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International Conference on Informatics and Computing (ICIC)

作者： Aulia Akhrian Syahidi Ahmad Afif Supianto Tsukasa Hirashima Yutaka Watanobe Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin City Indonesia Research Center for Data and Information Sciences National Research and Innovation Agency (BRIN) Bandung City Indonesia Learning Engineering Laboratory Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Higashihiroshima Japan Department of Computer Science and Engineering Division of Information Systems University of Aizu Aizu-Wakamatsu City Fukushima Japan

ISBN: (纸本)9798350345728

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the “if-then” rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process.

关键词： Visualization Codes Media Data models Recording Data mining Problem-solving

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Importance of Wearable Health Monitoring systems Using IoMT;Requirements, Advantages, Disadvantages and Challenges

Importance of Wearable Health Monitoring Systems Using IoMT;...

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International Symposium on Computational Intelligence and Informatics

作者： Fahime Khozeimeh Mohamad Roshanzamir Afshin Shoeibi Mohammad Tayarani Darbandy Roohallah Alizadehsani Hamid Alinejad-Rokny Davood Ahmadian Abbas Khosravi Saeid Nahavandi Institute for Intelligent Systems Research and Innovation (IISRI) Deakin University Victoria Australia Department of Computer Engineering Fasa University Fasa Iran Internship in Health Data Analytics Program AI-enabled Processes (AIP) Research Centre Macquarie University Sydney Australia School of Architecture Islamic Azad University Taft Taft Iran BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney Sydney NSW Australia Faculty of Mathematics Statistics and Computer Sciences University of Tabriz Tabriz Iran

ISBN: (纸本)9798350398830

Providing better quality of service is one of the most important goals in medical/healthcare systems. The services provided should have features such as low latency, appropriate geographic distribution, and real-time interaction. Internet of Medical Things (IoMT) technology is one of the solutions to achieve high quality of services with these features. The wearable health monitoring systems which have become popular in the last decade are one of the foundations of achievement to these features. In this paper, the importance of wearable devices under IoMT technology is investigated. There are several reasons for using wearable devices under IoMT technology, such as reducing healthcare costs and long waiting times. Therefore, anyone working on wearable devices needs to have a general understanding of how they are designed and function. In fact, the integration of new devices to monitor and alert patients about their physical health is a promising option for improving health care systems around the world. Overcrowding in medical centers will be prevented by upgrading the facilities for the virtual presence of patients. It can also ensure real-time monitoring and reduce operating costs. In addition, it can accelerate treatment of patients and reduce the cost of investment and increase its coverage.

关键词： Costs Medical devices Wearable computers Quality of service Organizations Real-time systems Security

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Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things

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InfoMat 2020年第6期2卷 1131-1162页

作者： Qiongfeng Shi Bowei Dong Tianyiyi He Zhongda Sun Jianxiong Zhu Zixuan Zhang Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore117576Singapore Center for Intelligent Sensors and MEMS National University of SingaporeSingapore117608Singapore Hybrid-Integrated Flexible(Stretchable)Electronic Systems Program National University of SingaporeSingapore117608Singapore NUS Suzhou Research Institute(NUSRI) Suzhou215123China NUS Graduate School for Integrative Science and Engineering National University of SingaporeSingapore117456Singapore

The past few years have witnessed the significant impacts of wearable electronics/photonics on various aspects of our daily life,for example,healthcare monitoring and treatment,ambient monitoring,soft robotics,prosthetics,flexible display,communication,human-machine interactions,and so *** to the development in recent years,the next-generation wearable electronics and photonics are advancing rapidly toward the era of artificial intelligence(AI)and internet of things(IoT),to achieve a higher level of comfort,convenience,connection,and ***,this review provides an opportune overview of the recent progress in wearable electronics,photonics,and systems,in terms of emerging materials,transducing mechanisms,structural configurations,applications,and their further integration with other ***,development of general wearable electronics and photonics is summarized for the applications of physical sensing,chemical sensing,humanmachine interaction,display,communication,and so *** self-sustainable wearable electronics/photonics and systems are discussed based on system integration with energy harvesting and storage ***,technology fusion of wearable systems and AI is reviewed,showing the emergence and rapid development of intelligent/smart *** the last section of this review,perspectives about the future development trends of the next-generation wearable electronics/photonics are provided,that is,toward multifunctional,self-sustainable,and intelligent wearable systems in the AI/IoT era.

