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Analysis for Maximal Optimized Penalty for the Scheduling of Jobs with Specific Due Date on a Single Machine with Idle Time

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Procedia computer Science 2015年 47卷 247-254页

作者： D. Jagan A.N. Senthilvel R. Prabhakar S. Uma Maheswari PG Scholar Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore - 641014 India Assistant Professor(SG) Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore - 641014 India Emeritus Professor Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore - 641014 India Associate Professor Department of Electronics and Communication Engineering Coimbatore Institute of Technology Coimbatore641014 India

In the real world the Scheduling of Jobs in industries is provided without any idle time which is very tedious. Practically it becomes difficult when any of the spare part has started to malfunction and has to be changed in the machine then some idle time is needed in order to undergo the change. In this proposed work some amount of idle time is allotted to schedule the jobs in a single machine which includes three stages namely scheduling strategy, inserting idle time and optimizing the net penalty value of all the jobs.

关键词： Single machine scheduling Early/Tardy scheduling optimization techniques

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Neural Network-Based Drug Abuse Treatment Optimization

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Procedia computer Science 2015年 61卷 454-459页

作者： Jeff Cohen Abby Ilumoka Iman Salehi Professor of Economics University of Connecticut Storrs CT 06269 Professor of Electrical & Computer Engineering University of Hartford West Hartford CT 06117 Graduate Assistant Department of Electrical & Computer Engineering University of Hartford West Hartford CT 06117

In 2009, 2.6 million people in the United States over 12 years of age received treatment for substance abuse at a “specialty facility”. The direct cost of substance abuse treatment was estimated to be $22 billion in 2005, up from $11 billion in 1991. With recent federal health care reform, more clients may seek treatment, but it is unclear how this would affect clinics’ costs per client. Although past studies on substance abuse costs find some evidence of economies of scale, they also find wide variation in the average costs of treatment, the reasons for which require further investigation. As a result, state substance abuse agencies and other payers face difficulty in determining how to pay providers, in fact, very often funding is inadequate or wasted. The drug abuse treatment process can be viewed as a complex adaptive system in which system inputs such as workers, physical capital and other materials are converted into outputs such as treatment completions and outcomes. Treatment clinics desire the most cost efficient input mix to generate desired outputs. Although substance abuse researchers are ahead of many other fields in developing and refining instruments such as the Drug Abuse Treatment Cost Analysis Program, many of these instruments are restricted by the fact that databases have many omissions making it difficult to answer research questions that might otherwise be informed by economic analysis. Additionally, due to the large numbers of variables involved, trade-offs are difficult to explore. Questions such as “what are the relationships between costs and case-mix?” or “what are reasonable reimbursement rates for substance abuse treatment and how do they differ for specialized populations such as heroin users?” are difficult to answer. The work reported in this paper provides significant insight that can help policymakers to decide where to focus funding through 1) prediction of missing treatment data and 2) identification of critical variables.

关键词： complex adaptive systems drug abuse treatment neural networks total functional cost sensitivity analysis

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Hybrid Intrusion Detection System for Private Cloud: A Systematic Approach

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Procedia computer Science 2015年 48卷 325-329页

作者： Praveen Kumar Rajendran B. Muthukumar G. Nagarajan Department of Computer Science and Engineering Sathyabama University Chennai India Professor Faculty of Computing Sathyabama University Chennai India Assistant Professor Faculty of Electrical and Electronic Engineering Sathyabama University India

Cloud computing is one of the latest and an emerging area in the Information and Technology (IT) sector, which has given a different dimension to the organizations. Performance and security aspects of private cloud and widely used public cloud are the major issues which have to be addressed in Cloud Computing. Intrusion is one such critical and important security problem for Cloud Computing. This paper will attempt to give an overall idea about Cloud computing, Intrusion, types of Intrusion Detection Systems and earlier works done on Intrusion Detection System. The key proposal of this paper is to give an overall idea for building a Hybrid Intrusion Detection System that would detect any type of intrusion into the cloud.

关键词： Cloud computing Types of cloud Services of Cloud Issues in Cloud Intrusion Hybrid Intrusion Detection System.

