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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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Performance Analysis of a Cloud Computing System using Queuing Model with Correlated Task Reneging

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Journal of Physics: Conference Series 2021年第1期2091卷

作者： Rakesh Kumar Bhavneet Singh Soodan Godlove Suila Kuaban Piotr Czekalski Sapana Sharma School of Mathematics Shri Mata Vaishno Devi University Katra Jammu and Kashmir 182320 India Department of Mathematics and Statistics Namibia University of Science and Technology Private Bag 13388 Windhoek Namibia 13 Jackson Kaujeua Street Windhoek Namibia Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 44-100 Gliwice Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Department of Mathematics Cluster University of Jammu Jammu and Kashmir

Queuing theory has been extensively used in the modelling and performance analysis of cloud computing systems. The phenomenon of the task (or request) reneging, that is, the dropping of requests from the request queue often occur in cloud computing systems, and it is important to consider it when developing performance evaluations models for cloud computing infrastructures. Majority of studies in the performance evaluation of cloud computing data centres with the use of queuing theory do not consider the fact that the tasks could be removed from queue without being serviced. The removal of tasks from the queue could be due to the user impatience, execution deadline expiration, security reasons, or as an active queue management strategy. The reneging could be correlated in nature, that is, if a request is dropped (or reneged) at any time epoch, and then there is a probability that a request may or may not be dropped at the next time epoch. This kind of dropping (or reneging) of requests is referred to as correlated request reneging. In this paper we have modelled a cloud computing infrastructure with correlated request reneging using queuing theory. An M/M/1/N queuing model with correlated reneging has been used to study the performance analysis of the load balancing server of a cloud computing system. The steady-state as well as the transient performance analyses have been carried out. Important measures of performance like average queue size, average delay, probability of task blocking, and the probability of no waiting in the queue are studied. Finally, some comparisons are performed which describe the effect of correlated task reneging over simple exponential reneging.

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Multi Path Routing Technique Based RRP for P2P Network

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IOP Conference Series: Materials science and Engineering 2020年第1期994卷

作者： Mary Subaja Christo R. M. Bommi K. Mariyappan Associate Professor Department of Information Science and Engineering Faculty of Engineering Technology Jain University Bangalore India Associate Professor Mechatronics Engineering Department Chennai Institute of Technology Kundratur India Assistant Professor Department of Computer Science and Engineering Jain University Bangalore India

All articles must contain an abstract. Peer to Peer (P2P) network is useful for developing applications and downloading files from the internet. In the existing P2P networks, communication is initiated and supported by peers. Security issues constitute the main challenge in the design of reliable communication techniques for P2P networks. In the past, Rumor Riding Protocol was used in distributed systems for performing coordination and communication. However, the existing Rumor Riding Protocol is used flooding technique to forward the response to the initiator it may leads high network traffic to avid this I have Enhanced Multi path forwarding technique to Rumor Riding Protocol and also enhancement with security features to make them suitable for downloading applications in P2P networks. In this method, it enhances the Rumor Riding Protocol with security features by including a Cryptographic Puzzle, a Challenge Question scheme using trust modeling and an intelligent beta reputation model for secured communication in P2P networks. For this purpose, five new techniques are proposed in this research work, all of which aim at enhancing the security of communication using Rumor Riding Protocol in the P2P networks.

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Machine Learning Models for Prediction of Cardiovascular Diseases

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Journal of Physics: Conference Series 2021年第1期2040卷

作者： K. Sivaraman V. Khanna Research Scholar Department of Computer Science and Engineering Bharath Institute of Higher Education and Research Chennai-73 Tamil Nadu India. Professor Department of Information Technology Bharath Institute of Higher Education and Research Chennai-73 Tamil Nadu India.

