题目：Solving Constrained Total-Variation Image Restoration and
Reconstruction Problems via Alternating Direction Methods
报告人：Prof. Michael Ng
Department of Mathematics, Hong Kong Baptist University
时间：8月27日，14:30-15:30
地点：南京大学蒙民伟楼404

摘要：In this paper, we study alternating direction methods for solving
constrained total-variation image restoration and reconstruction problems.
Alternating direction methods can be implementable variants of the classical
augmented Lagrangian method for optimization problems with separable
structures and linear constraints. The proposed framework allows us to solve
problems of image restoration, impulse noise removal, inpainting and image
cartoon+texture decomposition. As the constrained model is employed, we
cartoon+only need to input the noise level and the estimation of the
regularization parameter is not required in these imaging problems.
Experimental results for such imaging problems are presented to illustrate
the effectiveness of the proposed method. We show that the alternating
direction method is very efficient for solving image restoration and
reconstruction problems.

简介：Michael Ng is a Professor in the Department of Mathematics at the Hong
Kong Baptist University. He obtained his B.Sc. degree in 1990 and M.Phil.
degree in 1992 at the University of Hong Kong, and Ph.D. degree in 1995 at
Chinese University of Hong Kong. Michael is the Programme Director of the
MSc Programme on Operational Research and Business Statistics and Director
of the Centre for Mathematical Imaging and Vision (CMIV), Executive Director
of the Institute for Computational Mathematics (ICM) at Hong Kong Baptist
University. He is also the Engineering Panel Member of the Hong Kong
Research Grants Council starting from 2009. Michael has published and edited
5 books, published more than 200 journal papers. He currently serves on the
editorial boards of several international journals.

摘要：Sparse Learning has attracted much attention in recent years. There are two classes of methods: convex relaxation such as L1 regularization and greedy algorithms. Although the former has received more attention in the machine learning community, my opinion is that the latter approach is more flexible and powerful. This talk will discuss variations of greedy algorithms in the context of sparse recovery.

简介: Tong Zhang received a B.A. in mathematics and computer science from Cornell University in 1994 and a Ph.D. in Computer Science from Stanford University in 1998. After graduation, he worked at IBM T.J. Watson Research Center in Yorktown Heights, New York, and Yahoo Research in New York city. He is currently a statistics professor at Rutgers University. His research interests include machine learning, algorithms for statistical computation, their mathematical analysis and applications.

作者：黄合来

【核心提示】本文提出科研思维和论文写作的五大原则，包括评判性（critical）、一致性（consistent）、简洁性（concise）、清晰性（clear）和完整性（complete），以期为年轻学者和在读博士生的科研思维训练和规范提供参考。

【前言】

科学研究可以笼统的用胡适先生提出的“大胆假设，小心求证”进行概括，是一个开拓求新与严谨求实的有机结合。求新是一个基于对客观现象或问题的深入思考和探究，挣破旧有理论束缚，大胆创新，对未解决的问题提出新的假设或解决的可能。而求实是一个尊重证据，对新的方法或理论严谨求证的过程。科学的进步离不开两者的相辅相成，“求新”和“求实”两大准则应该贯穿整个科研实践过程。

然而，求新和求实两大准则往往由于其抽象性很难得到严格界定。实际科研工作过程往往要求遵循一些实用性更强的原则。良好的科研思维对于一个科研工作者极为重要，而科研思维的形成需要一个基于一系列具体原则的较为长期的训练。本文提出一个科研思维与论文写作的“5C”原则，力求具体，力求实用，以期为年轻学者和在读博士生的科研思维训练和规范提供参考。

【原则一】 Critical （评判性）

培养评判性思维能力（critical thinking）是西方高等教育体系的一个关键目标，也是我国目前争论最为广泛的教育和科研改革的重要内容。美国哲学学会对评判性思维的定义为， “Critical thinking is defined as purposeful, self-regulatory judgment, an interactive, reflective reasoning process of making a judgment about what to believe or do”（评判性思维是有目的的，自我调节的判断过程，是个体对相信什么或做什么作出判断的互动的反映性的推理过程）。笔者认为，针对科学技术发展的评判性思维是科研能力的核心价值，评判性思维的培训是年轻学者培养如博士生教育的关键任务。

