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17th International Conference on Advances in ICT for Emerging Regions, ICTer 2017

作者： Manisha, U.K.D.N. Liyanage, S.R. Department of Computer Systems Engineering Faculty of Computing and Technology University of Kelaniya Kelaniya Sri Lanka Department of Software Engineering Faculty of Computing and Technology University of Kelaniya Kelaniya Sri Lanka

ISBN: (纸本)9781538624432

This paper proposes a system that is capable of detecting, recognizing and indicating traffic signs to the driver to provide a safe and convenient driving experience. The system is composed of three phases;image pre-processing phase, detection phase and recognition phase. Image pre-processing phase deals with image segmentation that is employed to enhance the images to obtain clearer information under variable lighting conditions. During the detection phase, the objective is to find traffic signs in the input image frames and to return the regional coordinates of detected signs. In order to detect traffic signs, a cascade classifier was trained to analyse the frame and to detect signs in each frame. In the recognition phase, a multiclass support vector machine image category classifier was trained to recognize and alert the driver. The system comprised of these phases is capable of detecting, recognizing and alerting traffic signs with 98.6% accuracy while the vehicle is moving at a speed in the range of 40-45 km/h. © 2017 IEEE.

关键词： computer vision

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Predicting Churn: How Multilayer Perceptron Method Can Help with Customer Retention in Telecom Industry

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IOP Conference Series: Materials Science and engineering 2020年第1期864卷

作者： NNA Sjarif NF Azmi HM Sarkan SM Sam MZ Osman Advanced Informatics Department Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia Jalan Sultan Yahya Petra 54100 Kuala Lumpur Malaysia Soft Computing Research & Intelligent System Group (SPINT) Faculty of Systems Computer & Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak 26300 Gambang Pahang Malaysia

Customer churn prediction has been used widely in various kind of domain especially subscription-basis industries. With the rapid growth of telecommunication industry over the last decade, this industry not only focuses on providing numerous products, but also satisfying the customers as it is one of the key solutions to remain competitive. This research proposed MultiLayer Perceptron Method for churn prediction. The evaluation is compared with three classifiers which includes are Support Vector Machine, Naïve Bayes and Decision Tree in term of several aspects. In preprocessing phase, we employed Principal Component Analysis and normalization to find the correlation among all the variables. For the postprocessing, InfoGainAttribute is used to identify the highest factor attribute that leads to customer retention. It is found that MultiLayer Perceptron outperforms other classifiers and international plan plays important role to retain customer from leaving organization.

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Preface

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CEUR Workshop Proceedings 2022年 3304卷

作者： Jia, Weijia Yin, Jian Hu, Shaolin Peng, Shaoliang Niu, Shaozhang Srinivasa Rao, P.C. Lu, Yao Mirsaeidi, Sohrab Cao, Bin Wu, Yilin Wang, Xingbo Subramaniyam, Kannimuthu Boddu, Raja Sarath Kumar Li, Zhonghua Tao, Qian Zhang, Lei Li, Yi Ding, Deqing Wang, Dahan Zhang, Ziyan AlShawabkeh, Mahmoud Aslam, Muhammad Dib, Omar Sahibuddin, Shamsul Bin Wagh, Sanjeev J. Pardalos, Panos M. Al-Sammarraie, Najeeb Abbas Liu, Linfeng Kong, Jin-Heung Borrego, Carlos Tahir, Sabeen Wu, Zhiheng Li, Jiongcheng Xu, Yong Xie, Zhi Wang, Jiahai Cai, Hongmin Yang, Yuedong Qin, Xiaolin Beijing Normal University Zhuhai China Sun Yat-sen University China Guangdong University of Petrochemical Technology China Hunan University China Beijing University of Posts and Telecommunications China India Beijing Jiaotong University China Hebei University of Technology China Guangdong University of Education China Foshan University China Karpagam College of Engineering India Lenora College of Engineerin India Yat-sen University Guangdong High Performance Computing Society China South China University of Technology China Henan University China Wenzhou University China National University of Defense Technology China Xiamen University of Technology China Hainan Tropical Ocean University China Guangxi Normal University for Nationalities China Wuhan University China Wenzhou-Kean University China School of Software Engineering Universiti Teknologi Malaysia Information Technology Government College of Engineering Karad India Department of Industrial & Systems Engineering University of Florida United States Al-Madinah International University Faculty of Computer and Information Technology Malaysia School of Computer Science and Technology Nanjing University of Posts and Telecommunications China School of Computer and Information Engineering Kwangwoon University Korea Republic of Departament Enginyeria of Information Comunicacions Autonomous University of Barcelona Spain Information Technology Department King AbdulAziz University Jeddah Saudi Arabia Institute of Manufacturing GDAS China Guangdong Planning and Designing Institute of Telecommunications Co. Ltd China Guangzhou Institutes of Biomedicine and Health Chinese Academy of Sciences China Cheng Du Information Technology of Chinese Academy of Sciences Co. Ltd China

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Radiation Assurance of CubeSat Payloads Using Bayesian Networks and Fault Models

Radiation Assurance of CubeSat Payloads Using Bayesian Netwo...

