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Self-Awareness for Autonomous Systems

PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Investigation of Power Networks and their Patterns by Mathematical methods in order to Voltage Stability Enhancement

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Journal of Physics: Conference Series 2019年第1期1391卷

作者： Seyed Morteza Moghimi Ali Bostani Abolfazl Elahimanesh Department of Electrical Engineering Islamic Azad University Iran. Associate Professor Department of Electrical and Computer Engineering American University of Kuwait Salmiya Lecturer Department of Electrical Engineering University of Applied Science and Technology (UAST) Qom Iran

Authors in the research paper has considered IEEE 14-bus and 34-bus test network for creation generation and load patterns. This paper aims at analysing the potential impacts that distributed generation (DG) might have on voltage stability of electrical power networks. It is expected that increasing amounts of new generation technologies will be connected to electrical power systems in the near future. Most of these technologies are considerably smaller scale than conventional synchronous generators. In this paper, the impact of DG pattern (size and location of DG) on the voltage stability of two test system is investigated. The simulation methodology is discussed as well. It is found that the effects of DG the voltage stability of a power system strongly depend on the size and location of the distributed generators. The results show that install of DG on the weak bus, improve loadability limit and voltage stability and decrease loss of system. By investigating and reviewing the results of similar patterns in these two systems, the different generation and load patterns impact mechanism of DG units over the behaviour of the systems in terms loadability limit and voltage stability is achieved.

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Privacy preserving query model using inverse laplacian differential technique

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Journal of Physics: Conference Series 2019年第1期1228卷

作者： K Sandhya Rani Kundra J Hyma P V G D Prasad Reddy K Venkata Rao Assistant Professor Department of Information Technology GVPCOE (A) Vishakhapatnam. Associate Professor Department of computer science engineering ANITS Vishakhapatnam. Professor Department of Computer Science & Systems Engineering Andhra University Vishakhapatnam.

Digitalization of data has proven its competent edge in the present digital era, leading to aggregation of mass amounts of data. This segregated data is made expendable by discovering interesting patterns made possible by 'Data Mining'. Setting apart its perks, it possesses a discernible intimidation of outpouring personal information of data owners to anonymous resources. As always privacy is a prime issue of concern, On the other hand trading absolute privacy for loss of certainty of a query may not produce efficient patterns like in in-depth analysis of the source data sets. To maintain a balance among the above mentioned areas of interest 'Privacy Preserving Data Mining (PPDM) using various privacy techniques is employed. The proposed work potentiates the working of privacy protection technique namely differential privacy using privacy parameter ε with heterogeneous adaptable method. In addition, this framework provides a basis for working with the inverse laplacian data distortion for better privacy protection in an interactive query model.

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Visuo-haptic Simulations to Improve Students’ Understanding of Friction Concepts

Visuo-haptic Simulations to Improve Students’ Understanding...

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Frontiers in Education (FIE) Conference

作者： Luis Neri Alejandra J. Magana Julieta Noguez Yoselyn Walsh Andres Gonzalez-Nucamendi Victor Robledo-Rella Bedrich Benes Professor of the School of Engineering and Sciences Tecnologico de Monterrey Mexico City Mexico Associate Professor of Computer and Information Technology and Engineering Education Purdue University West Lafayette Indiana Graduate Student of Computer and Information Technology & Costa Rica Institute of Technology Purdue University West Lafayette Indiana Professor of Computer Graphics Technology and Computer Science Purdue University West Lafayette Indiana

ISBN: (纸本)9781538611753;9781538611746

Statics is a backbone course for several engineering disciplines and also a pre-requisite for dynamics and mechanics of materials. Researchers have identified a lack of understanding of statics as a significant source of difficulties in terms of both conceptual understanding, representation of free body diagrams (FBD) and problem-solving ability. Our approach to improve the learning of the concept of friction focuses on students' understanding of acting forces and specific components of such forces of a system. The presented quasi-experimental study investigates how the use of visuo-haptic simulations can improve students understanding and use of FBD. Specifically, we compared two visuo-haptic simulations; one that explicitly visually depicts FBD of multiple objects interacting with different surfaces, while the other only provides haptic feedback while students engage in the same forms of interaction. Our results suggest that using the visuo-haptic simulator with FBD leads to better learning results. These findings support the hypothesis that appropriately sequenced visuo-haptic simulators with well-designed visual cues can help students to better understand and use FBD.

