科技论文摘要四大要素的内容

1．目的：研究、研制、实验等课题所涉及的范围和所要解决的问题。2．方法：所采用原理、理论、思想、技术、条件、材料、工艺、结构等,如何创建的新理论、新技术、新方法、新材料、新工艺、新结构等。3．结果：研究的结果、所得数据、被确定的关系、得到的效果和性能等。4．结论：对结果通过分析、比较、升华所得到的具有普遍意义的规律和适用范围。这四大要素是简明扼要地、全面准确地表述论文关键内容的必要条件,缺一不可。     

计算机病毒研究与控讨

本文重点阐述计算机病毒的产生、特征.探讨有关计算机病毒的定义、起源、历史、特征、传播途径、分类、最新动态、错误认识、防毒原则、解决病毒的办法和措施.     

计算机病毒研究与探讨

本文重点阐述计算机病毒的产生、特征。探讨有关计算机病毒的定义、起源、历史、特征、传播途径、分类、最新动态、错误认识、防毒原则、解决病毒的办法和措施。     

《信息安全与技术》杂志文稿要求

正1.文稿应具备学术性、专业性、创新性、科学性,务求主题突出、论据充分、文字精炼、数据可靠,有较高的学术水平、专业水平和实用价值。2.文稿的篇幅(含摘要、图、表、参号文献等)不超过7000字。3.文稿结构一般为题名、作者姓名、单位(邮编)、摘要、关键词、中图分类号、引言、正文、参考文献以及上述各项的英文译文。     

培训基地

"培训基地"栏目的目的很简单,以传播IT培训、考试为宗旨,从资讯、内容、考点、机构、认证、技能、窍门七大方面,让爱好电脑、奋勇上进、勤奋好学、锻炼本领的你不断感受最新、最酷、最全的知识冲击!请记住:无论你身在何处、何等学历、有何需求,只要是读者朋友们关心的、需要的培训考试,就是"培训基地"乐于奉献的(电邮请寄:peixun@cpcfan.com)!     

面向农业的新一代物联网技术与系统

1背景随着互联网、移动通讯、物联网、云计算等数字化技术的发展和应用,城市运行的各方面与数字化已经深度融合,并走过了将近20年的过程。城市数字化已经覆盖了政府、企业、个人主体在交通、环保、水务、种植、养殖、楼宇、家居、消费、停车、房产、教育、医疗、制造、税务等等场景的所有行为过程。物联网系统为产业繁荣发展、生活健康便捷、治理精准科学提供了不可或缺的保障。     

征稿简则

一、征稿范围:《小型微型计算机系统》杂志刊登文章的内容涵盖计算技术的各个领域(计算数学除外).包括计算机科学理论、体系结构、计算机软件、数据库、网络与通讯、人工智能、信息安全、多媒体、计算机图形与图像、算法理论研究等各方面的学术论文.二、来稿要求     

便携导航就剩这些了

在各大IT网站、汽车媒体、GPS专业媒体上,现在能曝光的便携导航牌子不超过30个,以下就是我们搜集到的:Mio、新科、城际通、任我游、神行者、爱国者、向导神、奥可视、艾维特、万利达、VDO、黑剑、诺基亚、长虹领航者、E路航、麦哲     

以信息化为纽带构建供应链一体化业务模式

宝供信息化的成功是建立在八年来先后为宝洁、飞利浦家电、照明和小家电、厦华电子、红牛维他命饮料、美晨、TCL、联合利华、卡夫食品、中石油、养生堂、ICI等各行业客户提供供应链一体化信息服务和解决方案的基础上,在这里通过实际的案例谈谈宝供如何以信息化为纽带构建企业供应链一体化业务模式。     

创业公司C品官职位说明书

创业公司启航,三五十来个人、七八条枪,其中＂C＂字开头的官儿还真少不了CEO、CTO、COO、CFO、CMO、CIO、CCO、CLO、Chairman/Chairwoman……不过,和大公司不一样,创业公司里的＂C＂品官不是权力、待遇、级别的标志,     

泛系思维与应用：科学技术,方法论,创新与智能信息处理（Ⅱ）（上）

本文续前论述乏系思维的框架和方法论、创新运筹与智能信息处理问题,简化强化地介绍了几十种泛系理法及其应用,具体内容包括：泛系思维简式、泛系原则、泛系螺旋、显生原则、系统原则、广义系统、局整关系、分析与综合、整体性、结构与功能、遗憾原则、竞分三故、等价原则、竞标律、层标模型、简化５０计、转化原则、泛系数学建模总体转化模式、泛对称普适原则、广义量化、泛积原理、模糊控制、故障诊断的专家系统、数学建模三范畴     

