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IEEE Global Communications Conference

作者： Toan-Van Nguyen Tri-Nhu Do Vo Nguyen Quoc Bao Daniel Benevides da Costa Beongku An Dept. of Electronics and Computer Engineering in Graduate School Hongik University Republic of Korea Dept. of Computer Science University of Texas Dallas TX USA Faculty of Telecommunications Posts and Telecommunications Institute of Technology Vietnam Dept. of Computer Engineering Federal University of Cear Sobral CE Brazil Dept. of Software and Communications Engineering Hongik University Republic of Korea

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

This paper studies the performance of multi-hop cognitive wireless powered communication networks (WPCNs), where secondary nodes can harvest energy from multiple dedicated power beacons and access spectrum of primary receivers (PRs) to support data transmission. Specifically, we consider a practical scenario of cognitive WPCNs, where the channel state information (CSI) of interference links is assumed to be imperfect. To improve the network performance, we propose dual-hop scheduling scheme (DHS) for multi-hop network, where two best relays in two consecutive clusters are selected for data transmission. We then analyze the performance of the proposed scheme in terms of outage probability and outage floor. Numerical results show that DHS scheme outperforms random scheduling scheme, arising as an efficient scheme for multi-hop transmission. Furthermore, the effects of the number of hops, number of power beacons, and time switching ratio on multi-hop cognitive WPCNs are evaluated and discussed.

关键词： Relays Spread spectrum communication Interference Power system reliability Probability Data communication Switches

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Spectral Efficiency Maximization for Multiuser MISO-NOMA Downlink Systems with SWIPT

Spectral Efficiency Maximization for Multiuser MISO-NOMA Dow...

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IEEE Global Communications Conference

作者： Toan-Van Nguyen Van-Dinh Nguyen Tri-Nhu Do Daniel Benevides da Costa Beongku An Dept. of Electronics and Computer Engineering Graduate School Hongik University Republic of Korea Dept. of ICMC Convergence Technology Soongsil University Seoul Republic of Korea Dept. of Computer Science University of Texas at Dallas TX USA Dept. of Computer Engineering Federal University of Cear Sobral CE Brazil Dept. of Software and Communications Engineering Hongik University Republic of Korea

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

In this paper, we study the problem of jointly optimizing user pairing and beamforming design in multiuser multiple-input single-output (MU-MISO) non-orthogonal multiple access (NOMA) downlink systems with simultaneous wireless information and power transfer (SWIPT). Aiming at maximizing the achievable sum throughput subject to energy harvesting (EH) constraints, we propose a hybrid user pairing beamforming scheme (HBS), where two users with distinct channel conditions are optimally selected to perform user pairing. Moreover, we adopt a non-linear EH model for energy users to reveal their practical circuit characteristics. The sum throughput problem is formulated as a class of mixed-integer nonconvex optimization programming which is computationally prohibitive. To solve this challenging problem, we propose a low-complexity iterative algorithm, yet efficient, based on sequential convex approximation method to arrive at least the local optima. Numerical results are provided to demonstrate the performance improvement of the proposed HBS scheme over the multiuser beamforming one without user pairing, revealing to be an effective scheme for MU-MISO-NOMA downlink systems.

关键词： Array signal processing NOMA Interference Signal to noise ratio Downlink Throughput Integrated circuit modeling

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Data-Intensive Routing in Delay-Tolerant Networks

Data-Intensive Routing in Delay-Tolerant Networks

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Kazuya Sakai Min-Te Sun Wei-Shinn Ku Dept. of Electrical Eng. and Comput. Sci. Tokyo Metropolitan University 6-6 Asahigaoka Hino Tokyo Japan Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan Department of Computer Science and Software Engineering Auburn University Auburn Alabama

Mobile users and wireless devices are now the sources of a large volume of data. In such data-intensive mobile and wireless computing systems, delay-tolerant network (DTN) routing plays a critical role in data routing, dissemination, and collection. In this paper, we first introduce a new routing problem in DTNs - data-intensive routing - where data transmitted from one node to another is very large with respect to the size of data which can be transmitted in a single contact and available buffer size at relay nodes. In the proposed opportunistic path model, the contact frequency, contact duration, and buffer constraint are all integrated into a single routing metric. Then, we design the data-intensive routing (DIR) protocol where the path with the highest bottleneck link capacity is defined as the path weight. In addition, we propose the advanced DIR (A-DIR) protocol which focuses on the probability that the last message block will be delivered to its destination within the time constraint. Both the DIR and A-DIR protocols forward messages to better relays or to their destinations based on a greedy strategy with the proposed path metric. Simulations using real mobility traces demonstrate that the proposed DIR and A-DIR protocols achieve their design goals.

