of different load balancing schemesFigure 5: The turnaround time of different load balancing schemesFigure 6: The Throughput of different load balancing schemesFigure 7: The number of messages sent of different load balancing schemes4. ConclusionWe have proposed a new dynamic load balancing scheme based on Fuzzy Logic Control. The FLC-based algorithm is used to correctly evaluate the load status of a host in heterogeneous computing system. It also can efficiently determine the suitable host for migrating jobs. The performance of proposed scheme is better than that of the conventional schemes on the turnaround time and throughput. It also can effectively eliminate the unnecessary communication messages between hosts in distributed system.Reference[1]K. Benmohammed-Mahieddine, P. M. Dew, and M. Krar, A periodic Symmetrically-Initiated LoadBalancing Algorithm for Distributed Systems”, IEEE ICPDS, 1994, pp. 616-621.[2]Y-C Chow and Walter H. Kohler, “Model for Dynamic Load Balancing in a Heterogeneous MultipleProcessor System,” IEEE Trans. on Computers, vol. C-34, No. 3, March 1985, pp. 204-217 .[3] D. L. Eager, E.D. Lazowska, and J. Zahorjan, ¡ A Comparison of Receiver-Initiated andSender-Initiated Adaptive Load Sharing,” Proc. Of the 1985 ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, Aug. 1985, pp. 1-3.[4]Mohammad R.Emami, I.burhan Turksen, and Andrew A. Goldenberg, “Development of A SystematicMethodology of Fuzzy Logic Modeling,” IEEE Transactions on Fuzzy System, vol 6, no 3, Aug. 1998, pp. 346-360.[5] D. Ferrari and S. Zhou, An Empirical Investigation of Load Indices for Load Balancing Applications,Tech. Rep.UCB/CSD/87/353, Computer Science Division, Univ. of California, Berkeley, CA, 1987 [6]H-C Lin and C. S. Raghavendra, “A Dynamic Load Balancing Policy with a Central Job Dispatcher,”IEEE Trans. On Parallel and Distributed System, Jul. 1991, pp. 264-271.[7]Margaret Schaar, Kemal Efe, Lois Delcambre, and Laxmi N. Bhuyan, “Load Balancing with NetworkCooperation”, IEEE Trans. On Parallel and Distributed System, Jul. 1991, pp. 328-335.[8]K-M Yu, Siman J-W. Wu, and Tzung-Pei Hong. A Load Balancing Algorithm Using Prediction”,IEEE Computer Society. The Second Aizu International Symposium on Parallel Algorithms/Architecture Synthesis. March 17-21, 1997, pp. 159-165.[9]K-M Yu, Siman J-W. Wu, and Tzung-Pei Hong. “An Adaptive Load Balancing Algorithm inHomogeneous System”, Proceedings of 1997 Workshop on Distributed System Technologies & Applications, pp. 496-503.[10]K-M Yu and L-K Wang. “A Dynamic Load Balancing Algorithm Using Artificial Neural Network”,Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, July 27-31, 1997, pp. 364-367.[11]Kun-Ming Yu, Yau-Tien Wang and Chih-Hsun Chou, “A Dynamic load balancing Approach usingFuzzy Logic Control”, Proceedings of the IASTED International Conference Artificial Intelligence and Soft Computing (ACS’99), August 9-12,1999.。
2018IEEEEMCSIPI国际会议获奖文章(二)
PAPER EXTRACTS2018IEEE EMC&SIPI国际会议----获奖丈章（二）2018IEEE International Symposium on EMC&SIPI—Best Paper Awards Part2A Scalable Reduced-Order Modeling Algorithm for the Construction of Parameterized Interconnect Macromodels from Scattering Responses摘要：提出了一种数字系统互连结构降阶宏模型的构建算法。
该宏模型是基于采样散射参数而获得的.它对应于一个解析近似的模型方程，且模型方程依赖于几何尺寸、材料特性等外部参数。
最终生成的参数化模型很容易变换为参数化的SPICE网络表，从而可用于系统级信号完整性和电源完整性的评估。
本文的主要贡献是采用去耦的方法形成模型拟合方程，该方法考虑了含有大量端口的互连结构的高效处理：所提出的参数化模型具有良好的稳定性。
关键词：模型降阶算法；参数化建模；宏模型；矢量拟合；信号完整性；电源完整性电气互连结构的非理想行为会影响到电子系统的信号完整性和电源完整性。
信号完整性和电源完整性分析中需要进行大量的电磁场或电路级仿真，仿真时通常要考虑几何尺寸及材料等参数的影响。
行为宏模型搭起了互连结构的电磁场特性与电路描述的桥梁。
通过频域场求解器获得端口的采样散射数据，采用宏模型工具对这样的响应计算频域有理近似，然后综合出等效电路，从而可以在SPICE求解器中分析系统级信号完整性和电源完整性。
矢量拟合(Vector Fitting,VF)方法由于其广泛的可用性、代码的开源性，以及与EDA软件的商业集成.已成为标准的宏模型构建工具。
本文通过在模型中嵌入独立的一个或多个外部参数，如几何尺寸或材料特性等，扩展了行为宏模型的思想。
模型将变为多变量形式，一个独立的变量是频率，另外的变量则是外部参数这样的参数化模型将使信号完整性和电源完整性的分析得以简化与高效。
2018IECCISPR年会主要技术内容(下)CISPRD
■2018CISPR PLENARY MEETING2018IEC/CISPR年会主要技术内家(下) The Summary of Technical Contents of2018IEC/CISPR Plenary Meeting Part2CISPR/D中国汽车技术研究中心有限公司张旭1CISPR/D路线规划图•CISPR/D标准工作的优先级根据各国家委员会以及各工作组专家回复情况，确立了如下CISPR/D范围内的标准工作优先级：a)CISPR12b)CISPR25_General_Common_Partsc)CISPR25_Vehicle_Antenna Terminald)CISPR25_Component_CE_Current Probee)CISPB25_Component_RE_ALSEf)CISPR25_Component_RE_TEM Cellg)CISPR25_Component_RE_Striplineh)CISPR25_HV_Component_RE_ALSEi)CISPR25_HV_Component_Coupling Attenuationj)CISPR36k)PAS62437•CISPR/D新课题工作的优先级CISPR/D于2016年年会后梳理出13个CISPR/D今后关注的新课题.根据各国家委员会的回复情况，确立的优先级如下：a)New vehicle test methodology for quantitative evaluation of radio reception quality(signal to noise)b)Automated driving(radar,multiple sources,…)c)C2X conimunication(consideration of multiple antenna)d)Component Magnetic field eniissione)Vehicle near—field radiated emission(specific location and mobile devices frequency range)f)Conducted emission on vehicle in charging modeg)Follow-up and justification of standards creation, evolutions and limitsh)Component near-field radiated emission(5—10cm)i)LV/HV attenuation for driveshaftj)Levels for health protectionk)Automotive EMC u reference immunity standard1)Component emission—Rrverber.Chamberm)Vehicle emission一Reverbrr.Chamber 2CISPR25相关议题・电流法测量规定的进一步细化日本代表对CISPR25AMD1的CEV法提出建议并被会议采纳：所有的低压线束应放置在电流探头内：如果EUT低压端口有多个连接器，且对应了多个线束,则测试计划应规定放置在电流探头中的线束。
《安全与电磁兼容》2019年总目录(总第156~161期)