车联网隐私保护技术研究

随着汽车智能化、网联化程度的不断加深,车辆、用户及第三方机构之间的数据共享日益成为刚需,由车辆、用户、路边单元等通信实体之间构建的网络车联网应运而生,而车联网的高移动性和网络拓扑多变性使其更容易遭受攻击,进而导致严重的车联网用户隐私泄露问题。如何平衡数据共享和隐私保护之间的关系成为车联网产业发展所面临的一个关键挑战。近年来,学术界针对车联网隐私保护问题进行了深入的研究,并提出了一系列解决方案,然而,目前缺少对这些方案从隐私属性方面进行分析。为此,本文首先从车联网的系统架构、通信场景及标准进行阐述。然后对车联网隐私保护的需求、攻击模型及隐私度量方法进行分析与总结。在此基础上从车联网身份隐私、匿名认证位置隐私和车联网位置服务隐私三个方面出发,介绍了匿名认证、假名变更、同态加密、不经意传输等技术对保护车联网用户隐私起到的重要作用,并讨论了方案的基本原理及代表性实现方法,将方案的隐私性从不可链接性、假名性、匿名性、不可检测性、不可观察性几个方面进行了分析与总结。最后探讨了车联网隐私保护技术当前面临的挑战及进一步研究方向,并提出了去中心化的车辆身份隐私技术以保护车辆身份隐私、自适应假名变更技术以支持匿名认证、满足个性化隐私需求的位置服务隐私保护技术,以期望进一步推动车联网隐私保护技术研究的发展与应用。     

基于H.263解压算法和UDP协议的多方视频会议系统

简要概括了视频会议系统的设计原理,重点讲述了视频会议系统的实现过程,从视音频俘获、视音频数据压缩,数据传送、数据接收、数据解压,到音频数据播放、视频数据显示的整个过程.特别是对实现过程中的模拟会议室的创建过程、命令解析、视音频同步、音频数据的混音处理、中间代理服务器转发等做了详细的讲解.并对视频会议系统的发展和应用前景进行了认真的分析.     

Sixty years of cybernetics

Fundamental aspects of cybernetics, such as goals, problems, methods, tools, brief history, and correlation with other sciences, are considered. Cybernetics in its classical interpretation is the science of information management, communication, and processing. As cybernetics developed, this definition was formalized as the science of methods and processes of information acquisition, storage, processing, analysis, and evaluation, which allows it to apply to decision making in complex control systems. These systems include all engineering, biological, administrative, social, ecological, and economical systems. The main thesis that determined the goals, problems, subject matter, and development of cybernetics as a whole up to the present is the similarity in management and communication processes in machines, living organisms, and both animal and human societies. First of all, these are processes of transfer, storage, and processing of information, i.e., various signals, messages, and data. Any signal and any information may be considered independently from its particular content and destination as a certain choice between two or more values having the known probabilities (selective concept of information). It allows us to treat all processes on the basis of a unified measure and statistical apparatus. The idea of the general theory of control and communication, that is, cybernetics, is based on this hypothesis.     

Mapping complexity of spatial distribution of faults using fractal and multifractal models: vectoring towards exploration targets

In this paper, fractal and multifractal analyses are demonstrated as effective tools for mapping complexity in the spatial distribution of faults. Faults within the eastern part of Gejiu mining area, Yunnan province, west southern China were chosen to demonstrate mapping of the complexity of their spatial distributions using fractal and multifractal models. The results show that (1) the fractal dimensions of the spatial distributions of all faults, NW-trending faults, and NE-trending faults are 1.68, 1.49, and 1.42, respectively, indicating differences in spatial distributions of different sets of faults; (2) the fractal dimensions of the spatial distributions of faults in the four Sn fields in the Gejiu mining district, namely Malage, Gaosong, Laochang, and Kafang (arranged in the order of increasing proportions of surface-projected areas of Sn orebodies) are 1.38, 1.57, 1.65, and 1.41, respectively; and (3) complexity of the spatial distributions of faults, represented by fractal dimension, correlates well with surface-projected areas of Sn orebodies, and lengths of faults satisfy the multifractal statistical and singularity index α, which can be used to quantify the complexity of the spatial distributions of faults.     