科研方法有三种：新方法解决老问题，老方法解决新问题，新方法解决新问题。毫无疑问，科研需要“新”，即创新性。那么创新性应该来源于哪里呢？创新不是凭空臆想（主观主义），也不是灵光一现（机会主义），创新来源于对已有知识产生的背景、过程、证据、方法、理论、以及评价知识的标准等正确与否作出评判性的思考和推理。此外，由于资源有限性，单纯的求新不应是唯一的科研导向，有价值的科学意义上的创新研究工作应该拥有充分而合理的评判性的证据支撑。简言之，科研不应为“创新”而创新，而应为“实践”而创新。而这两方面反映到具体的科研能力上，其核心就是一种评判性的思维和实践。

具体来讲，对于运用“新方法解决老问题”，需要评判为什么老问题需要新方法？老方法为什么不能有效解决老问题？而更重要的是为什么该新方法可能具有解决该老问题的潜力？对与运用“老方法解决新问题”，需要评判为什么新问题需要解决？为什么老方法可以解决新问题？最后是对于运用“新方法解决新问题”，同样要评判为什么新问题值得研究？为什么老方法不能解决该新问题？当然，为什么提出的新方法有潜力解决该新问题？对这些问题的回答应该是科研设计和论文写作的必要切入点。

由于科研思维过程和论文写作思路具有内在的一致性，可以更为具体的把评判性思维反映到以基本论文结构为脉络的各个部分当中。

1）研究背景   研究领域大的背景的重要性，比如对社会、经济、环境、健康等方面的效应。

2）研究问题   对确立的研究问题的评判性的检测，即该研究问题对探究大的研究背景领域的积极意义和潜在的具体贡献。

3）文献综述   “文献综述”不是“综述文献”，而是“评判文献”。在科学论文中，对已有文献的方法和结论的回顾应该具有充分的评判性，在科研设计和论文撰写的时候，必须充分评判已有文献对该研究问题的解决程度、价值和意义，更重要的是基于此评判，为本研究的实施、方法的选取等进行合理辩护。

4）研究假定和研究目的   提出研究假定和研究目的的时候必须进行合理性、适度性和可行性的综合评判和辩护。

5）研究方法   提出的研究方法，不论是新方法或老方法，都必须充分评判该方法达到研究目的和解决研究问题的特质和潜力。

6）研究结果和结论   对取得的研究结果需要进行深入讨论和观察，以现存文献为基础，对研究结果的一致性和异常性等进行充分的评判，并获得具有充分证据支撑的结论。

【原则二】 Consistent （一致性）

牛顿说“如果我看得比别人更远些，那是因为我站在巨人的肩膀上”。这句名言可以从一致性的方面进行理解：伟大科研成果的取得离不开广大的科研同行多年的尝试和努力，换言之，创新具有广义一致性。实际上，广义的评判性思维可以看作一致性和批判性的有机结合，也就是继承和批判。但是，一致性由于其对严谨科研思维的培训极为重要而具有特殊地位。一致性是一个科研人员必须具备的基本素质。

具体来讲，一致性主要反映到科研设计和论文写作两个方面。

1）科研设计    前面提到的三种科研设计方法前两种都涉及到一个“老”：老问题，老方法。而在第三类“新方法解决新问题”，其中新方法和新问题的“新”也都不可避免属于相对意义的“新”。新的问题和方法往往来源于老问题或老方法的演变和发展，如同大自然的新陈更替，对新问题的解决和新方法的探究离不开对老问题和老方法的理解和评判。原理的一致性是科研设计的重要切入点，包括研究策略、实验设计、分析方法、变量定义等等，创新的获得来源于继承和批判，但都必须具有充分的与前人研究的广义一致性。