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2018 Annual Reliability and Maintainability Symposium, RAMS 2018

作者： Austin, Rebekah A. Mahadevan, Nagabhushan Witulski, Arthur F. Evans, John Witulseki, Arthur F. Vanderbilt University NashvilleTN37235 United States Institute for Software Integrated Systems Department of Electrical Engineering and Computer Science Vanderbilt University 1025 16th Av. South Suite 102 NashvilleTN37212 United States Institute of Space and Defense Electronics Department of Electrical Engineering and Computer Science Vanderbilt University 1025 16th Avenue South Suite 200 NashvilleTN37212 United States Office of Safety and Mission Assurance NASA 300 E St SW WashingtonDC20546 United States

ISBN: (纸本)9781538628706

Commercial off-the-shelf (COTS) electronics are used in satellites that span the size, cost, and acceptable risk spectrum. At one extreme the CubeSat, a platform originally created for university-based spacecraft design, is often constructed only from COTS electronics. At the other extreme, even high-budget NASA spacecraft use COTS electronics in non-mission critical circuits, especially when no radiation-hardened alternatives exist or the radiation-hardened parts do not meet the system requirements. There is significant uncertainty in the radiation test results of COTS electronics;hence additional means of assessing risk and radiation hardness are needed. In this work we construct a fault-propagation model of a CubeSat payload in a SysML platform, and then develop a Bayesian network from the fault model of the system. The sensitivity of the system to variations in component radiation response can be evaluated quantitatively, within the limits of the assumptions and available data. This sensitivity study then informs the structure and content of the overall radiation-reliability assurance case. © 2018 IEEE.

关键词： Bayesian networks

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Towards a standardization for simulation scenario development in aviation - Panel discussion

Towards a standardization for simulation scenario developmen...

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AIAA Modeling and Simulation Technologies Conference, 2018

作者： Durak, Umut Jafer, Shafagh Beard, Steven D. Reardon, Scott Murphy, James R. Crider, Dennis A. Gerretsen, Arno Lenz, Helge Macchiarella, Nickolas D. Rigby, Kevin T. Torens, Christoph Adolf, Florian-Michael Institute of Flight Systems Braunschweig38108 Germany Embry-Riddle Aeronautical University Daytona BeachFL32114-3900 United States NASA Ames Research Center Moffett Field CA94035 United States National Transportation Safety Board Washington DC20594 United States Amsterdam Netherlands Flight Dynamics and Simulation Department of Electrical Computer Software and Systems Engineering Aerospace Simulation Research and Development Branch Aviation Systems Division Vehicle Simulation Aerospace Operations Operator Performance Training and Simulation Aeronautical Sciences

ISBN: (数字)9781624105289

ISBN: (纸本)9781624105289

Aviation industry is characterized by its broad utilization of modeling and simulation starting from concept demonstration to operator training. Scenario development is an important aspect of any simulation study, however, the community is still lacking of a common understanding and standardized practices. This leads to degraded interoperability and shareability. The American Institute of Aeronautics and Astronautics (AIAA) Modeling and Simulation Technical Committee (MSTC) is recently trying to create a synergy towards development of a standard scenario definition language for aviation by conducting sessions and panel discussions in conferences and launching a working group. This paper presents the recap of the panel discussion that has been carried out as a part of the invited session "Aviation Simulation Scenario Development" in AIAA Modeling and Simulation Technologies Conference of Scitech 2017. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Aviation

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Social-feature enabled communications among devices towards smart IoT community

arXiv

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arXiv 2018年

作者： Du, Qinghe Song, Houbing Zhu, Xuejie Department of Information and Communications Engineering Xi'An Jiaotong University China Shaanxi Smart Networks and Ubiquitous Access Research Center Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

Future IoT is expected to get ubiquitous connection and access in a global scale. In the meantime, with the empowered communications capability for IoT devices, IoT will evolve to be highly autonomous, even under the help from infrastructure, and thus will gradually establish the smart IoT community. One of the major challenges imposed on the smart IoT communities is the socialization of IoT communications, because massive IoT accesses make centralized control very hard and also face the shortage of spectrum resources. Towards these issues, we in this article first present the overview and discussions on social features affecting connections among devices. Then, we motivate studies on the statistical characteristics of social features for connections among devices towards smart IoT. We further propose the queuing model under unified asymptotic analyses framework to characterize the statistical social features, with emphases on typical social metrics such as credit, reputation, centrality, etc. How to apply these features for network optimization is further suggested. Finally, we share our opinion on the open problems of social-aware design towards future smart IoT. Copyright © 2018, The Authors. All rights reserved.