云模式事件混沌关联特征提取的物联网大数据聚类算法

目前的聚类方法单纯从某个角度研究数据聚类问题,对基于云模式的混沌的物联网大数据聚类的考虑不足,聚类质量不高。为实现敏捷、智能、平稳的物联网大数据聚类,基于开展物联网事件的云模式通用描述模型、物联网事件混沌关联特征的云模式通用解析模型、基于云模式的物联网事件混沌关联特征提取算法、基于云模式混沌关联特征的物联网大数据关联挖掘研究,改进分解奇异值算法、网格耦合聚类算法、K-means算法、决策树学习法、分析主成分法、分层合并法等算法和分布概率函数,设计了一种基于事件混沌关联特征、敏捷、智能、平稳的物联网大数据聚类算法。最后,开展实验验证,并与传统算法进行性能对比分析。实验结果表明,相比传统算法,该算法聚类时间短、误差小,且敏捷性、智能性、动态演化性和平稳性高。因此,该算法实现了基于云模式的具有混沌关联特征的物联网事件大数据的有效聚类,具有较高的应用价值。     

Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers

In this paper, we present a new method for fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. The proposed method considers the centroid points and the standard deviations of generalized trapezoidal fuzzy numbers for ranking generalized trapezoidal fuzzy numbers. We also use an example to compare the ranking results of the proposed method with the existing centroid-index ranking methods. The proposed ranking method can overcome the drawbacks of the existing centroid-index ranking methods. Based on the proposed ranking method, we also present an algorithm to deal with fuzzy risk analysis problems. The proposed fuzzy risk analysis algorithm can overcome the drawbacks of the one we presented in [7]. Shi-Jay Chen was born in 1972, in Taipei, Taiwan, Republic of China. He received the B.S. degree in information management from the Kaohsiung Polytechnic Institute, Kaohsiung, Taiwan, and the M.S. degree in information management from the Chaoyang University of Technology, Taichung, Taiwan, in 1997 and 1999, respectively. He received the Ph.D. degree at the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, in October 2004. His research interests include fuzzy systems, multicriteria fuzzy decisionmaking, and artificial intelligence. Shyi-Ming Chen was born on January 16, 1960, in Taipei, Taiwan, Republic of China. He received the Ph.D. degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in June 1991. From August 1987 to July 1989 and from August 1990 to July 1991, he was with the Department of Electronic Engineering, Fu-Jen University, Taipei, Taiwan. From August 1991 to July 1996, he was an Associate Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1996 to July 1998, he was a Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1998 to July 2001, he was a Professor in the Department of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. Since August 2001, he has been a Professor in the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. He was a Visiting Scholar in the Department of Electrical Engineering and Computer Science, University of California, Berkeley, in 1999. He was a Visiting Scholar in the Institute of Information Science, Academia Sinica, Republic of China, in 2003. He has published more than 250 papers in referred journals, conference proceedings and book chapters. His research interests include fuzzy systems, information retrieval, knowledge-based systems, artificial intelligence, neural networks, data mining, and genetic algorithms. Dr. Chen has received several honors and awards, including the 1994 Outstanding Paper Award o f the Journal of Information and Education, the 1995 Outstanding Paper Award of the Computer Society of the Republic of China, the 1995 and 1996 Acer Dragon Thesis Awards for Outstanding M.S. Thesis Supervision, the 1995 Xerox Foundation Award for Outstanding M.S. Thesis Supervision, the 1996 Chinese Institute of Electrical Engineering Award for Outstanding M.S. Thesis Supervision, the 1997 National Science Council Award, Republic of China, for Outstanding Undergraduate Student's Project Supervision, the 1997 Outstanding Youth Electrical Engineer Award of the Chinese Institute of Electrical Engineering, Republic of China, the Best Paper Award of the 1999 National Computer Symposium, Republic of China, the 1999 Outstanding Paper Award of the Computer Society of the Republic of China, the 2001 Institute of Information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the 2001 Outstanding Talented Person Award, Republic of China, for the contributions in Information Technology, the 2002 Institute of information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the Outstanding Electrical Engineering Professor Award granted by the Chinese Institute of Electrical Engineering (CIEE), Republic of China, the 2002 Chinese Fuzzy Systems Association Best Thesis Award for Outstanding M.S. Thesis Supervision, the 2003 Outstanding Paper Award of the Technological and Vocational Education Society, Republic of China, the 2003 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision, the 2005 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 Taiwan Fuzzy Systems Association Award for Outstanding Ph.D. Dissertation Supervision, and the 2006 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision. Dr. Chen is currently the President of the Taiwanese Association for Artificial Intelligence (TAAI). He is a Senior Member of the IEEE, a member of the ACM, the International Fuzzy Systems Association (IFSA), and the Phi Tau Phi Scholastic Honor Society. He was an administrative committee member of the Chinese Fuzzy Systems Association (CFSA) from 1998 to 2004. He is an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics - Part C, an Associate Editor of the IEEE Computational Intelligence Magazine, an Associate Editor of the Journal of Intelligent & Fuzzy Systems, an Editorial Board Member of the International Journal of Applied Intelligence, an Editor of the New Mathematics and Natural Computation Journal, an Associate Editor of the International Journal of Fuzzy Systems, an Editorial Board Member of the International Journal of Information and Communication Technology, an Editorial Board Member of the WSEAS Transactions on Systems, an Editor of the Journal of Advanced Computational Intelligence and Intelligent Informatics, an Associate Editor of the WSEAS Transactions on Computers, an Editorial Board Member of the International Journal of Computational Intelligence and Applications, an Editorial Board Member of the Advances in Fuzzy Sets and Systems Journal, an Editor of the International Journal of Soft Computing, an Editor of the Asian Journal of Information Technology, an Editorial Board Member of the International Journal of Intelligence Systems Technologies and Applications, an Editor of the Asian Journal of Information Management, an Associate Editor of the International Journal of Innovative Computing, Information and Control, and an Editorial Board Member of the International Journal of Computer Applications in Technology. He was an Editor of the Journal of the Chinese Grey System Association from 1998 to 2003. He is listed in International Who's Who of Professionals, Marquis Who's Who in the World, and Marquis Who's Who in Science and Engineering.     