2）论文写作    科研论文的撰写是发布科研成果的一个最重要的手段。前面着重讲到评判性在论文各组成部分的体现，这里要更为具体的强调一致性的在论文写作中重要地位。西方科研体系对科学论文有极为严格的规范，其中一致性是一个最重要的方面。从大的方面讲，科研容许学派，但是对于同一科研人员来说，对研究问题的基本立场和观点，必须具备先后不同论文的一致性和同一论文的前后一致性。从具体论文元素来讲，一致性反映在文体、格式、专业词汇使用、缩略词以及文献列表等。不要忽视任何文章中出现的不一致的成份。很多专家在审稿的时候第一就是看文章格式和文献，比如是否第一次定义缩略词，之后一致使用？是否具有一致字体、空行、子标题？文献列表格式是否一致？所有这些都反映到审稿专家对该论文作者的科研能力的第一印象。

评判性思维的贫乏和对一致性原则的忽视是当今我国科学研究走向国际化的一个重要的瓶颈所在，青年科学研究者应该积极锻炼自己的评判性思维，同时时刻用最严格的一致性要求规范自己的科研实践和论文写作，这是取得重大科研成果的前提。

【原则三】 Concise （简洁性）

科研是创造科学知识的过程。简洁性对于知识的传播极为重要。更为重要的是，简洁的思维有利于取得好的科研成果。对比西方语言文化，我国文字和文学的简洁性更优。在这方面，笔者更加偏爱中文期刊论文对简洁性的要求，当然，需要注意的是，在具备简洁性的同时更要强调对所陈述的科研成果的论证的充分性。

形象言之，简洁性原则的最高境界是“多一分则多，少一分则少”。具体针对科研实践，简洁性原则反映的是一种内在的科研思维简洁性和外在的论文板书简洁性。内在地，在确立了研究目标之后，所有的研究策略、方法、步骤都应该无一例外的为检验研究假定或达到研究目的而服务，任何其它的多余步骤都应该排除。只有目的明确，才不会被其它非当前研究内容所干扰。当然，在研究过程中对一些异常现象应该积极思考和观察，从而引导出可能的新的研究目标。

外在地，对论文写作来讲，简洁性原则要求所有论文元素均服务于论文结论的获得。科研论文不是用来展示知道的老知识，而是用来发布获得的新知识。在这方面很多学者容易犯错误，往往希望在论文中展示自己的知识量，而忽视了这些内容对论证研究结论的作用。举例来讲，很多论文文献综述部分的撰写往往变成了一个简单陈列，一个文献一小段，缺乏自己的观点和评价。而实际上，前面讲到“评判文献”，同时，文献的写作也应该“创新性”的高度概括，只有那些对本研究相关的前系研究才应该进行合理评判，其它不相关甚至包括不直接相关的内容和评判都应该排除在论文之外。另外，科研论文是写给同行看的，不是科普文献，因此应该排除一些学科常识性的文字和评论。同时，从功利角度上来讲，文章越长，可以被批判的内容就越多。

最后要强调的是，中华文字的简洁性是我们的一个重要历史遗产，我们的学界不应该在科研国际化的过程中盲目追求和简单仿效英文式的长篇大论。

【原则四】 Clear （清晰性）

科研论文不是小说、不是散文、不是迷语，要求具有足够的清晰性。清晰的论文能让读者更容易理解和接受所发布的研究成果。不要让别人有机会猜测或寻找研究的任何元素，包括研究背景、目标、方法、结果、结论等。把各个元素都放在它们最应该存在的地方。

运用规范的子标题和清晰的逻辑语言标识论文各个部件；段落之间保持良好清晰的连接层次性，主次分明；每一个段落表达一个观点或一个小主题，中心句居首或居尾；运用清晰简单的文字组成句子表达各种观点，在使用英文丛句的时候注意强调部分居于前，等等。这样写出来的论文最后看上去就会像一小截一小截短小精悍却又联系紧密的小树枝组成，而这些小树干又在更高层面逻辑严密地组成大的树干。

