检索结果-内蒙古大学图书馆

Trust Based Certificate Revocation for Secure Routing in MANET

Procedia computer science 2016年 92卷 431-441页

作者： Banoth Rajkumar G. Narsimha Research scholar Department of computer science and engineering Jawaharlal Nehru technological university Hyderabad telangana india Associate professor Computer science and engineering department Jawaharlal Nehru technological university Hyderabad telangana india

Many trust establishment solutions in mobile ad hoc networks (MANETs) rely on public key certificates. Therefore, they should be accompanied by an efficient mechanism for certificate revocation and validation. In order to reduce the hazards from nodes and to enhance the security of network we propose to develop a CA distribution and a Trust based threshold revocation method. Initially the trust value is computed from the direct and indirect trust values. And the certificate authorities distributes the secret key to al the nodes. Followed by this a trust based threshold revocation method is computed. Here the misbehaving nodes are eliminated.

关键词： MANET attack Trust based threshold revocation method malicious nodes

来源：评论

学校读者我要写书评

暂无评论

Recommender System Framework for Academic Choices: Personality Based Recommendation Engine (PBRE)

Recommender System Framework for Academic Choices: Personali...

引用

IEEE International Conference on Information Reuse and Integration (IRI)

作者： Muhammad Fahim Uddin Soumita Banerjee Jeongkyu Lee School of Computer Science and Engineering Graduate Student School of Technology Management Associate Professor School of Computer Science and Engineering University of Bridgeport Bridgeport CT USA

ISBN: (纸本)9781509032082

A tremendous growth and progress has shown the potential of big data (i.e structured, unstructured and semi-structured) to extract valuable information and do reliable prediction for several industries. Social networking data has created additional opportunities for data scientists and researchers to utilize the data points to advance the predictive and mining models and techniques. However, predictive analysis in field of academics is at its infancy. In this paper, we present a framework to implement a recommender system to improve academic choice process for new students. The framework is based on our ongoing research for Predicting Educational Relevance For an Efficient Classification of Talent (PERFECT Algorithm Engine), that utilizes stochastic probability distribution based modeling. We present an algorithm and math construct to support our work along with providing graphical results for various parameters that help the recommendation and decision process for individuals. We show related study and conclude with future work.

关键词： Recommender systems Data mining Engines Prediction algorithms Data models Facebook

来源：评论

学校读者我要写书评

暂无评论

Future CSP in South Africa – A review of generation mix models, their assumptions, methods, results and implications

引用

AIP Conference Proceedings 2018年第1期2033卷

作者： D. Frank Duvenhage Omotoyosi O. Craig Alan C. Brent William H. L. Stafford 1Ph.D. candidates Engineering Management Stellenbosch University Department of Industrial Engineering Private Bag XI Matieland 7602 Stellenbosch South Africa 2Extraordinary Professor Department of Industrial Engineering and the Centre for Renewable and Sustainable Energy Studies Stellenbosch University South Africa 3Professor Sustainable Energy Systems Engineering and Computer Science Victoria University of Wellington New Zealand 4Extraordinary Associate Professor Department of Industrial Engineering Stellenbosch University South Africa 5Senior Researcher Green Economy Solutions Natural Resources and the Environment Unit Council for Scientific and Industrial Research South Africa

South Africa has experienced great uncertainty in its electricity supply sector. Many energy system modeling efforts have been undertaken. This is to determine the most appropriate energy mix and manage uncertainty. We review all available, relevant studies and summarize their results, modeling approaches, and input assumptions. From this, we try to understand their impact on CSP development in South Africa.

关键词：

来源：评论

学校读者我要写书评

暂无评论

We Are What We Generate - Understanding Ourselves Through Our Data

引用

Procedia computer science 2016年 95卷 335-344页

作者： Muhammad Fahim Uddin Jeongkyu Lee Graduate Student School of Computer Science and Engineering University of Bridgeport Bridgeport CT 06604 U.S.A Advisor Associate ProfessorSchool of Computer Science and Engineering University of Bridgeport Bridgeport CT 06604 U.S.A

We have tendency to exhibit ourselves through the data we share about ourselves including, liking, friendship, follows, disliking, pictures, audio, videos, causes, blogs and sites. Such data about us have already been used by big data companies to create customized ads and marketing tactics. However, while such data being in unstructured and noisy format, utilization and research is at its early stages. In this paper, we elaborate on the idea of understanding individuals through lens of data they produce in context of our main research work for Predicting Educational Relevance For an Efficient Classification of Talent (PERFECT) algorithm engine. We illustrate some of research problems in relevance of such data and identify research problem as ground for this paper. We present sub set of our framework including algorithm and math constructs, for the problem we identify. We conclude that such analytics and cognitive research can help to improve education, healthcare, Job economy, crime control, etc. Thus we coin the phrase “we are what we generate”, with our work in this paper. We suggest future work and opportunities in relevant directions.