评论电磁兼容的发展趋势………………………Frank Leferink 1 95G 通信面临的电磁兼容挑战及解决方法…………李尔平 2 9汽车EMC、计算机仿真和工业标准的最新报道—2019新奥尔良IEEE EMC+SIPI 国际会议的热点问题………Todd Hubing, Jason Bommer, Alistair P. Duffy 3 9产品EMC 风险评估技术……………………………郑军奇 4 9智能网联汽车电磁兼容测试验证的新挑战…………………………………………………………………………雷剑梅 5 95G 毫米波设备对EMC 符合性测试的影响…………………………………………………James Young, Jari Vikstedt 6 9驱动电机系统电磁发射研究驱动电机系统多端口电磁发射特性分析…………………………………………………………………高新杰 王志远 3 18车辆与驱动电机系统的辐射发射关联性研究………………………………………………………………高新杰 王志远 3 23车辆辐射骚扰源定位及优化电动汽车EMI 根源定位方法及优化策略…………………………………………………王志远 高新杰 冯来兵 等 4 17电动汽车BMS 辐射发射优化方法…………………………………………………………王志远 高新杰 冯来兵 等 4 21电动汽车电磁抗扰性测评电动汽车电磁兼容性测评发展趋势……………………………………………………………韩烨 高新杰 邱振宇 等 5 17电动汽车电磁抗扰测试分析……………………………………………………………………高新杰 韩烨 邱振宇 等 5 222018 CISPR 年会2018 IEC/CISPR 年会主要技术内容(下)……………………1 162019 IEC/CISPR 年会主要技术内容（上）…………………6 19EMC 材料应用镀Ni-Cu-La-B 玻璃纤维对电磁屏蔽复合涂料性能的影响…………………………………刘扬 管登高 胡德豪 等 1 23蜂窝吸波材料的研究现状：从基材到测试………………………………………………………张颖 盛家琪 刘列 等 1 27磁环的使用技巧………………赵五芹 赵阳 易华斌 等 2 45地铁空心电抗器盖板磁屏蔽效能分析…………………………………………………………毛瑞雷 张丹 肖建军 等 2 51羰基铁粉的电磁波吸收性能……………………………林媛 3 55石墨烯/EPS 颗粒填充水泥的宽频吸波性能…………………………………………………………………………程祥珍 3 60多层PCB 介质基板中嵌入高K 材料对信号完整性的影响…………………………………………………………胡玉生 4 53氧化石墨烯/碳纤维复合材料的制备及表征………………………………………………姜浩田 鞠艾洵 肖润平 等 4 58基于DGS 的EMC 高频共模噪声滤波……………高先科 5 53低频磁场屏蔽材料仿真与研制…………………………………………………………………王喆 李静 李炳章 等 5 59CDNE 法中支撑材料的介电常数更改为1.4的探讨………………………………………………………………李楠 6 41铁钴合金磁屏蔽薄膜的性能表征与工艺控制…………………………………………………韩利元 金鑫 陈志强 等 6 45期 页标准与应用IEC/ACEC 韩国会议综述………………………………李妮 1 31IEC 61851-21-2:2018标准测试难点介绍……………………………………………………郑上上 曾博 赖明宇 1 36解析GB/T 37130-2018……………张旭 蒋莉 刘欣 等 2 275G 承载网产品低时延及高精度时钟的抗扰性……王振英 2 34IEC 62368-1和IEC 60950-1对手机外壳的防火要求及差异……………………………………………………朱满 3 27GB 34660-2017与GB 14023-2011关于整车辐射发射试验的差异解析………………王东升 鲍宇 王子龙 等 3 30电磁兼容实验室评审中的典型问题……………刘佳 崔强 4 25基于Simulink 分析CS101测试设备配置引入的问题………………………………………………………叶畅 张强 4 28IEC/ACEC 日本会议综述………………………………李妮 5 35解析GB/T 36282-2018 ……王云 陈希琛 丁一夫 等 5 40 GJB 151B 中四个CS 项目试验电平施加的共同特点分析………………………………………………………陈世钢 6 26IEC/TC77及其分会上海会议综述………………………………………………………………李妮 尹婷 金善益 等 6 31解析ISO 11452-2:2019………………………付君 叶畅 6 35认证与标志工业机器人安全和电磁兼容认证检测与分析…………………………………………………易谦 皇甫亚波 蔺道深 1 41适用于MIMO OTA 认证及研发测试的辐射两步法…………………………………………沈鹏辉 漆一宏 于伟 等 2 37CE/FCC 认证中Spectrum Emission Mask 与Band Edge 的测试解析……………………………………招泽添 彭华睿 2 42日本多媒体设备干扰的自愿控制………………Akira Oda 3 35CBRS 类产品美国FCC 认证射频测试要求…………徐凯 3 39通信产品日本认证要点…………刘军鹰 牟芳氐 林奕翔 4 33无线通信终端设备CE/FCC 认证中的EMC 相关问题………………………………………张轩玮 王俊青 李艳 等 5 26 X 电容与Y 电容对电气安全及电磁兼容性能的影响…………………………………………………………何佳 李响 5 31CTIA 移动终端产品电池续航寿命评估方法…………李冬 6 71工程师日志低频模拟小信号的电磁兼容设计……………………朱文立 1 46实用整车EMC 性能开发方法探讨……………………马谦 2 56电动汽车用驱动电机系统EMC 测试………………罗辉生 3 43批量产品合格性判定法及应用………………………朱文立 4 39电气检测实验室电源特性核查方法………………………………………………………………王杰 叶长青 黄信锋 5 45信息类产品网口部分前期设计要点…………………赵五芹 6 51测试与测量无线电辐射骚扰测量中试验桌的影响评估…………杨顺家 1 48微带线法测量微波材料的复介电常数…………………………………………………………王佩佩 廖丽 唐章宏 等 1 53电动轮椅车电磁兼容测试方法解析…………刘浩明 叶瑀 2 59电磁辐射测试系统的谐波失真分析…………赵宏杰 李冶 2 65电源滤波器核电磁脉冲防护性能测试方法研究……………………………………………………………………胡景森 3 44工业机器人电磁兼容测试标准中的问题及建议……………………………………………………熊蒙 于超 宋江伟 3 51期 页《安全与电磁兼容》2019年总目录（总第156~161期）期 页期 页军用射频识别设备电磁兼容要求与测量研究…………………………………………………………朱赛 张强 叶畅 4 41整车辐射抗扰度发射天线探讨…………………………………………………………………何志辉 尹建文 黄涛 等 4 48电磁混响室场地性能参数确认方法………………………………………………………………熊蒙 叶琼瑜 焦琳 等 5 47电源EMI噪声源阻抗提取方法分析……………………………………………………………刘元龙 李伟 许科 等 6 52医院手术室电磁环境的检测和评价……………………………………………………………朱金俊 张武 包家立 等 6 57电磁仿真IEC 61000-4-8中矩形感应线圈磁场均匀性缺陷的分析………………………………李金龙 田禾箐 陈天华 等 1 59遥控接收机天线匹配电路设计及仿真………曾霞 黎小娇 1 64基于3D-DIFA的逆变器输出电压非线性失真分析………………………陈映卓 Balaji Narayanasamy 杨治 等 2 15渐进圆锥D-dot电场传感器频响分析……王悦 景莘慧 2 21“单端—差分”微带线串扰仿真分析…………………张昀 3 66开关电源RE102仿真与实测………………………………………………………………刘恩博 朱俊颖 王海星 等 4 63车载RKE天线布置的仿真优化………………………………………………………………鲍宇 赵明丽 王子龙 等 4 67通讯车多天线隔离度仿真…………吴啸晨 王媛 刘恩博 4 73电源功率线缆的串扰仿真分析……刘恩博 李庆颍 张钰 5 85柔直换流站宽频建模及传导电磁骚扰仿真………………………………………………张卫东 魏宇宁 张修武 等 5 91汽车玻璃天线电场仿真及线束布局优化………………………………………………………刘畅 郭加加 鲍宇 等 5 99吸波材料反射系数测量误差仿真分析………………………………………………………熊志成 景莘慧 周忠元 等 6 86 X波段矩形波导探头的介质加载优化……………………………………………………………张晓刚 霍宏艳 韩正涛 6 91电磁干扰抑制技术LED尾灯动态转向功能失效分析及对策…………………………………………………吴定超 吴大用 王骞岍 等 1 69某24 V系统车载终端电磁兼容测试和整改…………………………………………………张晨 邱振宇 吴在园 等 1 75某型网络交换机辐射发射超标的分析与整改………………………………………………………陈旗 阮鹏 刘洪颐 2 71机顶盒HDMI电磁兼容性设计改进………………宋文平 2 75电动汽车DC-DC变换器电磁骚扰的抑制………………………………………………刘庆鑫 张柏年 谭泽强 等 3 71小功率船用设备CE102项目的整改………………………………………………………………………张齐榕 任坤鹏 3 76某控制器网口芯片管脚的辐射骚扰消除………………鬲莉 4 78无人地面系统的电磁兼容性设计与应用……………………………………………………郝国欣 罗朝鹏 姜和俊 等 4 82电源线相关电磁兼容整改典型案例分析………………………………………………………宋金华 曹宏伟 廖伟 等 4 87智能马桶盖EMI测试条件初探…………………………………………………………………朱志鹏 还雅萍 尹海霞 5 64电动自行车电磁辐射发射测试及常见问题………………………………………………………马明宇 吕炎 韩烨 等 5 68显控台发射干扰测试及抑制………………………………………………………………………李娟 马静 杨晓峰 等 6 64医用多普勒血流仪的空气放电机理及防护…………陈宝祥 6 67专题研究系统电磁兼容性安全裕度实现………………………成伟兰 1 79遥感卫星地面站抗干扰策略………………………………………………………………………陈涛 胡建华 熊珑 等 1 84辐射骚扰测量中外置预放器的使用注意事项…………………………………………………………………姚棉竹 曾博 2 79天线电磁兼容技术探讨………………陈斌 夏微微 高节 2 83有线数字电视机顶盒HDMI防着火设计……………………………………………………………………宋文平 何鹏林 3 80汽车部件辐射发射测量不确定度评定的研究……………………………………………………………………………刘媛 3 85一种地面用频装备复杂电磁环境试验方法研究……………………………………………………丁永平 苏醒 党丽 4 92工业机器人安全之生命周期风险评估…………………邢琳 4 97影响电压暂降能力验证结果的原因分析……………………………………………………王帮玉 钱春泉 陈学锋 等 4 102 机载用电设备欠压浪涌防护方案设计及效能分析……………………………………………周成龙 郭艳辉 刘强 等 5 73采用质量控制图法对辐射发射测试系统期间核查…………………………………………………康小嫣 焦琳 华广胜 5 78低频磁场发射测试系统的期间核查方法………………………………………………………郑文生 刘晓迪 闵超 等 6 77移动电源行业现状分析………………………………………………………………………郑杰昌 耿振峰 谢志利 等 6 82产品介绍高功率激光装置电磁兼容设计……………………………………………………………………易涛 郑万国 江少恩 1 89熔断器电压降自动测试系统的研制…………………………………………………………………陈英霞 严薇 王燕雯 2 89 150 kHz~30 MHz容性电压探头设计………茅永胜 周香 3 91基于Arduino的剩余电压测试控制装置……………吴冰峰 4 105符合MIL-STD-188-125中PCI测试要求的HEMP滤波器研制………………………………………………Paul Currie 5 103无人机载空间电磁场测量系统…………………………………………………………………陆德坚 马天瑞 朱琨 等 6 97论文撷英2018 IEEE EMC ＆ SIPI 国际会议——获奖文章(二)…… 1 94 2018 IEEE EMC ＆ SIPI 国际会议——提名文章(一)…… 2 94 2018 IEEE EMC ＆ SIPI 国际会议——提名文章(二)…… 3 95 2018 IEEE EMC ＆ SIPI 国际会议——提名文章(三)…… 4 110 2019 APEMC 国际学术研讨会——最佳文章(一)……… 5 109 2019 APEMC 国际学术研讨会——最佳文章(二）……… 6 103实验室之窗专注电磁防护测评技术研究与电磁兼容试验——信息产业信息记录及防泄漏产品质量监督检验中心………………………………………………………………… 1 99整车混响室助力汽车整车EMC及复杂电磁环境测试——南京容测检测技术有限公司EMC实验室………… 2 99华南地区大型设备检测技术服务平台——承信科技电磁兼容与安全（环境）实验室………… 3 99 IC EMC测试认证技术助力国产芯片加速发展…………… 4 115广电计量电磁兼容检测中心………………………………… 5 112基于近场扫描的电磁干扰诊断技术——浙江大学电磁兼容实验室…………………………… 6 107。
RADECS Workshop 2018暨第二届电子器件辐射效应国际会议在京召开
Space International 国际太空·总第474期61孔令东 刘平 （中国航天电子技术研究院）2018年5月16-18日，“RADECS Workshop2018暨第二届电子器件辐射效应国际会议”在北京成功召开。
本次会议旨在构建高端学术交流合作平台，助推航天强国建设，引领元器件抗辐射专业创新发展。
经中华人民共和国外交部批准，在中国航天科技集团有限公司科技委的大力支持和指导下，会议由王海波副总经理发表主题演讲中国航天电子技术研究院主办，北京微电子技术研究所和哈尔滨工业大学承办。
元器件和系统辐射效应协会（RADECS）是国际辐射加固领域最重要的权威学术组织之一，本次RADECS Workshop 大会是第一次在中国举办，也是第一次在非欧洲国家举办。