Content-based image retrieval at the end of the early years

Presents a review of 200 references in content-based image retrieval. The paper starts with discussing the working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap. Subsequent sections discuss computational steps for image retrieval systems. Step one of the review is image processing for retrieval sorted by color, texture, and local geometry. Features for retrieval are discussed next, sorted by: accumulative and global features, salient points, object and shape features, signs, and structural combinations thereof. Similarity of pictures and objects in pictures is reviewed for each of the feature types, in close connection to the types and means of feedback the user of the systems is capable of giving by interaction. We briefly discuss aspects of system engineering: databases, system architecture, and evaluation. In the concluding section, we present our view on: the driving force of the field, the heritage from computer vision, the influence on computer vision, the role of similarity and of interaction, the need for databases, the problem of evaluation, and the role of the semantic gap     

基于大数据的烟草企业信息化战略布局研究

为了提升烟草企业自身的生产、经营、决策和管理的水平,做强品牌,做大企业,做实市场,本文基于大数据技术,结合企业数据应用现状,从数据管理、品牌定位、物流运营及市场投放层面着手,提出了烟草企业如何借助数据分析调整战略布局。应用大数据技术后,烟草企业通过清晰客户需求,实现品牌精准定位,运营模式由规模性制造转向为个性化定制;通过掌控业务流程、品牌营销、市场竞争等方面的数据,实现市场的支配,企业决策方式由业务驱动转型为数据驱动;通过内外部数据采集、筛选、存储、分析和决策,以支撑预测、辅助决策,实现决策机制由被动式演变为预判式。     

面向海洋的多模态智能计算：挑战、进展和展望

海洋是高质量发展的要地,海洋科学大数据的发展为认知和经略海洋带来机遇的同时也引入了新的挑战。海洋科学大数据具有超多模态的显著特征,目前尚未形成面向海洋领域特色的多模态智能计算理论体系和技术框架。因此,本文首次从多模态数据技术的视角,系统性介绍面向海洋现象/过程的智能感知、认知和预知的交叉研究进展。首先,通过梳理海洋科学大数据全生命周期的阶段演进过程,明确海洋多模态智能计算的研究对象、科学问题和典型应用场景。其次,在海洋多模态大数据内容分析、推理预测和高性能计算3个典型应用场景中展开现有工作的系统性梳理和介绍。最后,针对海洋数据分布和计算模式的差异性,提出海洋多模态大数据表征建模、跨模态关联、推理预测以及高性能计算4个关键科学问题中的挑战,并提出未来展望。