关键词： Friction Force Haptic interfaces Visualization Rough surfaces Surface roughness Kinetic theory

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Analysis on Various Machine Learning based Approaches with a Perspective on the Performance

Analysis on Various Machine Learning based Approaches with a...

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International Conference on Innovations in Power and Advanced Computing Technologies

作者： Meesala Shobha Rani Sumathy. S Research Scholar School of Computer Science and Engineering VIT University Vellore India Associate Professor School of Information Technology and Engineering VIT University Vellore India

ISBN: (纸本)9781509056835

With the rapid development of web 2.0, increased users of online social media show keen interest to express their opinion and reviews on numerous aspects such as microblogs, various products, hotels, movies and political issues. At present, text mining plays a vital role in various application domains such as online media, healthcare, security applications, business, marketing and industrial applications. In text mining, sentiment analysis or opinion mining is a task carried over to extract or classify the information. This paper presents an exhaustive study on the performance factors highlighting the current state-of art techniques and the open issues on various machine learning based text mining approaches.

关键词： Machine Learning Supervised Semi-supervised Unsupervised Sentiment Analysis

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Performance and analysis of MAC protocols based on application

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AIP Conference Proceedings 2018年第1期1952卷

作者： Ravi Yadav A. K. Daniel 1Research Scholar Computer Science and Engineering Department Madan Mohan Malaviya University of Technology Gorakhpur India 2Associate Professor Computer Science and Engineering Department Madan Mohan Malaviya University of Technology Gorakhpur India

Wireless Sensor Network is one of the rapid emerging technology in recent decades. It covers large application area as civilian and military. Wireless Sensor Network primary consists of sensor nodes having low-power, low cost and multifunctional activities to collaborates and communicates via wireless medium. The deployment of sensor nodes are adhoc in nature, so sensor nodes are auto organize themselves in such a way to communicate with each other. The characteristics make more challenging areas on WSNs. This paper gives overview about characteristics of WSNs, Architecture and Contention Based MAC protocol. The paper present analysis of various protocol based on performance.

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Middle East and North African Health Informatics Association (MENAHIA): Building Sustainable Collaboration

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Yearbook of Medical Informatics 2018年第1期27卷 286-291页

作者： Najeeb Al-Shorbaji Mowafa Househ Adel Taweel Abdullah Alanizi Bennani Othmani Mohammed Haitham Abaza Hala Bawadi Hamayon Rasuly Khalid Alyafei Luis Fernandez-Luque Mohamed Shouman Osama El-Hassan Rada Hussein Riyad Alshammari Salah Mandil Sarah Shouman Shahrad Taheri Tamer Emara Wasmiya Dalhem Zaid Al-Hamdan Zineb Serhier eHealth and Knowledge Management Consultant Retired Director of Knowledge Ethics and Research Department WHO/HQ Amman Jordan Department of Health Informatics College of Public Health and Health Informatics King Saud Bin Abdulaziz University for Health Sciences Ministry of National Guard-Health Affairs Riyadh Saudi Arabia Department of Computer Science BirZeit University Ramallah Palestine Head of Medical Informatics Unit 20 August Hospital Ibn Rochd University Hospital Casablanca Head of Casablanca Medical Informatics Laboratory Medical Faculty of Casablanca Morocco Department of Biomedical Engineering Misr University for Science & Technology Cairo Egypt Associate Professor College of Nursing University of Jordan Amman Jordan eHealth Program Coordinator Bamyan Provincial Hospital Bamyan City Afghanistan Chief Medical Informatics Officer (CMIO) - SIDRA Assistant Professor Clinical Pediatrics at Weill Cornell Medicine Qatar Qatar Computing Research Institute Hamad Bin Khalifa University Doha Qatar Faculty of Medicine Ain Shams University Cairo Egypt Vice-Chair of Emirates Health Informatics Society Head of eHealth Section at Dubai Health Authority Dubai United Arab Emirates Founder and Former Director of the Biomedical Informatics Center of Excellence (BMICoE) Information Technology Institute (ITI) Ministry of Communications and Information Technology (MCIT) Egypt President of Saudi Association for Health Informatics Riyadh Saudi Arabia Senior Consultant on eStrategies and eHealth to WHO and ITU Geneva Switzerland Department of Medicine Weill Cornell Medical College in Qatar Qatar Foundation Doha Qatar Executive Director of Nursing Informatics Hamad Medical Corporation Qatar Associate Professor of Nursing Management Faculty of Nursing Jordan University of Science and Technology Irbid Jordan Professor at Medical Informatics Laboratory Faculty of Medicine and Pharmacy Hassan II University Casablanca Morocco