RADECS 高度重视在中国举办的本次会议，派出了由6名专家组成的专业代表团出席会议。
中国航天科技集团有限公司副总经理王海波、科技委副主任江帆、国际业务部副部长郭建平，中国航天电子技术研究院副院长王燕林、科技委原主任谢天怀、科技委副主任赵元富，北京时代民芯科技有限公司副总经理王勇，哈尔滨工业大学副校长郭斌等领导出席会议。
中国科学院、中国电子科技集团有限公司、哈尔滨工业大学等60余家单位参会，共有来自15个国家的260余名专家、学者和代表应邀参加了本次会议。
开幕式上，中国航天科技集团有限公司副总经理王海波发表了题为《中国航天的成RADECS Workshop 2018 暨第二届电子器件辐射效应国际会议在京召开 RADECS Workshop 2018 and the 2nd International Conference on Radiation Effects of Electronic Devices Held in Beijing王燕林副院长致辞 大会主席赵元富主持会议就与发展》的主题演讲，重点介绍了中国航天在独立自主、自力更生发展历程中取得的伟大成就，展望了中国航天科技集团有限公司在航天强国中“开放包容、合作创新”的发展前景，并结合《筑梦航天》视频专题介绍了中国航天抗辐射加固元器件的技术发展和取得的丰硕成果。
2018第10届IEEE通信软件和网络国际会议(ICCSN2018)
ZHANG Guoliang, TANG Wenjun, ZENG Jing, et al. An overview on the cooperative SLAM problem of multi-ro-bot systems considering communication conditions[J].Acta automatica sinica, 2014, 40(10): 2073–2088.作者简介：周彦，男，1978年生，副教授，博士，主要研究方向为多传感器信息融合、图像处理与机器视觉。
发表学术论文40余篇，其中被SCI收录10余篇。
目前主持国家自然科学基金项目1项，参与国家自然科学基金项目4项；曾参与及主持“973”、国家自然科学基金等项目15项。
李雅芳，女，1993年生，硕士研究生。
主要研究方向为图像处理与机器视觉。
王冬丽，女，1980年生，副教授，博士，主要研究方向为模式识别与机器视觉。
发表学术论文30余篇。
目前主持国家自然科学基金项目1项。
曾参与国家自然科学基金、上海市自然科学基金等项目。
2018第10届IEEE通信软件和网络国际会议（ICCSN2018）2018 10th International Conference on CommunicationSoftware and Networks (ICCSN 2018)2018年第十届通信软件和网络国际会议将于2018年7月6—9日在中国成都召开。
会议旨在促进通信软件和网络等领域的学术交流与合作，热忱欢迎从事相关技术研究的专家、学者和专业技术人员踊跃投稿并参加大会。
IEEE，电子科技大学联合举办, 中电54所，通信网信息传输与分发技术重点实验室，是本次会议的协办方，广东工业大学为技术支持单位，《电子技术应用》是会议的赞助方。
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1. Journal of Communications (JCM)期刊为Scopus检索期刊, 目前该JCM期刊Scopus检索正常。
智能撤离指导系统开放系统架构（IEGSOS）说明书
Construct an Intelligent Evacuation Guidance System with Open System ArchitectureKun-Ming Yu1,*, Huan-Po Hsu2, Nien-En Chung1, Cheng-Chang Lien1, Shao-Tsai Cheng3, Ming-Yuan Lei4 andNancy Tsai41Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu, Taiwan2Ph.D. Program in Engineering Science, Chung Hua University, Hsinchu, Taiwan3Department of Construction Management, Chung Hua University, Hsinchu, Taiwan4Architecture and Building Research Institute, Ministry of the Interior, New Taipei City, Taiwan*Corresponding authorAbstract—Intelligent building and environment sensing technology are becoming more and more popular. Many office buildings use IoT to set up environment collection sensors to collect environmental information, however t he way of evacuation inside still using traditional evacuation guidance equipment. Therefore, this study proposes an intelligent evacuation guidance system with open system architecture (IEGSOS), integrating with environment monitoring system and intelligent guidance equipment. The IEGSOS is developed based on the service-oriented architecture (SOA) and the data exchange technology is utilized to provide an integrated programming interface. By adopting the multimedia technology and integrating with the existing communication and guidance devices in environments, the optimal evacuation path is provided to the asylum in case of environmental crisis as a reference for safety evacuation at critical times.Keywords—evacuation guidance system; service-oriented architecture; application programing interface; IoTI.I NTRODUCTIONWith the rise of the smart building, environment collection sensors have been wildly used and distributed in every space of buildings. For example, it can carry out indoor perception utilizing the IoT technology, collect environmental information, and adjust the central control air conditioning equipment to maintain the comfort of environment [2, 7, 8, 11]. However, when there is a fire in an intelligent environment, evacuees just only can accordance with traditional evacuation guidance equipment to escape although they are in the intelligent environment.When the fire occurs, if the evacuation route is blocked, the evacuees cannot obtain immediate and safety reference for escape guidance. Therefore, this study proposes an intelligent evacuation guidance system with open system architecture (IEGSOS) which possesses an application interface and integrates with multi-perception. The integration of the existed environment monitoring system with the intelligent refuge guidance system is provided through the application interface and the dynamic link library. Then, through open interface, multimedia devices with communication capabilities or guiding devices can receive the result of evacuation path, and display the evacuation information for guidance.This rest of the paper is organized as follows. Section 2 describes the theoretical concept of this paper. Section 3 introduces the architecture of the intelligent open-interface evacuation guidance system. And Section 4 put forward an implement case. The final section summaries the research and make a conclusion.II.R ELATED W ORKSA.Indoor EvacuationIndoor guidance equipment is a necessary equipment for many people or an open space to install. When the emergency occurs, the indoor guidance equipment is the only indicator referring the export for evacuees. Thus, the evacuation device must be regularly maintained and updated to ensure it can play a guiding role in the critical moment and let the evacuees can escape from the environmental crisis quickly.The guidance equipment often used in indoor is the escape indication device usually furnished in the skirting board or on the corner. The escape indication device makes use of the green arrow pointing in the direction of exports. With a standby power supply, when the environment is blackout, it can provide lighting and indicators continually as a reference for evacuees to escape. However, the evacuation routes in an environment change as places’ characteristics change, the fixed guide equipment is unable to provide other evacuation routes.Dynamic evacuation guidance equipment is a set of evacuation guidance equipment that can be cooperated with an intelligent evacuation