【原则五】 Complete （完整性）

完整性原则是论文写作的一个基本原则，无论文章长短，都必须具备完整性，“麻雀虽小，五脏俱全”。任何学术论文都应该独立成篇，决不容许“且听下回分解”。那么到底哪些元素是一篇完整论文所应该具备的呢？跟简洁性原则共轭，完整性原则要求论文包含充分论证研究目标所需要的必要证据。换言之，任何一篇论文都必须完成对提前设定的研究目标的实现。在这个逻辑之下，合理确立论文的研究目标和范围就变得十分重要。在所有论文都充分完成了所设定的或低或高、或新或旧的研究目标的前提下，不同档次期刊的审稿标准就可以简单地测定不同论文的目标及实现该目标所获得的结果的创新性、广度和深度。

具体运用完整性的时候，有三个容易引起歧义的情况。

1）假定最初研究目标为A, 但是在实现A的过程中，发现A不可行，却意外的发现了B。在这种情况，论文撰写应该围绕B来进行，对于A目标的辩护和相关文献最多只能作为研究背景来陈述，而对B的实现应该遵循完整性原则。

2）论文的局限性（Limitation）和未来研究建议（Future research）。任何研究都是基于某些假定，不可避免的在实验条件、分析工具、现存理论等限制下具有一定的局限性，所以对于局限性的认识和对未来研究的建议成为了很多论文很有价值的部分。但要注意的是，这两个部分和完整性原则不冲突。局限性是设定的研究目标和范围对于探索研究问题的局限性，而非完成研究目标的研究过程的局限性。虽然论文完成了研究目标，局限性表明该目标的完成对认识研究问题的不充分性，以此需要在未来研究中设立其它补充性的研究目标以充分认识研究问题。

3）联合论文形式。这种论文形式表现在针对一个研究的几个创新部分分别撰写2篇或以上的论文发表在同一个期刊上，并使用相同的大标题和不同的子标题。这类情况往往出现在“新方法解决新问题”的情况下，对于研究方法和研究成果都有显著的创新，所以在2篇文章里分别强调方法和结果。这类文章虽然比较少见，但是同样也必须遵循完整性原则，其中任何一篇论文都应该独立成篇，应该充分完成对研究目标的实现。所以该情况下，研究目标就必须合理的设定，比如对于方法创新论文应该以创新方法为目标，而对问题创新论文应该以探索新问题结果为目标。

【结语】

以上的5C法则基本概括了科研思维和论文写作的重要原则，对于年轻学者尤其是博士生来讲，可以用这个5个原则来不断衡量自己从课题选定、实验设计、结果分析、论文撰写等所有科研活动，假以时日，并可以渐渐形成好的科研习惯，从而获得比较成熟的科研思维，创造出突出的科研成果。

最后在科研精神方面，再打包附送两个C，加量不加价。 第一个是Candid, 那就是科研诚信，紧紧联系着一个学者的学术声誉，不抄袭、不造假、尊重事实、尊重证据，是一个合格科研人员的基本素养。第二个就是Crazy,，伟大的科研不是喝白开水，征服科学，需要激情，需要热爱，需要全身心投入。

本文引用地址： http://www.sciencenet.cn/m/user_content.aspx?id=335259

报告一：

题目：Using Computers to Find Out the Truth

报告人：Professor Boi Faltings

ECCAI Fellow, Director of AI Lab

Faculty of Information and Communication Sciences

Swiss Federal Institute of Technology, Lausanne, Switzerland

时间：5月18日 13:30-14:30

地点：蒙民伟楼404会议室

摘要：One of the major problems for decision makers today is that they are far removed from the details that are often crucial for the success of their plans. On the other hand, the people who know these details are often not likely to report them truthfully, as it is not in their best interest to do so. The anonymity afforded by computing systems can help in this situation. I present several approaches to eliciting truthful information, in particular scoring rules, peer prediction methods and opinion polls.