There has been a growing interest in Health Informatics applications, research, and education within the Middle East and North African Region over the past twenty years. People of this region share similar cultural and religious values, primarily speak the Arabic language, and have similar health care related issues, which are in dire need of being addressed. Health Informatics efforts, organizations, and initiatives within the region have been largely under-represented within, but not ignored by, the International Medical Informatics Association (IMIA). Attempts to create bonds and collaboration between the different organizations of the region have remained scattered, and often, resulted in failure despite the fact that the need for a united health informatics collaborative within the region has never been more crucial than today. During the 2017 MEDINFO, held in Hangzhou, China, a new organization, the Middle East and North African Health Informatics Association (MENAHIA) was conceived as a regional non-governmental organization to promote and facilitate health informatics uptake within the region endorsing health informatics research and educational initiatives of the 22 countries represented within the region. This paper provides an overview of the collaboration and efforts to date in forming MENAHIA and displays the variety of initiatives that are already occurring within the MENAHIA region, which MENAHIA will help, endorse, support, share, and improve within the international forum of health informatics.

关键词： eHealth Middle East and North Africa Health Informatics collaboration MENAHIA Universal Health Coverage Bioinformatics International Medical Informatics Association

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

Recommender System Framework for Academic Choices: Personali...

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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

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Automatic Characterization of Benign and Malignant Masses in Mammography

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Procedia computer science 2015年 46卷 1762-1769页

作者： K. Vaidehi T.S. Subashini Research Scholar Department of Computer Science and Engineering Faculty of Engineering and Technology Annamalai University India Associate Professor Department of Computer Science and EngineeringFaculty of Engineering and Technology Annamalai University India

The paper aims to develop an automated breast mass characterization system for assisting the radiologist to analyze the digital mammograms. Mammographic Image Analysis Society (MIAS) database images are used in this study. Fuzzy C-means technique is used to segment the mass region from the input image. GLCM texture features namely contrast, correlation, energy and homogeneity are obtained from the region of interest. The texture features extracted from gray level co-occurrence matrix (GLCM) are computed at distance d=1 and θ=0 o , 45 o , 90 o , 135 o . These with three classifiers namely adaboost, back propagation neural network and sparse representation classifiers are used for characterizing the region containing either benign mass or malignant mass. The experimental results show the SRC classifier is more effective with an accuracy of 93.75% and with the Mathew's correlation coefficient (MCC) of 87.35%.

关键词： Benign and malignant mass classification Fuzzy C-Means clustering Sparse representation classifier Mathews correlation coefficient.

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Refining of image using self-organizing map with clustering

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AIP Conference Proceedings 2016年第1期1715卷

作者： Neeraj Dahiya Surjeet Dalal Gundeep Tanwar 1)Assistant Professor Department of Computer Science & EngineeringSRM University Haryana India 2)Associate Professor Department of Computer Science & Engineering SRM University Haryana India 3)Associate Professor Department of Computer Science & Engineering BRCM College of Engineering & Technology BahalBhiwani Haryana India

Self Organization Map(SOM) is an automatic tool in data analysis in data mining,it is used to explore the multi-dimentional data which simplifies complexity and produce meaningful relation with each other or high dimentional into low dimentional .the powerful method of SOM i.e learning method results excellent performance .the SOM algorithum have various steps from starting stage to the final neuron and their weight updation and modification, these procedure resultant a lot of compplexity accoording to the parameters on the basis of experiments .this paper will compare and discuss various papameters and their result or factors that can improve and refine the image through varius process of SOM.

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