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10th International Symposium on Next Generation Electronics, ISNE 2022

作者： Rong, Zhao Zhang, Lining Chan, Mansun Hong Kong University of Science and Technology Ai Chip Center for Emerging Smart Systems InnoHK Centers Hksp Department of Ece Hong Kong Hong Kong Peking University Shenzhen Graduate School School of Electronic and Computer Engineering Shenzhen China

ISBN: (纸本)9781665455251

In this work, a methodology for developing a memory compact model is described using recurrent neural network (RNN). Compared to traditional modeling approaches, it is flexible and able to develop an accurate model based on physical data before the material physics is fully understood. A simple ReRAM-type memory model is demonstrated using Nonlinear Autoregressive with External Input (NARX) machine learning approach. To enable the neural network to capture the resistive switching characteristics of ReRAM, the output at a range of cycling voltages was captured and used as training data. The trained model is used for DC prediction under different voltage amplitudes, and the prediction results are consistent with the physical data, with MSE values below 10-9 . The accuracy of the RNN-assisted ReRAM model during the read, write and erase operations is also evaluated to show the validity of the approach. The calibration between the prediction results of the model and experimental data further proves the feasibility of the approach. © 2023 IEEE.

关键词： Recurrent neural networks

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Toward Parallelization Technique for Stream-based Lossless Data Compression

Toward Parallelization Technique for Stream-based Lossless D...

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IEEE International Conference on Big Data

作者： Taiki Kato Shinichi Yamagiwa Koichi Wada Master’s Program in Computer Science Degree Program in Systems and Information Engineering University of Tsukuba Tsukuba Ibalaki Japan Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Ibalaki Japan

IoT edge platform has become popular in various distributed environments. The edge devices need to communicate BigData among them or with the cloud servers by collaborating with AI technologies for finding events from the applications. Those devices exchange data streams from such as distributed sensors and remote image/video devices. We focus on an acceleration technique for the communication performance using a stream-based lossless data compression technology. This paper proposes a parallelization technique for the compression process in a software environment running on a multicore processor. The technique invokes concurrent compression processes assigned to multiple threads with splitting a data stream to chunks. The paper exposes three scheduling methods for assigning the chunks to the threads: in-order, hybrid and out-of-order. As an original data order of chunks must be obtained in decompression side, the proposed technique introduces packeting mechanisms in each chunk by adding headers to support the scheduling methods. Through experimental performance evaluations, we discuss the packeting overhead focusing on compression ratio and speedup by the parallelization with three scheduling methods.

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Control and Data Integrity are Important Factors of Data Governance Technology

Control and Data Integrity are Important Factors of Data Gov...

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International Conference on ICT For Smart Society (ICISS)

作者： Yakob Utama Chandra Harjanto Prabowo Ford Lumban Gaol Betty Purwandari Information Systems Department BINUS Graduate Program Doctor of Computer Science School of Information Systems Bina Nusantara University Jakarta Indonesia Management Department Doctor of Research Management BINUS Business School Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Depok Indonesia

The proliferation of data has become an inevitable consequence of the digital age as individuals across all domains increasingly rely on data for various purposes. Both companies and governments have a significant need for data. However, the sheer volume and complexity of this data, along with the potential risks associated with mishandling it, necessitate the establishment of a framework known as data governance. The primary objective of this research paper is to examine the factors that contribute to the effective implementation and utilization of Data governance. This study employs qualitative methods and adopts a systematic literature review approach to address the research inquiry: “What are the important factors that determine the utilization of data governance technology?” Through the systematic literature review, a total of 41 key factors were identified from 20 research literatures that have been found to significantly impact the effective implementation of data governance. There are thirteen primary technological factors that hold significance in the realm of data governance. These factors encompass technology, application and use, storage of data, sharing, archiving, and preservation, big data algorithmic systems, data flow, deletion, diversity of data, mechanisms, size of data, control, and data integrity.