guidance system for indoor guidance according to the evacuation route it calculated. If the environment’s evacuation route needs to be changed, it can make a dynamic change of guidance device’s direction through wired or wireless mode.B.Intelligent Evacuation Guidance SystemIntelligent evacuation guidance system is a set of environment evacuation guidance system applied in the indoor complex space. With intelligent environmental perception and evacuation route calculus and guidance functions, through the intelligent evacuation guidance system, a relative safe2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)evacuation route in environmental emergency is calculated to guide evacuees to escape [1].The intelligent evacuation guide system must have three layers of structure, which are intelligent sensing, computing and guiding [4].1) Sensing layer is an architectural layer that focuses on data collection. The format of sensing type has no strict requirements. It can be designed according to the environmental requirements like temperature, humidity, luminance, carbon monoxide or carbon dioxide, crowd recognition count or other risk factor data. It can also be selected according to the needs of evacuation route computation. In addition, the communication interface that receives environmental data from environmental monitoring system can also be referred to as one of the types of intelligent perception [9, 10]. 2) Computing layer is the information collection and calculation engine. It does environment calculus or path judgment on the basis of environmental data collected by intelligent sensing module. Through analysis on the results of intelligent computing, safety evacuation routes of the environment will be obtained and can be transmitted according to the form demanded. 3) Guiding layer transmits the evacuation route to the guidance equipment or guidance system, using wire or wireless communication protocol, to display, without a specific form, depending on the needs or forms of information transmission, so that evacuees can achieve safety guidance during the escape process.III. I NTELLIGENT O PEN -INTERFACE E VACUATIONG UIDANCE S YSTEM The environmental perception system is a sensing system installed by many intelligent buildings or open spaces to regulate environmental comfort. The environmental information can be collected and discriminate through sensors. However, when the environment is abnormal, the environmental sensing system will not carry out the initiative evacuation, so we must wait for the existing fire equipment to send the danger notice. The IEGSOS uses service-oriented architecture (SOA) [3] and the interface integration technology providing interface connections for integration with the existing environment perception system. By this way, the computing environment security path can be shared by the environmental information and evacuation guidance system, so that office buildings with environmental awareness system can also have the function of evacuation guidance.The IEGSOS needs to handle the integration interface and the main data types of the calculus. It is necessary to design an application interface that integrates with the environment monitoring system.Finally, complete content and organizational editing before formatting. Please take note of the following items when proofreading spelling and grammar:A. Application Interface DesignEnvironment perception system mainly collects different information according to different needs, but most environmental perceptions usually have the following information as environmental data, including: temperature, humidity, luminance, carbon monoxide, carbon dioxide or PM2.5. The fire alarm station uses temperature and smoke to API TheApplication Program InterfaceJson ObjectEnvironment CollectSystemEvacuation Guidance Data Object Analytic LyearFIGURE I. IEGSOS INTEGRATE WITH ENVIRONMENT MONITORINGSYSTEM THE INTERFACE STRUCTURE DIAGRAM.According to FIGURE I, IEGSOS use JSON to interchange data, by which the transmission can be resolved in a fast and light way, and the data format can also be more pluralistic. The data needed in the evacuation guidance engine include environmental perception data and map information, while map information is presented in the form of environmental nodes, as shown in FIGURE II .B. Evacuation Planning Computing EngineEnvironmental data is transmitted by JSON objects. Data is decompressed and stored in the local database through data object analysis layer, to resolve the problem of wasting too much time when calculating database. To integrate the algorithm and the evacuation guidance system, crowd scatter guidance algorithm (DBCS) is used to do modularized modification so that the algorithm can easily invoke resources when required to call.FIGURE II. THE MAP AND SET AREA NODEC. Evacuation Guidance Path FeedbackWhen the data through the evacuation guidance engine, suggestions for indoor evacuation path will be put forward. These guidance path will be send out in the form of JSON, and the guidance system can receive and analyze the data through the interface, then do indoor evacuation guidance. The outputin the form of JSON is shown in FIGURE III.FIGURE III. EVACUATION PATH IN JSON FORMATIV. T HE S YSTEM I MPLEMENTATION CASEIn this study, integration test for the IEGSOS integrating the environmental perception system and the audiovisual evacuation system is described as follows [5, 6].The environment perception system is a set of wide environmental information collection system adopting ZigBee transmission technology. The system collects temperature, humidity and illumination information of the environment. In order to know the sensor location in the environment, the system has an indoor environment map and the map information