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Clustering Models for Data Stream Mining

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Procedia computer Science 2015年 46卷 619-626页

作者： R. Mythily Aisha Banu Shriram Raghunathan Assistant Professor Department of Information Technology B.S. Abdur Rahman University Chennai India Professor Department of Computer Science and Engineering B.S. Abdur Rahman University Chennai India

The scope of this research is to aggregate news contents that exists in data streams. A data stream may have several research issues. A user may only be interested in a subset of these research issues; there could be many different research issues from multiple streams, which discuss similar topic from different perspectives. A user may be interested in a topic but do not know how to collect all feeds related to this topic. The objective is to cluster all stories in the data streams into hierarchical structure for a better serve to the readers. The work utilizes segment wise distributional clustering that show the effectiveness of data streams. To better serve the news readers, advance data organization is highly desired. Once catching a glimpse of the topic, user can browse the returned hierarchy and find other stories/feeds talking about the same topic in the internet. The dynamically changing of stories needs to use the segment wise distributional clustering algorithm to have the capability to process information incrementally.

关键词： Data streams information retrieval data mining

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A novel expert system for diagnosis of fetal alcohol syndrome using close range photogrammetry

A novel expert system for diagnosis of fetal alcohol syndrom...

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International Congress on Technology, Communication and Knowledge (ICTCK)

作者： Malihe Sadat Esmaeil Shahabi Amir Hossein Taherinia M.Sc. Student of Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran Assistant Professor of Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781467397636

Remaining necessary information will be received from the patient along with the output of last stage applies to expert system. Decision making in expert system is based on fuzzy method which is done in two stages. In the stage of extracting data from image, according to provided samples, the operator can choose the key points manually. However, due to the dependence of this method to the operator, it is recommended to the user to select image processing the accuracy and validity of input parameters extraction and accelerate the effective of the whole process. In this paper, we have tried to present an expert system to diagnose fetal alcohol syndrome in which we are able to diagnose the diagnose without the need for an expert. In this method according to the input image, the parameters for diagnose of eye deformities extracted and will be sent to the expert system as input.

关键词： Expert systems Diseases Decision making Medical diagnostic imaging Data acquisition

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Agricol: An application for the betterment of farming community

Agricol: An application for the betterment of farming commun...

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International Conference on Soft-Computing and Networks Security (ICSNS)

作者： K.R. Nivethitha S. Oswalt Manoj Final Year M.E Department of Computer Science and Engineering Sri Ramakrishna Institute of Technology Coimbatore TN Assistant Professor Department of Computer Science and Engineering Sri Ramakrishna Institute of Technology Coimbatore TN

The matter of great concern is that there exists wider gap between the proportion of the technologies generated by the public agricultural research system and technologies adopted by the farmers in India. One of the vital reasons for such wide gap is due to the lack of an appropriate extension/technology transfer model in agriculture that could establish better linkage between scientists and farmers in order to facilitate effective dissemination in a timely manner. Hence there is a need to develop suitable approach for technology transfer in agriculture. In order to bridge the gap between the technologies and the farming community, e-Velanmai project has been introduced. Under e-Velanmai, various applications and the projects are developed. Agricol, is one such application that can bridge the gap and it helps to provide the farming community with better solutions for the diseased plants in quickly manner.

关键词： Technology transfer Security Communication networks computer science Agriculture Bridges Data models

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Social Semantic Web Mining

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2015年

作者： Tope Omitola Sebastian A. Rios John G. Breslin

ISBN: (数字)9781627053990

The past ten years have seen a rapid growth in the numbers of people signing up to use Web-based social networks (hundreds of millions of new members are now joining the main services each year) with a large amount of content being shared on these networks (tens of billions of content items are shared each month). With this growth in usage and data being generated, there are many opportunities to discover the knowledge that is often inherent but somewhat hidden in these networks. Web mining techniques are being used to derive this hidden knowledge. In addition, the Semantic Web, including the Linked Data initiative to connect previously disconnected datasets, is making it possible to connect data from across various social spaces through common representations and agreed upon terms for people, content items, etc. In this book, we detail some current research being carried out to semantically represent the implicit and explicit structures on the Social Web, along with the techniques being used to elicit relevant knowledge from these structures, and we present the mechanisms that can be used to intelligently mesh these semantic representations with intelligent knowledge discovery processes. We begin this book with an overview of the origins of the Web, and then show how web intelligence can be derived from a combination of web and Social Web mining. We give an overview of the Social and Semantic Webs, followed by a description of the combined Social Semantic Web (along with some of the possibilities it affords), and the various semantic representation formats for the data created in social networks and on social media sites. Provenance and provenance mining is an important aspect here, especially when data is combined from multiple services. We will expand on the subject of provenance and especially its importance in relation to social data. We will describe extensions to social semantic vocabularies specifically designed for community mining purposes (SIOCM). In the