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Reconfiguration of vertex-disjoint shortest paths on graphs

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Journal of Graph Algorithms and Applications 2024年第3期28卷 87-101页

作者： Saito, Rin Eto, Hiroshi Ito, Takehiro Uehara, Ryuhei Graduate School of Information Sciences Tohoku University Sendai Japan School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan School of Information Science Japan Advanced Institute of Science and Technology Nomi Japan

We introduce and study reconfiguration problems for (internally) vertex-disjoint shortest paths: Given two tuples of internally vertex-disjoint shortest paths for fixed terminal pairs in an unweighted graph, we are asked to determine whether one tuple can be transformed into the other by exchanging a single vertex of one shortest path in the tuple at a time, so that all intermediate results remain tuples of internally vertex-disjoint shortest paths. We also study the shortest variant of the problem, that is, we wish to minimize the number of vertex-exchange steps required for such a transformation, if exists. These problems generalize the well-studied Shortest Path Reconfiguration problem. In this paper, we analyze the complexity of these problems from the viewpoint of graph classes, and give some interesting contrast. © 2024, Brown University. All rights reserved.

关键词： Graph theory

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The effect of visual advanced driver assistance systems on a following human driver in a mixed-traffic condition

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Procedia computer science 2023年 216卷 221-229页

作者： Dedy Ariansyah Bens Pardamean Giandomenico Caruso Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Department of Mechanical Engineering Politecnico di Milano Milan 20156 Italy

Rapid development in vehicular technology has caused more automated vehicle control to increase on the roads. Studies showed that driving in mixed traffic with an autonomous vehicle (AV) had a negative impact on the time headway (THW) of conventional vehicles (CVs) (i.e., driven by humans). To address this issue, there is a need to equip CV with visual advanced driver assistance systems (ADASs) that helps the driver maintain safe headway when driving near AVs. This study examines the perception of drivers using visual ADAS and their associated risk while driving behind the AV at constant and varying speeds. The preliminary results showed that while visual ADAS could help drivers keep the safe THW, it could affect drivers’ ability to react to emergencies. This implies that visual modality alone might not be sufficient and therefore requires some other feedback or intelligent transport systems to help drivers maintain safe driving in a mixed-traffic condition.

关键词： sustainable transport management platooning car-following visual advanced driver assistance system virtual realtiy

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A Constructive Heuristic for the Uniform Capacitated Vertex k-center Problem

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ACM Journal of Experimental Algorithmics 2023年第2期28卷 1-26页

作者： Cornejo-Acosta, José Alejandro García-Díaz, Jesús Pérez-Sansalvador, Julio César Ríos-Mercado, Roger Z. Pomares-Hernández, Saúl Eduardo Instituto Nacional de Astrofísica Óptica y Electrónica Computer Science Department Puebla72840 Mexico Tecnológico Nacional de México/ITS de Purísima Del Rincón Computer Engineering Department Guanajuato36425 Mexico Consejo Nacional de Humanidades Ciencias y Tecnologías Mexico City03940 Mexico Universidad Autónoma de Nuevo León Graduate Program in Systems Engineering San Nicolás de los GarzaNL 66455 Mexico LAAS-CNRS Université de Toulouse France INSA ToulouseF31400 France

The uniform capacitated vertex k-center problem is an -hard combinatorial optimization problem that models real situations where k centers can only attend a maximum number of customers, and the travel time or distance from the customers to their assigned center has to be minimized. This article introduces a polynomial-time constructive heuristic algorithm that exploits the relationship between this problem and the minimum capacitated dominating set problem. The proposed heuristic is based on the one-hop farthest-first heuristic that has proven effective for the uncapacitated version of the problem. We carried out different empirical evaluations of the proposed heuristic, including an analysis of the effect of a parallel implementation of the algorithm, which significantly improved the running time for relatively large instances. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Travel time

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Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space

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Procedia computer science 2023年 227卷 1046-1053页

作者： Fergianto E. Gunawan Arief S. Budiman Bens Pardamean Endang Juana Sugiarto Romeli Tjeng W. Cenggoro Kartika Purwandari Alam A. Hidayat Anak. A.N.P. Redi Muhammad Asrol Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta 11440 Indonesia PT Impack Pratama Industri Jakarta 14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99.