关键词： Social networking data data mining personality computing and prediction Big Five Personality Traits model

来源：评论

学校读者我要写书评

暂无评论

Utilizing Relevant Academic and Personality Features from Big Unstructured Data to Identify Good and Bad Fit Students

引用

Procedia computer science 2016年 95卷 383-391页

Education is the backbone for the success of every economy and industry. It is of vital importance to understand it through lens of academic and real world data for our students and job candidates. Such analytics and knowledge can help to improve the system towards making right academic and career choices for fresh individuals. Traditionally, very little data is used by individual to make decision and most of the time; he or she is at mercy of trend, family inclination, finance and inner motivation. However, chances of success or failures are absolute unknown to them at that time. In this paper, we discuss the potential of using personality data from social networking such as Facebook, Twitter, and LinkedIn and correlating it with academic and career data to improve prediction and classify good fit and bad students accordingly. We present framework to utilize huge data with relevant features of personality of individual to reveal the useful analytics and insights. This work is in conjunction with our main research using Stochastic Probability Distribution, Bayesian Networks and Excel data tools. We provide relevant study and conclude with future work with recommendation to produce more Good fit students in our school and colleges.

关键词： Personality computing unstructured big data academic data prediction stochastic probability distribution

来源：评论

学校读者我要写书评

暂无评论

Jump Starting Research: Preresearch STEM Programs

引用

Journal of College science Teaching 2016年第5期45卷 13-19页

作者： Schneider, Kimberly R Bahr, David Burkett, Susan Lusth, John C Pressley, Shelley VanBennekom, Neyda Director of the Office of Undergraduate Research in the University of Central Florida in Orlando Head and professor in the School of Materials Engineering at Purdue University in West Lafayette Indiana Professor in the Department of Electrical and Computer Engineering at the University of Alabama in Tuscaloosa Associate professor in the Department of Computer Science at the University of Alabama in Tuscaloosa Associate research professor in the Department of Civil and Environmental Engineering at Washington State University in Pullman Director of the Office of Undergraduate Research at Washington State University in Pullman Graduate teaching associate in the Office of Undergraduate Research in the University of Central Florida in Orlando

There are many benefits to getting students involved in research early in their career. However, first- and second-year students are often unaware of the research process and have no experience interacting with faculty, especially at large institutions. Three different course models devoted to preparing science and engineering students for successful research endeavors were offered at three research institutions. Goals of this work include (a) involving students early in their academic career so they can gain the most out of subsequent research experiences and (b) providing basic skills to make the transition into the research environment easier. These preresearch course models include a semester-long seminar, a 1-week faculty-led "boot camp," and an intense 3-day peer mentor led course. A pre- and posttest have been developed to help with the evaluation of the project. Results show similar gains in conceptual awareness between each course format and at each institution. This suggests that the educational models may be transferrable and easily adopted. Additionally, survey data indicate that students completing the program have a high placement into research experiences within 1 year of completing the course. Since 2011, over 500 science and engineering preresearch students have completed the courses through this collaboration.

关键词： STEM education STUDENT research STUDENT engagement UNDERGRADUATES CURRICULA (Courses of study) STUDY & teaching (Higher)

来源：评论

学校读者我要写书评

暂无评论

Optimal Cluster Head Selection Based Energy Efficient Technique for Defending against Gray Hole and Black Hole Attacks in Wireless Sensor Networks

引用

Procedia computer science 2016年 78卷 423-430页

作者： Snehal P. Dongare R.S. Mangrulkar M.Tech. (Computer Science and Engineering) Department of Computer Engineering B. D. College of Engineering Sevagram-442102 WARDHA (M.S.) INDIA Associate Professor and Head Department of Computer Engineering B. D. College of Engineering Sevagram-442102 WARDHA (M.S.) INDIA