简介：Boi Faltings is a full professor of computer science and director of the AI lab. His main research contributions are in the area of qualitative and case-based reasoning, constraint programming, distributed problem-solving, and recommender systems. He has co-founded 6 companies in e-commerce and computer security and acted as advisor to several other companies world-wide. Prof. Faltings has published over 300 refereed papers and graduated over 25 Ph.D. students, several of which have won national and international awards. Boi Faltings is a fellow of the European Coordinating Committee for Artificial Intelligence. He has served as head of the computer science department from 1996-1998 and as head of the Institute of Core Computing Sciences from 2005-2008. He serves or served as associate editor of several journals, in particular the AI Journal (2000-2008), JAIR (2004-2007), Annals of AI and Mathematics (2008-today), and as member of editorial boards (AI Communications, AI Magazine, Constraints, and others). He also regularly serves in conference committees (IJCAI, AAAI, ECAI, and others) and have been program (co-)chair of several workshops and conferences. He holds a Diploma from ETH Zurich and a Ph.D. from the University of Illinois at Urbana-Champaign.

报告二：

题目：User Experience and Technology Acceptance Issues in Recommender Systems

报告人：Dr. Pearl PU

Director of Human Computer Interaction Group

Faculty of Information and Communication Sciences

Swiss Federal Institute of Technology, Lausanne, Switzerland

时间：5月18日 14:40-15:40

地点：蒙民伟楼404会议室

摘要：As online stores offer practically an infinite shelf space, recommender systems are playing an increasingly important role in helping users *search* and *discover* items that they may want to buy. In this talk, I first start with a brief survey of the rating based social recommender systems and their applications in online industry. I will then spend some time discussing some of the unsolved issues, especially concerning user adoption problems such as the cold start phenomena, users’ acceptance of recommendations, and personalization. The main part of the talk focuses on the technology behind critiquing based recommender (CBR) systems. Even though they may not address all of the user issues, CBR systems offer some effective solutions. They do not require users to leave traces of their interests via behavioral patterns. Instead, they encourage users to express them via the interface. Moreover, since users are completely involved in the preference elicitation process in such systems, users feel more in control of the recommendation process, and as a consequence they are more convinced of the products recommended to them. I will finish the talk by explaining the baggage carousel phenomenon and show you how critiquing based recommender systems enable users find personalized items without expending extra interaction effort. Through the analysis of some of our empirical studies, I hope to reveal to you some insights on the effective design of recommender systems for scalable user adoption.

简介：Dr. Pearl Pu is the director of the Human Computer Interaction Group in the School of Computer and Communication Sciences at the Swiss Federal Institute of Technology in Lausanne. Her research interests include decision support, electronic commerce, online consumer decision behavior, product recommender systems, travel planning tools, trust-inspiring interfaces for recommender agent, music recommenders, scalable user experience, and social navigation. She has been recently elected as the general chair for the ACM international conference on Recommender Systems (Recsys 2008) and ACM international conference on Intelligent User Interfaces (IUI 2011), and program co-chair of the ACM international conference in Electronic Commerce (EC 2009) and Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2008).She is an associate editor of IEEE Transactions on Multimedia. She obtained her Master and Ph.D. degrees from the University of Pennsylvania in artificial intelligence and computer graphics. She was a visiting scholar at Stanford University in 2001, both in the database and HCI groups.