关键词： Routing Routing protocols Relays Measurement Wireless communication Buffer storage

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The Effect of Cybersickness of an Immersive Wheelchair Simulator

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Procedia computer science 2019年 160卷 665-670页

作者： Débora P. Salgado Thiago B. Rodrigues Felipe R. Martins Eduardo L.M. Naves Ronan Flynn Niall Murray Assistive Technology Lab Faculty of Electrical Engineering“ Federal University of Uberlandia Uberlandia MG 38400-902 Brazil Dept. of Computer Science & Software Engineering Athlone Institute of Technology Athlone Co. Westmeath N37 HD68 Ireland

A key challenge that Immersive applications have to overcome is cybersickness. Cybersickness is particularly prevalent in dynamic applications such as vehicles simulators. The work presented here aims to understand the cause of cybersickness symptoms in an assistive technology (AT) application, the virtual wheelchair training simulator. This evaluation is performed in terms of errors made during experience and post-experience Simulator Sickness Questionnaire (SSQ). The performance metrics analyzed are time to complete the proposal task and number of collisions (errors/mistakes). The post-experience questionnaires (subjective measurements) collected the user’s experience in terms of simulator sickness by applying the Simulator Sickness Questionnaire (SSQ) and immersion questions. The experiments were conducted with 10 participants. In terms of results, analysis of human factors reveals that the average cybersickness score is slightly higher for women compared to men. However, these differences were not statistically significant. There was an inverse correlation between cybersickness symptoms and task performance as well as between cybersickness symptoms and immersion.

关键词： Cybersickness Immersive Technologies Wheelchair Simulator Assistive Technologies

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State-of-the-art genomic data compression technology 10

State-of-the-art genomic data compression technology

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10th International Conference on Bioinformatics and Computational Biology, BICOB 2018

作者： Li, Dunling Chang, Lin-Ching BTS Software Solutions ColumbiaMD United States Dept. of Electrical Engineering and Computer Science Catholic University of America WashingtonDC United States

ISBN: (纸本)9781943436118

The demand for efficient genomic data storage and distribution has increased substantially as advanced high-throughput sequencing has dramatically reduced costs and processing time required for genomic data collection. However, these advances generate a new challenge with data storage, transmission, and manipulation. To wit, the sizes of genomic databases are often very huge;for example, the genomic data in Cancer Genome Atlas database is over 2.5 petabytes (2.5 million gigabytes). Data compression would be the key to meet the technical and cost challenges of genomic data storage, transmission, and access for analysis. Recently, there has been growing interest in developing high-performance compression tools designed specifically for genomic data. This paper provides an overview of state-of-the-art genomic data compression technology, the commonly used tools, and their performance. © 2018 ISCA, BICOB.

关键词： Genome

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Fair and autonomous sharing of federate learning models in mobile Internet of Things

arXiv

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arXiv 2020年

作者： Hao, Xiaohan Ren, Wei Xiong, Ruoting Zheng, Xianghan Zhu, Tianqing Xiong, Neal N. School of Computer Science China University of Geoscience Wuhan China Guangxi Key Laboratory of Cryptography and Information Security Guilin541004 China Key Laboratory of Network Assessment Technology CAS Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Mingbyte Technology QingDao China School of Software University of Technology Sydney UltimoNSW2007 Australia Dept. of Mathematics and Computer Science Northeastern State University United States

Federate learning can conduct machine learning as well as protect the privacy of self-owned training data on corresponding ends, instead of having to upload to a central trusted data aggregation server. In mobile scenarios, a centralized trusted server may not be existing, and even though it exists, the delay will not be manageable, e.g., smart driving cars. Thus, mobile federate learning at the edge with privacy-awareness is attracted more and more attentions. It then imposes a problem - after data are trained on a mobile terminal to obtain a learned model, how to share the model parameters among others to create more accurate and robust accumulative final model. This kind of model sharing confronts several challenges, e.g., the sharing must be conducted without a third trusted party (autonomously), and the sharing must be fair as model training (by training data)is valuable. To tackle the above challenges, we propose a smart contract and IPFS (Inter-Planetary File System) based model sharing protocol and algorithms to address the challenges. The proposed protocol does not rely on a trusted third party, where individual-learned models are shared/stored in corresponding ends. Conducted through extensive experiments, three main steps of the proposed protocol are evaluated. The average executive time of the three steps are 0.059s, 0.060s and 0.032s, demonstrating its efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： Smart contract

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Tethered Balloon Technology for Green Communication in Smart Cities and Healthy Environment 1

Tethered Balloon Technology for Green Communication in Smart...

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1st International Conference of Intelligent Computing and engineering, ICOICE 2019

作者： Alsamhi, S.H. Mohsen Aljabali, Hasan Najim, Mohd Srivastava, Ashutosh Samar Ansari, Mohd Zhao, Liang Nguyen Van, Sau Gupta, S.K. Alammari, Amr A. Hatem Saber, Akram Hebah, Mohammed Y.A.M. Ahmed Abdullah Alasali, Marwan IBB University Yemen and Aligarh Muslim University Dept. of Electronics Engineering Ibb Yemen Aligarh Muslim University Department of Electrical Engineering Aligarh India University of Jaddah Department of Electrical and Electronics Engineering Jaddah Saudi Arabia Department of Electrical Engineering Varanasi India Software Research Institute Athlone Institute of Technology Athlone Ireland School of Computer Science Shenyang Aerospace University Shenyang China Biomedical of Information Technology Shenzhen Insitutes of Advanced Technology UCAS Shenzhen China School of Electronics and Communication Engineering Shri Mata Vaishno Devi University Katra India