is constructed by the data interchange format JSON. The FIGURE IV is an integrated structure diagram of the environmental perception system with the open intelligent evacuation guidance system, and the FIGURE V is a diagramfor JSON information.FIGURE IV. ENVIRONMENT MONITORING SYSTEM AND IEGSOSSTRUCTUREFIGURE V. ENVIRONMENT DATA JSON PACKAGEIEGSOS receives callback data from the environment perception system through the JSON object, stores it to the database through the analytic layer, and extracts the database data by the evacuation guidance engine for algorithm calculation. Take advantage of the modular construction, the original two-dimensional time complexity algorithm is dismantled independently into multiple one-dimensional time complexity algorithms for simultaneous computing. Accordingly, even a multi-space building can be calculated in a short time, and the results are imported to the database for the storage of the evacuation path.This study uses the actual site simulation. 22 space nodes are set according to the demand as shown in FIGURE VI. During the implementation, the temperature of node 14 in the environment perception system is increased by 50 degrees, making the sensing temperature abnormal, to initialize the IEGSOS. The operation result is shown in FIGURE VII. The operation results are transmitted in the form of JSON through the result feedback module, waiting for other guide systems to collect. The output results are shown in FIGURE VIIIV. C ONCLUTIONThe IEGSOS proposed by this study is an integrated interface system based on the concept of diversification integration which can complete interface integration with the existing environment perception system, which possesses a high extensibility and provides guide command. By this way, it can integrate any existing intelligent devices meeting the needs by developing different integrated interfaces. It can integrate with existing environment system to reduce the cost of new system installation and provide the evacuation plan to the intelligent guidance equipment to guide evacuees to escape. Through simple translation, the guidance commands offered by the IEGSOS, through a simple translation, can be accepted by intelligent guidance devices, enabling the existing devices in the environment to become a part of the intelligent evacuationguidance system to make the intelligent environment safer.FIGURE VI. SET THE OUTPUT DIAGRAM OF THE ENVIRONMENTSPACE NUMBERFIGURE VII. OUTPUT DIAGRAM OF ABNORMAL OF NODE 14(REDARROW)FIGURE VIII. Evacuation path feedback in JSON encapsulationA CKNOWLEDGMENTThis paper was supported by Architecture and Building Research Institute, Ministry of the Interior (research No. 106301070000G0026).R EFERENCES[1] Chung, N.-E., Yu, K.-M., Hsu, H.-P., Cheng, S.-T., Lien, C.-C., Lei, M.-Y., & Tsai, N. (2017). An Effectiveness Study of an Intelligent Emergency Evacuation System Using Field Verification Techniques. Sixth International Conference on Future Generation Communication Technologies (FGCT 2017) (pp. 96-101). Dublin, Ireland: IEEE.[2] Cohen, B. (2012, 9 19). What Exactly Is A Smart City? Retrieved 3 12,2017, from https:///1680538/what-exactly-is-a-smart-city[3] Fredlund, L. Å., Earle, C. B., Herranz, Á., & Mariño, J. (2014).Property-Based Testing of JSON Based Web Services. 2014 IEEE International Conference on Web Services (pp. 704 - 707). Anchorage, AK, USA: IEEE.[4] Hsu, H.-P. (2015). Design and Implement an Intelligent EvacuationGuiding System with Modular methodology. Hsinchu, Taiwan: Chung Hua University.[5] Hsu, H.-P., Yu, K.-M., Chine, S.-T., Cheng, S.-T., Lei, M.-Y., & Tsai, N.(2014). Emergency Evacuation Base on Intelligent Digital Signage Systems. 2014 7th International Conference on Ubi-Media Computing and Workshops (pp. 243-247). Ulaanbaatar, Mongolia: IEEE.[6] Hsu, H.-P., Yu, K.-M., Lien, C.-C., Cheng, S.-T., Lee, C.-L., Lei, M.-Y.,& Tsai, N. (2016). An Intelligent Emergency Evacuation System Based on Multiple Guidance Technology. The 9th IEEE International Conference on Ubi-Media Computing (U-Media 2016) (pp. 397-402). Moscow, Russia: Science Index.[7] IEEE. (2015, 12 17). IEEE 802.15 WPAN™ Task Group 4 (TG4).Retrieved from IEEE 802.15: /15/pub/TG4.html [8] ITU. (2005). ITU Internet Reports 2005: The Internet of Things.Retrieved from ITU: https://www.itu.int/net/wsis/tunis/newsroom/stats/The-Internet-of-Things-2005.pdf[9] Wu, C.-C. (2013). Development of a Personalized Crowd GuidanceAlgorithm for Emergency Fire Evacuation with Crowd Streaming Capability. Hsinchu, Taiwan: Chung Hua University.[10] Yu, K.-M., Yu, C.-S., Lien, C.-C., Cheng, S.-T., Lei, M.-Y., Hsu, H.-P.,& Tsai, N. (2015). Intelligent evacuation system integrated with image recognition technology. 2015 8th International Conference on Ubi-Media Computing (UMEDIA) (pp. 23-28). Colombo, Sri Lanka: IEEE. [11] ZigBeeAlliance. (n.d.). Retrieved from ZigBee Alliance:/。
基于局部多片段的轻量级行为识别网络MLNet
DOI：10. 11772/j. issn. 1001-9081. 2020111737
基于局部多片段的轻量级行为识别网络 MLNet
徐传淇 ，姚 1，2* 宇 1，王浩然 1，2，胡智翔 1，2，徐传健 3
（1. 中国科学院 成都计算机应用研究所，成都 610041； 2. 中国科学院大学，北京 100049； 3. 常州大学 材料科学与工程学院，江苏 常州 213164）
（Temporal Convolution Module），在时序维度进行融合。最后， 将融合输出的全局特征通过 softmax 层来对视频中的动作进 行判别。
1 相关工作
视频行为识别的关键在于捕获有效的时空特征。目前有 基于手工设计特征的方法和基于深度学习提取特征的方法。 手工设计特征的方法是将 2D 手工提取特征的方法扩展到了 3D。相关方法有：STIP（Space-Time Interest Points）算法［14］从 视频中检测时关键点来提取特征；为了能解决小尺度、没有视 点 变 化 的 运 动 ，研 究 者 提 出 了 3D-SIFT（3-Dimension Scale Invariant Feature Transform）算法［15］，可以补偿摄像机运动引 起 的 运 动 估 计 误 差 ；尺 度 不 变 特 征 变 换（Scale Invariant Feature Transform，SIFT）算法［16］通过建立带时空差分的高斯 金字塔来检测局部极值，从而定位动作信息；文献［17］通过有 向 三 维 时 空 梯 度 直 方 图 来 定 义 视 频 时 序 局 部 描 述 符 ；文 献 ［18］基于密集轨迹和运动边界描述和轨迹来捕捉视频时空特 征，密集轨迹表示可以保证前景运动和周围环境有良好的覆 盖语境。
2018年国际会议报告情况
日本，仙台
Switching multi-function via external stimuli tuned spin transition
邀请报告
刘涛
27.