题目：Transcriptome analysis for identifying stress-inducible microRNAs

报告人：Weixiong Zhang

Department of Computer Science and Engineering

Department of Genetics

Washington University in St. Louis

http://www.cse.wustl.edu/~zhang

时间：5月10日15:30-16:30

地点：蒙民伟楼404室

摘要：MicroRNAs (miRNAs) are ~21nt non-coding RNAs that regulate gene expression at the post-transcriptional level. Plant miRNAs regulate many genes that are involved in development and stress response. Although a large number of miRNAs have been identified and studied, most of them remain to be functionally annotated. Experimental functional analysis is laborious and costly. It is, therefore, desirable to develop computational approaches to support and complement experimental approaches for miRNA functional analysis. In this talk I will describe a novel, machine learning/datamining approach for identifying microRNA genes in plants that are responsive to environmental stresses. Our overall approach consists of a new computational method for identifying cis-regulatory DNA sequences (motifs) from the promoters of mRNA genes, a method for predicting core promoters of miRNA genes, a new transcriptome-based gene expression modeling method, and experimental verification of mature miRNAs and miRNA precursors. We applied our approach to study cold-responsive microRNA genes in Arabidospsis thaliana. We predicted nineteen individual microRNAs in twelve miRNA families to be up-regulated in Arabidopsis seedlings under cold stress. Our experimental validation showed that among the twelve microRNA families, eight were differentially induced by cold and three were constantly expressed under cold stimulus. A promoter analysis also showed that these cold-inducible microRNA genes contain many known stress-related cis-regulatory elements in their promoters. I will also discuss putative transcriptional down-regulation pathways triggered by the induction of these microRNA genes. Particularly, our result indicated that auxin signaling pathways in Arabidopsis seedlings may be mediated by many microRNAs.

简介：Weixiong Zhang is a professor of Computer Science and of Genetics at Washington University in St. Louis, Missouri, USA. He received his B.S. and M.S. in computer engineering from Tsinghua University, Beijing, China, and his M.S. and Ph.D. in computer science from University of California at Los Angeles (UCLA). Professor Zhang’s research interests include computational systems biology and genomics, artificial intelligence, data mining, and combinatorial optimization. He has published more than 100 papers in these areas and is the author of a research monograph, State-Space Search: Algorithms, Complexity, Extensions and Applications, published by Springer in 1999. He is currently associate editors of PLoS Computational Biology, J. Alzheimer’s Disease, Artificial Intelligence, and AI Communications – The European Journal on Artificial Intelligence.

IEEE CS Nanjing Chapter 5月4日16：00~17：00在南京大学蒙民伟楼404举行学术报告会，信息如下。欢迎参加！

Bayesian Ying-Yang System, Best Harmony Learning, and Five Action Circling

LEI XU

Proposed in 1995 and systematically developed over fifteen years, Bayesian Ying-Yang (BYY)  learning is a statistical approach for an intelligent system via two complementary Bayesian representations of a joint distribution on the external observation X and its inner representation R, called BYY system. A Ying-Yang best harmony principle is proposed for learning all the unknowns in the system, in help of an implementation featured by a five action circling.  BYY learning provides not only a general framework that accommodates typical learning approaches from a unified perspective but also a new road that leads to improved model selection criteria, automatic model selection during learning, and coordinated implementation of Ying based model selection and Yang based learning regularization. This talk introduces BYY learning principles, implementing techniques, and typical learning algorithms, in a comparison with other algorithms, particularly with the EM algorithm as a benchmark. These algorithms are summarized in a unified Ying-Yang alternation procedure with major parts in a same expression while differences simply characterized by few options.

Lei Xu, chair professor of Chinese Univ Hong Kong, Chang Jiang Chair Professor of Peking Univ, IEEE Fellow (2001-) and Fellow of International Association for Pattern Recognition (2002-), and Academician of European Academy of Sciences (2002-).  He completed his Ph.D thesis at Tsinghua Univ by the end of 1986, then joined Dept. Math, Peking Univ in 1987 first as a postdoc and then exceptionally promoted to associate professor in 1988 and to a full professor in 1992. During 1989-93 he worked at several universities in Finland, Canada and USA, including Harvard and MIT. He joined CUHK in 1993 as senior lecturer, as  professor in 1996 and chair professor in 2002. He has published a number of well-cited papers on neural networks, statistical learning, and pattern recognition, e.g., his papers got over 3200 citations according to SCI and over 5500 citations according to Google Scholar (GS), with the first 10 papers scored over 2000 (SCI) and 3600 (GS). One single paper has scored 750 (SCI) and 1211 (GS). He served as associate editor for several journals, past governor of international neural network society (INNS), a past president of APNNA, and a member of Fellow committee of IEEE CI Society. Also, he has received several national and international academic awards  (e.g., 1993 National Nature Science Award, 1995 INNS Leadership Award and 2006 APNNA Outstanding Achievement Award).