Wireless Sensor Networks (WSNs), is prone to various types of attacks and security threats. Due to its dynamic topology, highly decentralized infrastructure and resource constraint sensors, proper energy utilization becomes a challenging issue. Such entities are responsible to make WSNs susceptible to various types of denials of service attacks which results in disastrous consequences like energy-hole creation in the network. Various cluster head selection based energy efficient protocols have been proposed to improve the lifetime of WSNs. In most of the energy efficient techniques, different approaches for energy utilization by sensors are proposed to extend lifetime of WSNs. The earlier scheme is defend against cooperative Gray-Hole and Black-Hole attacks that lead to performance degradation in WSNs containing mobile sensors. In order to overcome this, an energy efficient technique is presented in this paper to mitigate the impact of both kind of attacks simultaneously, on improving cluster head selection mechanism. Here, an energy efficient technique, on detecting and preventing compromised node to be a part on network communication in WSNs. The honest nodes is also determined to entrust as cluster head during packets transmission phase. The simulation results compare proposed protocol with state of the art LEACH protocol, which argues that the proposed scheme effectively minimize the chance of compromised node to become the cluster head and significantly improves network performance using networks dynamics viz. Packet Delivery Ratio(PDR), throughput, end-to-end delay and energy utilization in WSNs.

关键词： Black-Hole Attack Cluster Head Selection Energy Efficiency Gray-Hole Attack LEACH Network Delay Network Lifetime Packet Delivery Ratio Throughput Wireless Sensor Networks.

来源：评论

学校读者我要写书评

暂无评论

Use of Fuzzy Tool for Example Based Machine Translation

引用

Procedia computer science 2016年 79卷 199-206页

作者： Manish Rana Mohammad Atique Research Scholar Post Graduate Department of Computer Science & Engineering Sant Gadge Baba Amravati University Amravati India Mohammad Atique Associate Professor Post Graduate Department of Computer Science Sant Gadge Baba Amravati University Amravati India

This research paper proposes work carried in machine translation. It shows the comparison of various techniques like SMT, SSER, EBMT, RBMT etc used for machine translation. After going through the result of various techniques it conclude that still better result can be gained . Thus proposes an idea of using Fuzzy logic tool to improve the natural learning process and get better result around 81.7 percentage. This work shows the implementation of the tool for refining the result in example based machine translation using fuzzy logic.

关键词： SMT NLP RBMT EBMT SSER etc.

来源：评论

学校读者我要写书评

暂无评论

Cloud Computing – A Unified Approach for Surveillance Issues

引用

IOP Conference Series: Materials science and engineering 2017年第1期225卷

作者： C R Rachana Dr. Reshma Banu Dr. G F Ali Ahammed Dr. B D Parameshachari Associate Professor & Head DoS in Computer Science Pooja Bhagavat Memorial Mahajana Education Centre K.R.S. Road Metagalli Mysuru-16. Professor & Head Department of I S E GSSSIETW Mysore Karnataka India. Associate Professor Department of Computer Science Engineering VTU Post Graduate Centre Mysuru. Professor & Head TCE Dept. GSSSIETW Mysore Karnataka India.

Cloud computing describes highly scalable resources provided as an external service via the Internet on a basis of pay-per-use. From the economic point of view, the main attractiveness of cloud computing is that users only use what they need, and only pay for what they actually use. Resources are available for access from the cloud at any time, and from any location through networks. Cloud computing is gradually replacing the traditional Information Technology Infrastructure. Securing data is one of the leading concerns and biggest issue for cloud computing. Privacy of information is always a crucial pointespecially when an individual's personalinformation or sensitive information is beingstored in the organization. It is indeed true that today; cloud authorization systems are notrobust enough. This paper presents a unified approach for analyzing the various security issues and techniques to overcome the challenges in the cloud environment.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analytical study of sandwich structures using Euler–Bernoulli beam equation

引用

AIP Conference Proceedings 2017年第1期1798卷

作者： Hui Xue H. Khawaja 1Master Student Department of Computer Science and Computational Engineering UiT The Arctic University of Norway Narvik Norway 2Associate Professor Department of Engineering and Safety UiT The Arctic University of Norway Tromsø Norway

This paper presents an analytical study of sandwich structures. In this study, the Euler–Bernoulli beam equation is solved analytically for a four-point bending problem. Appropriate initial and boundary conditions are specified to enclose the problem. In addition, the balance coefficient is calculated and the Rule of Mixtures is applied. The focus of this study is to determine the effective material properties and geometric features such as the moment of inertia of a sandwich beam. The effective parameters help in the development of a generic analytical correlation for complex sandwich structures from the perspective of four-point bending calculations. The main outcomes of these analytical calculations are the lateral displacements and longitudinal stresses for each particular material in the sandwich structure.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：