2018 International Conference on Novel Functional Materials(ICNFM2018)
2018.8.17-20
加拿大大瀑布城
Some key scientific problems in direct coal conversion
Keynote
胡浩权
10.
2ndInternational Symposium on Molecular Design of Opto-Electronic Materials
22-27 July 2018
新加坡
2D indium-based heterostructures for robust solar water splitting
IL
侯军刚
14.
International Symposium on Plasmonics and Nano-photonics(iSPN18)
July 30‒August 4, 2018
Sendai, Japan
A distinctive Fe/S complex bearing a phenylene S-to-S bridge with high activity and selectivity toward electrocatalytic reduction of CO2to CO
2018.7.30-8.4
日本仙台
Transition Metal Complexes Showing Strong Absorption of Visible Light and Long-lived Triplet State
2018年度国家技术发明奖
2018年度国家技术发明奖安徽省提名项目公示（一）项目名称城镇污水处理厂智能监控和优化运行关键技术（二）提名意见该项目针对我国污水处理厂水质与水量波动性大的特征，围绕污水处理厂的智能监控和优化运行问题，经过十几年的研究与实践，研发了污水处理厂的模拟、监测和优化运行的关键技术，发展了污水处理系统的动态模拟技术，建立了污水处理系统的数字化模型和仿真平台，构建了污水处理厂运行工况在线监测与诊断技术系统，实现了污水处理工艺的运行优化，形成了适合于不同污水水质和工艺条件，且经济、高效的污水处理厂智能监控和优化运行关键技术。
项目集成了多项技术理论和技术创新，获得了授权发明专利21项、计算机软件著作权4项，发表60多篇SCI论文，该项目成果成功应用于多个污水处理厂，为污水厂的节能降耗和升级改造提供了强有力的技术支撑。
项目所研发的经济、高效污水处理厂智能监控和优化运行技术，已推广到安徽、陕西、江苏、广东等地的30多个城镇污水处理厂，在降低污水处理厂运行费用，增加COD和氨氮减排量方面成效显著，取得了很好的环境、经济和社会效益。
该成果带动了污水处理行业监控和运行技术的整体发展，为污水处理行业的可持续发展起到了很好的示范作用。
项目相关成果获2015年安徽省科学技术一等奖。
项目材料填写规范，内容真实，经公示无异议。
对照国家科学技术进步奖授奖条件，提名该项目为国家科技奖技术发明奖二等奖。
（三）项目简介本项目属于水污染防治工程的科学技术领域。
城镇污水处理厂属于多输入、多输出、长时滞的动态开放系统，涉及复杂的生化反应、物化反应及物质/能量的转化和传递，因而普遍存在能耗高、出水水质波动大、难以被监控和运行等突出问题。
因此，本项目通过对污水处理厂长期的深入研究，发现了污水生物处理过程中微生物呼吸及其产物形成的特性和规律，发明了污水处理厂在线监测和动态模拟新方法，发展了污水处理系统运行状态判定系列新技术，进而研发了集智能监控与优化控制为一体的污水厂运行控制平台，突破了污水厂常规中控系统只面向设备控制的局限性，显著提升了污水处理厂运行效率和稳定性。
2018年度科技论文(着作)奖励
2704.5
作物所
1.803
2704.5
作物所 经啤所
1.803 1.718
2704.5 2577
生技所
1.632
2448
2018年度科技论文（著作）奖励
序 号
论文题目
第一作者
期刊名称
发表期数及页码
24
轮叶党参EST-SSR标记的开发及在党参属中 的应用
刘新星
《中草药》
2018年第49卷第13期，3110-3115
2018年度科技论文（著作）奖励
序 号
论文题目
第一作者
期刊名称
发表期数及页码
第一单 位
SCI论文（共 9篇）
Consensus genetic linkage map construction
1 and QTL mapping for plant height-related
traits in linseed flax (Linum usitatissimum L.)
3 盐胁迫对菘蓝幼苗生长和抗性生理的影响 米永伟 《草业学报》
2018年第27卷第6期，43-51
耕作方式与长期定位施肥对雨养农田冬小 4 麦产量的调控效应
种植密度对光敏型高丹草营养成分及动态 5 变化的影响
6
旱地玉米不同覆盖栽培模式的土壤水热特 征及产量品质效应
7
生物降解膜对甘肃河西棉花的生态生物学 效应
Maize – fababean rotation under double ridge
3 and furrows with plastic mulching alleviates
soil water depletion.
盲人导航系统设计说明书
Guidance System Based on Image ProcessingDahai Yu and Manman ShenSchool of electrical information of Changchun Guanghua University, Changchun, China, 130031 Abstract—To solve the problem of blind travel, a guidesystem based on image processing is designed. The visualinformation collected by a CCD camera. The voice information isused to communicate with the user. The overall design of thissystem is given. Recognize the zebra line by the bipolar systemvalue. Recognize the blind road using saturation histogram andGaussian function.Keywords—blind identification; zebra crossing recognition;image processing; guideI I NTRODUCTIONAccording to the World Health Organization (WHO)statistics in 2010, the total number of people in the world with vision impairment is estimated to be 285 million. 39 million arewhole blind. While China has the most people, the number of blind people is also the most. There is about 5 million blindpeople in China. Due to the physiological defects and the increasingly complex living environment, it brings manyinconveniences to the blind people's life. In view of theinconvenience of blind people, guide dog and guide stick gradually become tools to help blind people travel. However, the guide dog is not easy to train and the cost is high, so the detection range of the blind guide rod is limited.H Wang has designed an interactive guide robot. The robot is composed of haptic device and human-computer interaction system. Analyze the 2D information through the haptic system and transmits the information to the user. But the robot can only detect the surrounding obstacles, not the main effective identification the traffic signs. Zhang Ying designed a guide robot based on embedded technology to identify obstacles and traffic signs. But the robot will not receive the voice message to the blind, which caused a lot of inconvenience to the blind. Han Xuefeng designed an interactive guide robot, through the sensor detection of the external environment, and transfer in the form of voice for the blind. But the robot of traffic sign recognition effect is poor, which can’t meet the actual needs of the blind. Zhang Zhimei et al designed a crawler type guide robot. Use ultrasonic sensor to track the trajectory of black ground preset to avoid obstacles. But it can’t work in no-black environment.In view of the deficiency of the blind guiding technology atpresent, the design of intelligent guide system has greatpractical significance.II S TRUCTURE OF GUIDANCE SYSTEM According to the restriction of the activity of the blind, the function of the guide robot is confirmed, and the overall scheme of the