电气电子工程师协会（IEEE）中文网站http://cn.ieee.org今天正式发布！

1984年IEEE在中国成立了首个分会-北京分会-并拥有100名会员。今天，IEEE在中国已经有超过5000名会员，7个分会，3个支分会，1个联合会和1个代表处，在中国的影响力不断扩大，并成为中国工程师和全球科技团体沟通和交流的纽带和桥梁。

IEEE中文网站的成立标志着IEEE为中国会员的服务提升至一个新的台阶。在这里，我们将为您提供IEEE的最新咨询，会议信息，中国境内活动，会员专享服务等等。我们会继续努力，也坚信我们的会员，为了人类美好明天而不断创新。

感谢加入我们一起庆祝IEEE中文网站的成立！欲知更多网站内容，敬请访问http://cn.ieee.org。

此致

IEEE中国代表处

2010年3月22日

Dear IEEE Members:

IEEE Chinese Website http://cn.ieee.org Announcement today!

IEEE formed its first Chinese Section-Beijing Section-in 1984 with barely 100 members. Today, IEEE has more than 5,000 members, seven sections, three sub-sections, one council and one representative office. IEEE has expanded its efforts to establish links between China’s engineers and the global technical community.

The Establishment of IEEE Chinese website indicates IEEE membership services for the Chinese to upgrade to a new level. Here we are providing IEEE news, conference information, activities in China and China’s exclusive membership services. As we move forward, we are confident that our members will continue to innovate in the service of mankind.

Thank you for joining with us to celebrate Chinese website announcement! For more information, please visit http://cn.ieee.org .

Sincerely,

IEEE China office

March 22, 2010

看来还是有人不知道在哪里下载IEEE的802族协议文本。IEEE802协议族，由于广泛流行，长了IEEE标准化协会的很大面子。所以IEEE802族协议，是可以在其官方网站上免费下载的。网址是

http://standards.ieee.org/getieee802/

或许朋友们可以在若干个协议文本里搜索到我的名字哦 Wenhao Zhu，呵呵。比如在 802.15.4c协议里。

由于相关许可协议限制，我不能把该协议文本贴在我的博客上，我也建议您不要做。以下是许可协议摘录

COPYRIGHT

This IEEE Standards Publication ("Document") is approved by the IEEE Standards Association ("IEEE-SA") Standards Board and is published in accordance with established IEEE-SA Standards Board bylaws and operations procedures.

The Institute of Electrical and Electronics Engineers, Inc., ("IEEE") owns the copyright to this Document in all forms of media. Copyright in the text retrieved, displayed or output from this Document is owned by IEEE and is protected by the copyright laws of the United States and by international treaties. The IEEE reserves all its rights not expressly granted herein.

The IEEE is providing the Document to you at no charge. However, the Document is not to be considered "Public Domain", as the IEEE is, and at all times shall remain, the sole copyright holder in the Document.

TERMS OF USE

You may retrieve, download and print one (1) copy of this Document for your personal use. You may retain one (1) additional copy of this Document as your personal archive copy.

Except as allowed by the copyright laws of the United States of America or applicable international treaties, or as explicitly allowed in these Terms of Use, you may not further copy, prepare, and/or distribute copies of this Document, nor significant portions of the document, in any form, without prior written permission from the IEEE.

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不仅IEEE的这类标准可以下载，ITU的几乎所有标准都可以很容易的从官网上下载到相关文件。

最后建议一下，搜索这些东西，尽量用英语关键词，尽量用Google.com

你有没有注意过平时使用的饮料瓶上都有一个这样的标志, 它表示什么?

所有人都知道那个"箭头围成的三角形"表示它可以被回收再利用. 但圈里那个数字和下面的字母是什么呢?