关键词： closed space deep learning humity prediction indoor temperature prediction

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Augmented Reality With Authentic GeometryGo App to Help Geometry Learning and Assessments

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IEEE Transactions on Learning Technologies 2023年第5期16卷 769-779页

作者： Hwang, Wu-Yuin Nurtantyana, Rio Purba, Siska Wati Dewi Hariyanti, Uun Suprapto National Dong Hwa University Department of Computer Science and Information Engineering College of Science and Engineering Hualien974 Taiwan National Central University Graduate Institute of Network Learning Technology Taoyuan City320 Taiwan Telkom University School of Computing Bandung40257 Indonesia Universitas Pelita Harapan Department of Master of Educational Technology Kota Tangerang15811 Indonesia Brawijaya University Information Systems Department Kota Malang65145 Indonesia State University Yogyakarta Department of Electronics Engineering Education Yogyakarta55281 Indonesia

We developed an Authentic GeometryGo (AGG) app to help students application of geometry in authentic contexts through authentic measurements and peer assessments. The study included an experimental group (EG) using an AGG app and a control group (CG) using paper-based methods. The results showed that the EG outperformed the CG in terms of estimation. Measuring authentic geometry shapes using the app could foster students' estimation. Furthermore, meaningful peer assessments with visual representations in authentic contexts can facilitate the evaluation of peers' work and improve students' geometry understanding. Therefore, we encourage educators to use augmented reality with appropriate learning activities to sharpen students' measurement quality and visual representations by measuring real geometry shapes and applying mathematics knowledge in authentic contexts. © 2008-2011 IEEE.

关键词： Augmented reality

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Aspect-based Sentiment Analysis for Improving Online Learning program Based on Student Feedback 6

Aspect-based Sentiment Analysis for Improving Online Learnin...

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6th IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Murad, Dina Fitria Tho, Cuk Hashimoto, Kiyota Binus Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Online Learning Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Online Learning Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Phuket83120 Thailand

ISBN: (数字)9781665497428

ISBN: (纸本)9781665497428

This paper presents an empiric results of aspectbased sentiment analysis in education to extract and classify opinions, sentiments, evaluations, attitudes, and emotions from newly graduates of an online learning program. As part of continuous education monitoring system, the sentiment analysis process produces valuable input to leverage service quality of online learning program. In this study, the aspect-based sentiment analysis is implemented to analyze a set of feedbacks from 162 newly graduate from Binus Online program majoring in Accounting, Management, Information System, and computer science. The important qualitative results of this study are confirmation that the main benefits of online learning from student perspective are mainly: the knowledge they gained from the program, learning guidance, reliable student team to work on thesis, quality of education support system, and learning happiness. © 2022 IEEE.

关键词： Sentiment analysis

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Relip: Reliable in-Band Parallel Communication for Magnetic MIMO Wireless Power Transfer System

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IEEE Transactions on Mobile Computing 2025年

作者： Wang, Xinyu Zhou, Wangqiu Zhou, Hao Jiang, Shenyao Liu, Zhi Wang, Xiaoyan Ji, Yusheng Song, Qi City University of Hong Kong Department of Computer Science Hong Kong University of Science and Technology of China School of Computer Science and Technology Hefei230027 China The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo182-8585 Japan Ibaraki University Graduate School of Science and Engineering Ibaraki310-8512 Japan National Institute of Informatics Information Systems Architecture Science Research Division Tokyo101-0003 Japan

In magnetic resonant coupling (MRC) based wireless power transfer (WPT) systems, receiver (RX) feedback communication is promising to enhance the capability and efficiency of the system. Although some studies have explored in-band implementations with low overhead costs, it has not been comprehensively investigated. In this paper, we propose Relip, a Reliable layer-level in-band parallel feedback communication mechanism for MIMO MRC-WPT systems, which addresses the impact of RX-RX couplings (i.e., non-negligible interference from strong couplings and positive effects of relay phenomenon), and provides a theoretical analysis of communication reliability. Technically, we first devise an On-Off based two-phase modulation mechanism to achieve RX identification and dependency detection under relay phenomenon. Then, we utilize observed channel decomposability to collect group-level power transfer channel conditions for eliminating the interference caused by strong RX-RX couplings. Furthermore, we perform RX selection to optimize the trade-off between communication reliability and time overhead. We design and implement the Relip prototype and conduct extensive experiments. The results validate the effectiveness of our mechanism, i.e., Relip can provide ≥99% average decoding accuracy for concurrent feedback communication of 14 devices, achieving an 18.31% improvement compared to the state-of-the-art solution. © 2002-2012 IEEE.

关键词： Inductive power transmission

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