guide system is worked out. As shown in Figure I.FIGURE I.O VERALL SCHEME DESIGNA camera is used to collect the image information of the environment. The data are transferred to DSP. GPS module is used to position the user. Voice module is used to receive or play voices for users. The data are also transferred to DSP. Do some calculate in DSP including traffic signal recognition, Blind identification, zebra crossing recognition and so on.III Z EBRA LINE RECOGNITIONThe zebra belt consists of a group of parallel strips with alternate black and white intervals. The difference of color between black and white stripes is very obvious. Gray contrast is very strong. The rule of black and white alternating is strong. So we can use the bipolar coefficient of the image to characterize and quantify the intensity of the intensity contrast of the zebra line region. Analyze and judge the region with strong gray contrast in the road image by the bipolar system value. If the test area is in the zebra line region, the value of the bipolar system is very high. Otherwise, if the region to be inspected i s not a zebra region, its gray value is basically the same, and the value of the bipolar system is small.First we can use a threshold to segment the image.(a) O RIGIN IMAGE(b) T HRESHOLD SEGMENTATIONFIGURE II.I MAGE SEGMENTATIONThen suppose (μ1,σ1)is the average value of density distribution function of black pixels. (μ2,σ2)is the average2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)value of density di stribution function of whith pixels. n1,n2 presents the pixel number of black and white.α=n1n1+n2(1)σ02=ασ12+(1−α)σ22+a(1−α)(μ1−μ2)2(2) The bipolar coefficient γisγ=1σ02[α(1−α)(μ1−μ2)2](3)γ is a value between 0 and 1. When γis 0 , the image is not zebra area. And when γis 1, the image must be zebra area.Then search the edge of the zebra. When there are parallel lines in the image. It could be recognized as zebra lines.(a) T HRESHOLD SEGMENTATION(b) R EGIONS USING BIPOLARITYFIGURE III. R ESULT OF BIPOLAR COEFFICIENT At the end, use the edge of the zebra line. Then we can get the zebra lines info rmation.FIGURE IV. R ESULT OF ZEBRA CROSSING RECOGNITIONIV B LIND ROAD RECOGNITIONThe color of b lind road is usually very bright. So the colors can be used to detect the characteristics of the blind road. This paper gets the blind area using image segmentation. Extract the edge of blind road. First, convert the image from RGB to HSI color space. HSI has three color components. Use the saturation histogram to segment image.(a)O RIGINAL IMAGE(b)H ISTOGRAM OF SATURATION(c) THE SEGMENT IMAGEFIGURE V. R ESULT OF IMAGE SEGMENTATION However, sometimes the color histogram will appear "jagged" shape. It is difficult to divide the image through the peaks and troughs in the histogram. So in order to determine the segmentation point, first use the Gauss smoothing filter to smooth the original color histogram. Suppose S L(x)is the histogram of saturation. The processed color histogram function is:F(x,σ)=S L(x)∗G(x,σ)(4) Here, G(x,σ)is the Gauss function. * presents convolution.This operation not only reduces noise, but also eliminates some tiny saw teeth.FIGURE VI. R ESULT OF BLIND ROAD RECOGNITIONV GPS RECOGNITIONThe remote positioning function can send the blind people to the blind's relatives and friends in real time, strengthen the connection between the blind and relatives and friends, and ensure the safety of the blind. Using SIM808 module and SIM telephone card to realize GPS remote positioning. Through the GPRS flow data of SIM808 GPS upload module programming through the SIM card to the China Mobile networking platform, open platform (OneNET) by computer through the GPS data from the OneNET platform and processed, displayed on the map to achieve GPS remote location positioning module.VI C ONCLUSIONSAiming at the needs of the blind, a guide system is designed. According to the confirmation of the blind activities restrict the function of the system and established the general scheme of the robot; then the realization of recognition, such as the zebra and blind important traffic signs. However, the system needs to be further improved, then to realize traffic lights recognition, intelligent guide system development.R EFERENCES[1]Meng Xiangwei, Yan Xijun, Ouyang, stars, et al. Design of guide barbased on ultrasonic sensors [J]. electronic design engineering, 2012, 20(17): 11-14.[2]Zhang Zhimei, C heng Liying, Zhao Yiheng, et al. Study of guide rob otbased on fuzzy PID control alg orithm [J]. Journal of Shenyang Normal University (NATURAL SCIENCE EDITION), 2015, 33 (1): 81-85. [3]Tang Zhichao, Su Lin, He Chao, et al. Research on traffic sign visualrecognition technology of guide rob ot [J]. compu ter technology and development, 2014 (9): 23-27.[4]Yang Wanhai. Multisensor data fusion and its application [M].Northwest University of Electronic Science and Technology Press, 2004. [5]Xu Yan, Wei Zhen Yu. An improved traffic sign image recognitionalgorithm [J]. laser and Optoelectronics Progress, 2017 (2): 118-125. [6]Khatib O. Real-Time Obstacle Avoidance for Manipulators and MobileRobots[C]// IEEE International C onference on Rob otics and Automation.Proceedings. IEEE, 1986:500-505.[7]Huang Yanbiao, Lu o Guangyue, ho ho. Application of B P neuralnetwork in multisensor data fusion of patrol rob ot [J]. Journal of sensing technology, 2016, 29 (12): 1936-1940.[8]Otsu N. A Threshold Selection Method from Gray-Level Histograms [J].IEEE Transactions on Systems Man & Cybernetics, 2007, 9(1):62-66.。