这个顺时针旋转的箭头形成的三角形和它里面的数字一起, 叫做塑胶分类标志 (Resin identification code).

很多人误以为有这个标志就意味着这个塑料制品是可以回收的, 而这个数字表示这个材料被回收的难度或者频率. 其实这个数字只是一个编号, 是美国塑胶工业协会制订的分类编码方式, 不同的编号表示不同种类的塑料材料. 而且虽然绝大多数塑料都可以回收, 但需要根据它们是不同的聚合物种类来分类. 而且由于挑选, 分类, 清洁和再加工等工序的成本, 目前经济上只能应付回收聚对苯二甲酸乙二酯(PET)与高密度聚乙烯(HDPE). 看这个 "PET" 是不是很眼熟? 上面那个标志就是 "PET" 塑料的标志. 我们平时用的大多数矿泉水, 碳酸饮料的瓶子就是用它做的.

不同种类的塑料制品的物理化学性质是有区别的. 例如除了PP塑料之外的大部分塑料都不耐热, 而不耐热的塑料制品遇热就容易释放出有毒的, 致癌的物质.

下面的塑料性质介绍来自网络. 部分内容我在 Wikipedia 上找到了相关资料, 但我没有查证以下所有描述, 不保证它们完全准确. 如果有任何错误请留言指出.

1. PET 聚对苯二甲酸乙二醇脂

常见矿泉水瓶, 碳酸饮料瓶等. 耐热至70℃, 易变形, 有对人体有害的物质融出. PET塑料品用了10个月后, 可能释放出致癌物DEHP. 不能放在汽车内晒太阳; 不要装酒, 油等物质.

2. HDPE 高密度聚乙烯

常见白色药瓶, 清洁用品, 沐浴产品的塑料瓶. 不要再用来做为水杯或者用来做储物容器装其他物品. 不要循环使用.

3. PVC 聚氯乙烯

常见雨衣, 建材, 塑料膜, 塑料盒等. 可塑性优良, 价钱便宜, 故使用很普遍, 只能耐热81℃. 高温时容易释放有毒物质, 很少被用于食品包装. 不要循环使用. 若装饮品不要购买.

4. PE 聚乙烯

常见保鲜膜, 塑料膜等都是用PE材料制作. 根据高中化学知识, PE本身是没有毒的. 但塑料制品在制作时会添加小分子的助剂, 它们通常是有毒的. 在高温下有毒的助剂容易迁移到塑料制品的表面. 如果用它来装高温的食物, 有毒物质随食物进入人体后, 可能引起乳腺癌, 新生儿先天缺陷等疾病. 所以别把保鲜膜放进微波炉.

5. PP 聚丙烯

常见豆浆瓶, 优酪乳瓶, 果汁饮料瓶, 微波炉餐盒. 熔点高达167℃, 是唯一可以放进微波炉的塑料盒, 可在小心清洁后重复使用. 需要注意, 有些微波炉餐盒, 盒体以5号PP塑料制造, 但盒盖却以1号PE塑料制造. 由于PE不能抵受高温, 故不能与盒体一并放进微波炉.

6. PS 聚苯乙烯

常见碗装泡面盒, 快餐盒. 不能放进微波炉中, 以免因温度过高而释出化学物. 装酸(如柳橙汁), 碱性物质后, 会分解出致癌物质. 别用微波炉煮碗装方便面, 或者干脆和我一样戒掉方便面.

7. OTHER 其它类 (包括ABS树脂、聚甲基丙烯酸甲酯、聚碳酸酯、聚乳酸、尼龙与玻璃纤维强化塑胶)

常见水壶, 太空杯, 奶瓶, CD 光盘, 桶装水瓶都是用这一类里的 PC 塑料制作, 容易释放出双酚A. 关于双酚A对人类的影响, 说法不一. 但加拿大政府已宣布双酚A是一种危险的化学品, 并正式将双酚A列入有毒化学品名单, 禁止在制造婴儿奶瓶的过程中添加双酚A.[1] 使用时不要加热, 不要在阳光下直晒.