Support Vector Machines (SVM) [9], Ada Boost (AB) [10], and Gradient Boosting (GB). Maximum Relevance, Minimum Redundancy (mRMR), Relief, and Least Absolute Shrinkage and Selection Operator (LASSO) are examples of fast correlation-based filters. The authors tested all attributes as well as the selected attributes generated by the above feature selection methods on the Cleveland heart disease dataset (CHDD) and the Hungarian heart disease dataset (HHDD). For their suggested framework, the authors were able to attain the greatest feasible model accuracy of 92.09 percent (all features) and 94.41 percent (selected features). The early detection of cardiac disease was demonstrated by several additional researchers.

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RNN based prediction of spatiotemporal data mining

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IOP Conference Series: Materials science and Engineering 2020年第2期981卷

作者： Mohammed Ali Shaik Dhanraj Verma P Praveen K Ranganath Bonthala Prabhanjan Yadav Department of Computer Science & Engineering SR University Warangal Telangana India Professor Department of Computer Science & Engineering Dr. APJ Abdul Kalam University Indore India Sumathi Reddy Institute of Technology for Women Warangal India

The Spatiotemporal pattern is considered by most of the researchers to be a rehashed arrangement or relationship of specific occasions or highlights of spatiotemporal and to distinguish these groupings or affiliations are related to the spatiotemporal patterns of wrongdoing events and proper separation are clearly based on length based estimations that are expected to oblige the size or state of the pattern and ST patterns comprises of various sizes and shapes after some time are non-consistently disseminate over space by performing analytical learning of spatiotemporal successions as it is capable of creating future pictures by knowledge from the authentic edges. Spatial advents and temporal varieties are two pivotal structures which are considered in this paper which proposes the predictive methodology which utilizes recurrent neural network where the approach of persistent neural networks stands apart as a suitable worldview for without model as the data is based on the prediction of nonlinear dynamical frameworks by applying the methodology in Spatiotemporal pattern which predicts the limited mistake.

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Smart Villages: IoT technology Based Transformation

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Journal of Physics: Conference Series 2021年第1期2070卷

作者： Pankaj Mudholkar Megha Mudholkar B S Puneeth Kumar V Dankan Gowda S. Srinivasulu Raju Assistant Professor Department of Master of Computer Applications. Thakur Institute of Management Studies Career Development and Research Mumbai Maharashtra (State) INDIA Assistant Professor Department of Computer Science. St. Joseph's College (Autonomous) Bangalore Karnataka (State) INDIA Assistant Professor Department of Electronics and Communication Engineering. B.M.S. Institute of Technology and Management Bangalore Karnataka (State) INDIA Department of Electronics and Instrumentation Engineering. Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada Andhra Pradesh(State) INDIA

In recent years, large-scale urbanisation has been on the rise with cities being the hubs for growth, but rural business continues to play an important role in any country's overall development. A recent report reveals that almost 69 percent of India's population resides in their villages, accounting for almost 50 percent of the nation's GDP. This agricultural region varies from small towns with less than 500 residents to small towns. There are also similar situations in western nations. Despite their economic contribution, smaller villages seem to earn fewer in terms of infrastructural expenditure. The major problems addressed in these small towns include shortage of adequate public transit, emergency care and limited knowledge on federal subsidies for rural areas. Our vision is to expand the Smart city to Smart village by allowing use of recent technical advances and giving more attention to the problems in rural areas. The approach in this chapter is to bring IoT technology to Villages by literally showing a network of linked sensors and knowledge dissemination devices, controlling energy use and ensuring infrastructure protection. It gives a wide-ranging vision of enhancing the standard of living in villages and encourages them to meet the essential needs of domestic villagers.

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H-array system on picture languages with array rewriting rules

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AIP Conference Proceedings 2020年第1期2277卷

作者： D. K. Sheena Christy P. John Paul D. G. Thomas 1Assistant Professor Department Of Mathematics SRM Institute Of Science And Technology India 2Teaching Associate Department Of Computer Of Science And Engineering SRM Institute Of Science And Technology India 3Professor Department Of Science and Humanities Saveetha School Of Engineering SIMATS India

Splicing systems was first proposed by Head on organic considerations to demonstrate indubitable chimeric behavior of DNA particles and are of current intrigue and study. In this paper, we study some of the chomskian hierarchy of array grammars namely (Regular:Regular)array grammar,(Context Free:Regular)array grammar and (Regular:Context Free)array grammar using H-array system. The Array rewriting rules is limited to extent by the action of row and column splicing.