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94PAPER EXTRACTSSAFETY & EMC No.2 2019Development and Evaluation of Waveforms for EMI Radiated Susceptibility Testing of Avionic Systems摘要：目前军用航空电子系统的电磁干扰敏感度测试的推荐波形不符合现代电信标准，没有带宽和峰值平均值功率比（PAPR）等特性。
文中提出了一种参数简化过程，用于开发代替LTE 信号的候选波形，并通过航空电子设备的电磁干扰测量结果来评估这些波形。
分析测量数据，以确定带宽和PAPR 是否对实际LTE 信号的电磁干扰测量结果具有明显影响。
该方法也可用于评估测试波形对其他通信标准的适用性。
关键词：电磁干扰；LTE；辐射敏感度；便携式电子 设备本文评估作为LTE 信号的简化版本的候选波形代替LTE 信号进行电磁兼容实验的可行性。
通过测量受体系统上的电磁干扰来评估候选波形模拟真实波形的电磁干扰的有效性。
根据波形类型、带宽和PAPR，测量、分析候选波形到飞机对讲系统的后门耦合。
每次简化都可能改变电磁干扰引起的影响，使用的参数缩减过程如图1所示。
每一步骤都移除了LTE 信号的某些特性，使得每个波形的复杂度低于前一波形。
作者分析的波形包括长期演进技术（LTE）、单载波频分多址（SC-FDMA）、正交相移键控（QPSK）、噪声（Noise）四种。
选择了五个频率带宽来评估测试波形，以匹配用于LTE 的六个信道带宽中的五个：1.4 MHz，3 MHz，5 MHz，10 MHz 和20 MHz。
五个通道带宽和四种信号调制产生20种不同的测试波形。
PAPR 是相对峰值功率的量度：PAPR[dB]=P peak [dB]-p t [dB] （1）其中P peak 是峰值功率，P t 是平均功率。
图2给出了互补累积分布函数测量候选波形的PAPR。
可以看出，带宽为20 MHz 的LTE 波形和SC-FDMA 波形有0.0001%的概率超过值为7.7 dB 的PAPR，因此频谱整形滤波器和探测参考信号（SRS）静默期不影响波形的PAPR。
虽然QPSK 的理论PAPR 应为0 dB，但是根升余弦滤波器的引入使其幅度明显变化，导致PAPR 为5.2 dB。
带宽为20 MHz 的滤波噪声波形有0.0001%的概率超过值为9.2 dB 的PAPR。
滤波噪声波形的PAPR 高于LTE 波形的PAPR。
辐射敏感度测试装置由矢量信号发生器、电波暗室、天线、待测设备和示波器组成，如图3所示。
所有测试波形使用+16 dBm 的平均发射功率。
LTE 的PAPR 为 7.7 dB，LTE 波形的峰值功率为+23.7 dBm。
PM1000II 对讲系统被选为辐射敏感度测试的待测设备。
PM1000II 内部滤波器的频率响应是通过改变传输到PM1000II 辅助输入端的信号频率来测量的，同时测量音频输出。
内部滤波器是一个通带滤波器，截止频率为180 Hz 和90 kHz。
待测设备位于电波暗室内贴片天线附近。
测试结果表明，20 MHz 带宽的LTE 引起的干扰幅度小于1.4 MHz 带宽。
SRS 静默期的下降沿和上升沿引2018 IEEE EMC ＆ SIPI 国际会议——提名文章（一）2018 IEEE International Symposium on EMC ＆ SIPI—Nominated Paper Part 1图1参数缩减过程图2 带宽为20 MHz 的测试波形的PAPR比较图3辐射敏感性测试装置95论文撷英2019年第2期 安全与电磁兼容起正负电压尖峰，较小信道带宽的波形会比宽信道带宽的波形引起更大强度的干扰。
为了比较候选测试波形对待测设备辐射敏感度的影响，使用50 Ω的阻抗来计算干扰样本功率的平均值和峰值。
在评估载频为700 MHz 的信号引起干扰的平均功率时，发现滤波噪声引起干扰的平均功率高于其他三种波形，其他三种波形引起干扰的平均功率基本相同。
测试波形的PAPR 对待测设备电磁干扰敏感度具有较大影响。
图4给出了载频为700 MHz 信号的干扰峰值功率。
滤波噪声引起的干扰峰值功率高于LTE 波形。
LTE 引起的干扰峰值功率高于SC-FDMA 和滤波后的QPSK 信号。
对于具有较宽带宽的波形，LTE 和SC-FDMA 波形引起的干扰峰值功率之间的差异变大。
鉴于LTE 静默周期的上升沿和下降沿对待测设备的敏感度具有重要影响，并且随着带宽的增加这些边缘效应更为明显，如果研究峰值干扰功率，则SRS 静默期是一个重要特征。
替代性，候选波形和LTE 波形应具有相同的敏感度。
待测设备的两个敏感带宽为20 MHz，载频为 700 MHz 和810 MHz。
LTE 在810 MHz 处引起的峰值干扰功率低于在700 MHz 处引起的峰值干扰功率。
因此，在810 MHz 时，LTE 波形中的上升沿和下降沿会比在700 MHz 时受到的影响更小，另外两种载频情况下，耦合机制可能不同。
在载频为700 MHz 时，滤波噪声波形和AM 波形引起的峰值干扰功率在LTE 引起的峰值干扰功率的两个标准偏差范围内，此时仅有滤波噪声波形和AM 波形可以代替具有20 MHz 带宽的LTE 波形。
在载频为 810 MHz 时，滤波噪声比LTE 引起更多的干扰，其他候选波形的峰值干扰功率都在LTE 引起的峰值干扰功率的三个标准偏差范围内。
因为滤波噪声有LTE 信号在载频为810 MHz 处也有的敏感度，所以认为滤波噪声也可以代表20 MHz 带宽的LTE 波形。
相比之下，AM 波形在载频为950 MHz 处也出现了不同程度的敏感度，不能代替类似于LTE 的复杂信号。
与具有相同发射功率的LTE 波形相比，滤波噪声在该特定的待测设备中会引起更多的干扰。
如果在安全裕度内，作者认为在敏感度测试中使用滤波噪声是 可以的。
Electromagnetic Compatibility Analysis Using Embedded Domain Decomposition Method摘要：介绍了一种基于有限元的嵌入式区域分解方法。
通过这种方法，作者将计算区域分解为一个背景子区域和几个嵌入式的子区域。
子区域之间的信息交流是在它们的共享区域进行的，共享区域有四个要素点：场域连续性、材料差异性、理想导体和理想端口。
该方法允许完全不规范的子区域，从而为电磁兼容和信号完整性应用的建模和设计提供了很大灵活性。
关键词：麦克斯韦方程组；区域分解方法；有限元法；嵌入式网格在图1中，作者考虑一个平滑有界的区域Ω，物质属性为ε1（x ）、μ1（x ），辐射边界满足一阶吸收边界条件。
区域Ω2位于区域Ω内部，区域Ω2的物质属性为ε2（x ）、μ2（x ）。
区域Ω2中包括理想导体和端口，端口激励可以是入射电磁波、端口上的外加电流或它们的组合。
为简单而不失一般性，将原始域Ω分解为两个子域，即背景子域Ω1和嵌入子域Ω2。
注意Ω1的形状与Ω相同，除了∂Ω2内的区域，它现在不包含Ω2的几何信息，并且设置为填充与Ω\Ω2中相同的材料。
图5给出了带宽为20 MHz 信号的波形引起的峰值干扰。
将四种不同测试波形引起的干扰与由正弦调幅波（AM）形引起的干扰进行了比较。
为了使候选波形具有图4 不同波形在载波700 MHz的干扰峰值功率图5 带宽20 MHz的不同波形干扰峰值功率96PAPER EXTRACTSSAFETY & EMC No.2 2019随后，作者对子域进行网格化，如图2所示。
子域的初始分解边界值问题，不考虑它们之间的耦合，分别用有限元法对子区域进行求解，背景子域和嵌入式子域将会在他们的共享区域迭代地交换信息，直到所有的结果收敛到所需的精度为止，该方法允许完全不共型子域。
因此，每个子域都可以根据其局部几何特征选择合适的离散化子域。
此外，这种嵌入式区域分解方法可以在问题域中添加逻辑替换对象。
然后,作者使用嵌入式区域分解方法分析了一个复杂程度较高的实际问题。
如图3所示，在人脑附近使用的是手机和平板电脑。
作者计算了从平板电脑到手机的电磁干扰，以及从设备到人脑的比吸收率。
为了验证嵌入式区域分解方法的准确性，本文以传统的单域有限元求解结果为参考。
在应用嵌入式区域分解方法时，将问题域离散为一个背景子域Ω1和四个嵌入式子域Ω2、Ω3、Ω4、Ω5，如图4所示。
在嵌入式子域中，印制电路板和天线在手机和平板电脑内部。
表面电流被施加在天线的端口上，起到激励作用。
首先，在平板电脑的天线端口上引入表面电流，为了评估平板电脑对手机的电磁干扰，作者计算了手机天线端口处的接收功率。
这样，电磁干扰就可以重新表示为手机端口接收到的功率与平板电脑端口发射功率之间的功率比。
嵌入式区域分解方法和有限元计算的功率比如图5所示,可以看出，嵌入式区域分解方法结果与常规有限元分析结果吻合度较好。
如果需要进一步预测手机在不同位置时对人脑或平板电脑的影响，可以简单地移动/旋转嵌入的子域，重新进行仿真，在此过程中，子域网格不需要改变。
在传统的有限元方法中，简单的几何变化会导致整个系统矩阵的重新划分和计算。
嵌入式区域分解方法的优点是在建模和网格离散化方面具有灵活性，这将加快重复模拟的速度。
最后,对手机中的天线和平板电脑中的天线同时进行激励，并计算了设备辐射引起的人脑比吸收率分布。
嵌入式区域分解方法在0.9 GHz 和2.4 GHz 处产生的比吸收率分布与传统有限元法相似。
首先,在移动设备的设计中，设备的比吸收率值不能超过技术指标。
同时,由于手机/平板电脑的传输功率要求很小，不能任意降低比吸收率值。
其次,为了在比吸收率值和发射功率之间取得良好的平衡，一个器件的设计过程中可能需要重复建模，需要大量的仿真工作,此时,嵌入式区域分解方法将有助于提高效率。
编辑：王淑华 E-mail:wangsh@图2嵌入式区域分解方案图3靠近人头的手持手机和平板电脑图4问题的嵌入式区域分解方法设置图5平板电脑对手机的电磁干扰图1一阶吸收边界条件的边值问题。