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Motor task event detection using Subthalamic Nucleus Local Field Potentials

Motor task event detection using Subthalamic Nucleus Local F...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Soroush Niketeghad Adam O. Hebb Joshua Nedrud Sara J. Hanrahan Mohammad H. Mahoor is a neurosurgeon the electrical and computer engineering dept. University of Denver Denver CO is a neurosurgeon at Colorado brain and spine institute Englewood CO and a visiting assistant professor of electrical and computer engineering dept. University of Denver Denver CO is an Investigator Scientist at Colorado Neurological Institute Englewood CO is an associate professor in the department of electrical and computer engineering University of Denver Denver CO

ISBN: (纸本)9781424492695

Deep Brain Stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson's disease. Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and DBS side effects. In such systems, DBS parameters are adjusted based on patient's behavior, which means that behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local Field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. A practical behavior detection method should be able to detect behaviors asynchronously meaning that it should not use any prior knowledge of behavior onsets. In this paper, we introduce a behavior detection method that is able to asynchronously detect the finger movements of Parkinson patients. As a result of this study, we learned that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We used non-linear regression method to measure this connectivity and use it to detect the finger movements. Performance of this method is evaluated using Receiver Operating Characteristic (ROC).

关键词： STN LFP ROC

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Role of Movement and Stillness Elements in Development of Iranian-islamic Cities in order to Make Optimal Satisfaction in Human (Case Study: Bazaar, Mosque, House)

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Procedia - Social and Behavioral Sciences 2015年 201卷 201-212页

作者： Masoumeh Ghanaati Amir Reza Karimi Azeri Fatemeh Ghanaati S.Bagher Hosseini Student of Master Institute for Higher Education Deylaman University Lahijan Iran Assistant Professor Architecture and Art Faculty University of Guilan Rasht Iran Department of Computer Engineering Faculty Islamic Azad University Astaneh Ashrafiyeh Branch Iran Associate Professor Architecture & urban study University of science and technology Iran

According to Islamic beliefs, movement and stillness of Iranian architecture, also to its literal meaning, has a more complex meaning and understanding its space has a special place. The purpose of this research is to study the role of some movement and stillness elements in the development of Iranian-Islamic cities to make optimal satisfaction in human. The method of this study is descriptive-analytical. Hence, in this research, first, the concepts of movement and stillness and its components in Iranian-Islamic architecture have been expressed. Then, we introduce Iranian-Islamic mosques, houses and Bazaars (markets) as the prominent buildings of our paper. The finding result of the research shows that movement and stillness elements have an important influence on the satisfaction of the environment and realization of peace in human.

关键词： Movement stillness Iranian-Islamic architecture satisfaction

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Restructuring Web Search Results by Generating Feedback Session and Clustering Pseudo Documents

Restructuring Web Search Results by Generating Feedback Sess...

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Conference on Power, Control, Communication and Computational Technologies for Sustainable Growth

作者： Bhagyashri Girdhar Salve R. B. Wagh PG Student Department of Computer Engineering North Maharashtra University SES's R. C. Patel Institute of Technology Shirpur India Assistant Professor Department of Computer Engineering North Maharashtra University SES's R. C. Patel Institute of Technology Shirpur India

ISBN: (纸本)9781467368919

Restructuring web search results is the best solution for ambiguous queries being entered to the search engine. When ambiguous queries are entered to the search engine gives multiple results for same query, so user don't get specific and accurate information about what they really want, so it becomes difficult for a user to get specific information related to the submitted keyword. For this reason a new criterion is used in which feedback sessions are first generated from user clicked through logs. Using Feedback session a pseudo documents are generated by calculating TF-IDF (Term Frequency Inverse Data Frequency) vectors for each URL in clicked through logs. Then k-means clustering algorithm is applied and these pseudo documents are clustered and user search goals are generated and restructuring is done through user search goal and user gets specific information fast and correctly. Then the performance of each user search goal is calculated by using CAP metric. These metrics shows how correct restructuring is done. On the basis of this metrics we conducted our experiments on 1720 queries from which 100 most ambiguous queries were separately considered. We observed that the results were high in performance of restructure and less risk.

关键词： queries user search goal pseudo documents classified average precision k-means clustering TF-IDF vector

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