关键词： Internet of things

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Dynamical Sampling with Additive Random Noise

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Sampling Theory, Signal Processing, and Data Analysis 2018年第2期17卷 153-182页

作者： Akram Aldroubi Longxiu Huang Ilya Krishtal Akos Ledeczi Roy R. Lederman Peter Volgyesi Department of Mathematics Vanderbilt University Nashville USA Department of Mathematics Northern Illinois University DeKalb USA Department of Electrical Engineering and Computer Science Vanderbilt University Nashville USA Department of Statistics and Data Science Yale University New Haven USA Institute for Software Integrated Systems Vanderbilt University Nashville USA

Dynamical sampling deals with signals that evolve in time under the action of a linear operator. The purpose of the present paper is to analyze the performance of the basic dynamical sampling algorithms in the finite dimensional case and study the impact of additive noise. The algorithms are implemented and tested on synthetic and real data sets, and denoising techniques are integrated to mitigate the effect of the noise. We also develop theoretical and numerical results that validate the algorithm for recovering the driving operators, which are defined via a real symmetric convolution.

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Preface

Lecture Notes of the Institute for Computer Sciences, Social...

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Lecture Notes of the Institute for computer Sciences, Social-Informatics and Telecommunications engineering, LNICST 2019年 295 LNICST卷 v页

作者： Song, Houbing Fang, Yuguang Jiang, Dingde Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL United States School of Astronautics Aeronautics UESTC Chengdu China

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A Flexible Keyphrase Extraction Technique for Academic Literature

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Procedia computer Science 2018年 135卷 553-563页

作者： Gollam Rabby Saiful Azad “ Mufti Mahmud Kamal Z. Zamli Mohammed Mostafizur Rahman Faculty of Computer Systems & Software Engineering University Malaysia Pahang Gambang Kuantan Malaysia IBM Centre of Excellence Gambang Kuantan Malaysia Department of Computing and Technology Nottingham Trent University Nottingham United Kingdom Department of Mathematics American International University - Bangladesh (AIUB) Dhaka Bangladesh

A keyphrase extraction technique endeavors to extract quality keyphrases from a given document, which provide a high-level summary of that document. Except statistical keyphrase extraction approaches, all other approaches are either domain-dependent or require a sufficient amount of training data, which are rare at present. Therefore, in this paper, a new tree-based automatic keyphrase extraction technique is proposed, which is domain-independent and employs nominal statistical knowledge; but no train data are required. The proposed technique extracts a quality keyphrase through forming a tree from a candidate keyphrase; and later, it is expanded or shrunk or remained in the same state depending on other similar candidate keyphrases. At the end, keyphrases are extracted from the resultant trees based on a value, µ (which is the Maturity Index (MI) of a node in the tree), which enables flexibility in this process. A small µ value would yield many and/or lengthy keyphrases (greedy approach); whereas, a large µ value would yield lower and/or abbreviated keyphrases (conservative approach). Thereby, a user can extract his/her desired-level of keyphrases through tuning µ value. The effectiveness of the proposed technique is evaluated on an actual corpus, and compared with Rapid Automatic Keyphrase Extraction (RAKE) technique.

关键词： Candidate keyphrase keyphrase automatic keyphrase extraction technique tree data structure

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Using Sparse Matrices to Prevent Information Leakage in Cloud Computing

Using Sparse Matrices to Prevent Information Leakage in Clou...

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International Conference on Future Internet of Things and Cloud (FiCloud)

作者： Khaled Khan Mahboob Shaheen Yongge Wang Computer Science and Engineering KINDI Computing Lab Qatar University Qatar Department of Math and Physics North South University Dhaka Bangladesh Software and Information Systems University of North Carolina Charlotte USA

ISBN: (纸本)9781538675045

Cloud computing represents the promise of outsourcing of scientific computing such as matrix multiplication. However, this can introduce new vulnerabilities such as information leakage. Cloud server intentionally or unintentionally may reveal sensitive input matrices of the client as well as multiplication results to unauthorised entities. In this paper, we propose two protocols that use sparse matrices to prevent information leakage in outsourcing matrix multiplications to cloud computing without encryption. The protocols are considered lightweight compared to other comparable approaches. We also provide a running example to demonstrate how the protocols ensure no information leakage of client data.

关键词： Sparse matrices Cloud computing Servers Protocols Encryption software

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