ISBN: (纸本)9781728144870

The development and adopting of advanced communication technologies provide mobile users more convenience to connect any wireless network anytime and anywhere. Therefore, a large number of base stations (BS) are demanded keeping users connectivity, enhancing network capacity, and guarantee a sustained users Quality of Experiences (QoS). However, increasing the number of BS leads to an increase in the ecological ad radiation hazards. In order to green communication, many factors should be taken into consideration, i.e., saving energy, guarantee QoS, and reducing pollution hazards. Therefore, we propose tethered balloon technology that can replace a large number of BS and reduce ecological and radiation hazards due to its high altitude and feasible green and healthy broadband communication. The main contribution of this paper is to deploy tethered balloon technology at different altitude and measure the power density. Furthermore, we evaluate the measurement of power density from different height of tethered balloon comparison with traditional wireless communication technologies. The simulation results showed that tethered balloon technology can deliver green communication effectively and efficiently without any hazardous impacts. © 2019 IEEE.

关键词： Smart city

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Performance Evaluation of Parallel Particle Swarm Optimization for Multicore Environment

Performance Evaluation of Parallel Particle Swarm Optimizati...

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2018 International Conference on Advanced science and engineering, ICOASE 2018

作者： Abdullah, Eman Abdulaziz Ahmed Saleh, Ibrahim Al Saif, Omar Ibrahim Computer Science Dept. Mosul University Mosul Iraq Dept. of Software Engineering Mosul University Mosul Iraq Technical Institute in Mosul Northern Technical University Mosul Iraq

ISBN: (纸本)9781538666968

Particle swarm optimization (PSO) has become universal due to its simplicity and effectiveness in solving many problems in various applications with low computational cost. This algorithm consumes time as dealing with large tasks programs. The main goal of this paper is to introduce a parallel particle swarm optimization (PPSO) on multi-core processing kernel to decrease the determination. In order to ease transfer information among particles of shared area and exchange information by switching randomly. Most of serial PSO algorithms allow updating information among particles which takes a long time during the implementation period. The algorithm was applied to the standard optimization test set CEC (Congress on Evolutionary Computation) 2014 and gave good results compared to the previous algorithm. The empirical results show the execution time of Shared-PSO is more efficient than the serial PSO's. The proposed algorithm using a multicore CPU technique to improve it via parallelization and enhanced the efficiency of an algorithm by increase the range of PSO application. © 2018 IEEE.

关键词： Particle swarm optimization (PSO)

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Analyzing Various Machine Learning Algorithms for the Classification of Malwares

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IOP Conference Series: Materials science and engineering 2020年第1期993卷

作者： J Pavithra J S Femilda Josephin School of Computing Dept of Computer Science and Engineering SRM Institute of Science and Technology SRM University Kattankulathur-603203 Chennai India School of Computing Dept of Software Engineering SRM Institute of Science and Technology SRM University Kattankulathur-603203 Chennai India

Malware, brief for Malicious software, is increasing continuously in amounts and sophistication as our digital world continues to develop. Lately, tools for forming malware have been increasing rapidly on the internet, making it more accessible for people without expertise to create malware. Towards the end, the number of malware is growing fast. To deal with the problem, it is necessary to classify malware instantly and accurately. These malware programs play a role such as encrypting or destroying sensible data, stealing, changing or capturing main computing functions, controlling users and perform computer activity without their consent. In this paper, six different algorithms for classification like Linear Regression, Random Forest, Adaboost, Gaussian, Gradient Boosting, Decision Tree has been used for classifying a file as malicious or benign. Based on the results, the Random forest attained 99.43% accuracy and infers that it is suitable for malware prediction.

关键词：

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Qualitative Findings from an Online Course on Machine Learning

Qualitative Findings from an Online Course on Machine Learni...

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Frontiers in Education (FIE) Conference

作者： Steve Chenoweth Panagiotis K. Linos Computer Science & Software Engineering Dept. Rose-Hulman Institute of Technology Terra Haute Indiana Computer Science & Software Engineering Dept. Butler University Indianapolis Indiana

ISBN: (纸本)9781538611753;9781538611746

This is a full paper in the Innovate Practice category. It reports experiences while teaching a largely online course about Machine Learning at two separate Universities. We targeted our course for a much wider than usual audience -- as “computer science (CS) for All,” with undergraduate non-CS majors learning the same material alongside CS majors. We discuss why the majority of the students appreciated the flexibility of online classes designed for this wide group, and how they welcomed the opportunity to learn together about a “hot” topic such as Machine Learning. We explain our handling of challenges coordinating diverse and remote teams working with realistic big data of their own interest. Moreover, we describe how we engaged students in stimulating discussions about their readings and team projects, and how we balanced keeping everyone on the same pace while providing opportunities for learning ahead. Finally, we explain how we were able to attract the non-CS majors to take a CS special topics course and how we plan to use their constructive suggestions to improve future offerings of this course.

关键词： Education Machine learning software Programming profession software engineering

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