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Self-Awareness for Autonomous Systems

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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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Recent progress and trends in predictive visual analytics

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Frontiers of computer science 2017年第2期11卷 192-207页

作者： Junhua LU Wei CHEN Yuxin MA Junming KE Zongzhuang LI Fan ZHANG Ross MACIEJEWSKI State Key Lab of Computer Aided Design and Computer Graphics Zhejiang University Hangzhou 310058 China College of Science Zhejiang University of Technology Hangzhou 310023 China College of Computer Science and Technology Zhejiang University of Technology Hangzhou 310023 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287-8809 USA

A wide variety of predictive analytics techniques have been developed in statistics, machine learning and data mining; however, many of these algorithms take a black-box approach in which data is input and future predictions are output with no insight into what goes on during the process. Unfortunately, such a closed system approach often leaves little room for injecting domain expertise and can result in frustration from analysts when results seem snurious or confusing. In order to allow for more human-centric approaches, the visualization community has begun developing methods to enable users to incorporate expert knowledge into the pre- diction process at all stages, including data cleaning, feature selection, model building and model validation. This paper surveys current progress and trends in predictive visual ana- lytics, identifies the common framework in which predictive visual analytics systems operate, and develops a summariza- tion of the predictive analytics workfiow.

关键词： predictive visual analytics visualization visual analytics data mining predictive analysis

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Coordinate Access System for Live Video Acquisition

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Journal of Physics: Conference Series 2020年第1期1712卷

作者： B. Annapurna T Rama Reddy Ch. V. Raghavendran Raushan Kumar Singh Vedurai Veera Prasad Associate Professor Department of Computer Science and Engineering Aditya College of Engineering Surampalem East Godavari Dt. AP India. Professor Department of Computer Science and Engineering Aditya Engineering College (A) Surampalem East Godavari Dt. AP India Professor Department of Information Technology Aditya College of Engineering and Technology Surampalem East Godavari Dt. AP India Technical Director Spectrum Solutions Pondicherry India Assistant Professor Department of Computer Science and Engineering Aditya College of Engineering Surampalem East Godavari Dt. AP India.

Biometric systems are the most advanced access technology developed so far in the 21st century. It does not even require to carry key cards or passwords in mind. Today most of the commercial and private entries are protected by biometric recognition systems like fingerprint scans facial recognition, retina scans, voice matching, etc. Even our phones, laptops, and daily access devices are equipped with biometric systems. In banks, the PCs are secured by the combination of passwords and fingerprint scans. Biometric scans are considered the most secure access technology so far. Our paper is to examine whether they are secure? Should we rely on them with our hard-earned money and social identity? Is there any way we can use these services without actually compromising our data and security? Our observation is on our digital identity. Promoting digitization in every department brings our topic in the picture. All our information is saved in our phones, our daily routine, whom we talk, what we purchase, whom we chat, where we travel, etc. Almost every smartphone has biometric fingerprint locks which means our phones have our fingerprint scans in database and with internet blend it's tethered worldwide. Our fingerprints are connected to our bank accounts, PAN Cards, Passport, and SIM Cards using Aadhar Cards. If someone has our fingerprint they can easily reach our Aadhar Card and through that to all our personal information. Most of the phone companies are Chinese, Korean, German, and American. As per their country policies, they must share their data with the governing authorities. We aim to create a security system without actually using the biometric scans. The system is an advancement of the biometric system but with better accuracy and intelligence. We interface image acquisition tools to live track the red color things. The web camera or inbuilt system lens can be used as the acquisition system. When the red color object is moved in front of the lens it shows the co

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