关键词： artificial intelligence energy harvesting human-machine interface internet of things wearable electronics wearable photonics

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Feasibility of Bluetooth Low Energy wearable tags to quantify healthcare worker proximity networks and patient close contact: A pilot study

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Infection, Disease and Health 2022年第2期27卷 66-70页

作者： Curtis, Stephanie J. Rathnayaka, Asanka Wu, Fan Al Mamun, Abdulla Spiers, Craig Bingham, Gordon Lau, Colleen L. Peleg, Anton Y. Yuce, Mehmet Rasit Stewardson, Andrew J. Research School of Population Health The Australian National University Building 62 Mills Road Acton Canberra 2601 Australian Capital Territory Australia Department of Infectious Diseases The Alfred Hospital and Monash University 85 Commercial Road Melbourne 3004 VIC Australia Department of Electrical and Computer Systems Engineering Monash University 14 Alliance Lane Clayton Melbourne 3800 VIC Australia Alfred Brain Program Alfred Health 55 Commercial Road Melbourne 3004 VIC Australia Information Development Division Alfred Health 55 Commercial Road Melbourne 3004 VIC Australia School of Public Health University of Queensland 288 Herston Road Herston 4006 QLD Australia Infection and Immunity Program Monash Biomedicine Discovery Institute Department of Microbiology Monash University Clayton 3800 VIC Australia

Background: The hospital environment is characterised by a dense network of interactions between healthcare workers (HCWs) and patients. As highlighted by the coronavirus pandemic, this represents a risk for disease transmission and a challenge for contact tracing. We aimed to develop and pilot an automated system to address this challenge and describe contacts between HCWs and patients. Methods: We developed a bespoke Bluetooth Low Energy (BLE) system for the hospital environment with anonymous tags worn by HCWs and fixed receivers at patient room doors. Proximity between wearable tags inferred contact between HCWs. Tag-receiver interactions inferred patient room entry and exit by HCWs. We performed a pilot study in four negative pressure isolation rooms from 13 April to 18 April 2021. Nursing and medical staff who consented to participate were able to collect one of ten wearable BLE tags during their shift. Results: Over the four days, when divided by shift times, 27 nursing tags and 3 medical tags were monitored. We recorded 332 nurse–nurse interactions, for a median duration of 58 s [interquartile range (IQR): 39–101]. We recorded 45 nursing patient room entries, for a median 7 min [IQR: 3–21] of patient close contact. Patient close contact was shorter in rooms on airborne precautions, compared to those not o transmission-based precautions. Conclusion: This pilot study supported the functionality of this approach to quantify HCW proximity networks and patient close contact. With further refinements, the system could be scaled-up to support contact tracing in high-risk environments. © 2021 The Author(s)

关键词： Contact tracing Coronavirus Epidemiology Healthcare-associated infections Technology

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Physics-Informed Neural Nets for Control of Dynamical systems

arXiv

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arXiv 2021年

作者： Antonelo, Eric Aislan Camponogara, Eduardo Seman, Laio Oriel de Souza, Eduardo Rehbein Jordanou, Jean Panaioti Hübner, Jomi Fred Department of Automation and Systems Engineering Federal University of Santa Catarina FlorianópolisCEP: 88040-900 Brazil Gradute Program in Applied Computer Science University of Vale do Itajaí Itajaí CEP: 88302-901 Brazil

Physics-informed neural networks (PINNs) impose known physical laws into the learning of deep neural networks, making sure they respect the physics of the process while decreasing the demand of labeled data. For systems represented by Ordinary Differential Equations (ODEs), the conventional PINN has a continuous time input variable and outputs the solution of the corresponding ODE. In their original form, PINNs do not allow control inputs, neither can they simulate for variable long-range intervals without serious degradation in their predictions. In this context, this work presents a new framework called Physics-Informed Neural Nets for Control (PINC), which proposes a novel PINN-based architecture that is amenable to control problems and able to simulate for longer-range time horizons that are not fixed beforehand, making it a very flexible framework when compared to traditional PINNs. Furthermore, this long-range time simulation of differential equations is faster than numerical methods since it relies only on signal propagation through the network, making it less computationally costly and, thus, a better alternative for simulation of models in Model Predictive Control. We showcase our proposal in the control of two nonlinear dynamic systems: The Van der Pol oscillator and the four-tank system. Copyright © 2021, The Authors. All rights reserved.

关键词： Ordinary differential equations

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FaSTrack:A Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking

FaSTrack:A Modular Framework for Real-Time Motion Planning a...

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作者： Chen, Mo Herbert, Sylvia L. Hu, Haimin Pu, Ye Fisac, Jaime Fernandez Bansal, Somil Han, Soojean Tomlin, Claire J. School of Computing Science Simon Fraser University BurnabyBCV5A 1S6 Canada Department of Mechanical and Aerospace Engineering University of California San Diego San DiegoCA92122 United States Department of Electrical Engineering Princeton University PrincetonNJ08536 United States Department of Electrical and Electronic Engineering University of Melbourne ParkvilleVIC3010 Australia Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94704 United States Control and Dynamical Systems Program California Institute of Technology Los AngelesCA90019 United States

Real-time, guaranteed safe trajectory planning is vital for navigation in unknown environments. However, real-time navigation algorithms typically sacrifice robustness for computation speed. Alternatively, provably safe trajectory planning tends to be too computationally intensive for real-time replanning. We propose FaSTrack, Fast and Safe Tracking, a framework that achieves both real-time replanning and guaranteed safety. In this framework, real-time computation is achieved by allowing any trajectory planner to use a simplified planning model of the system. The plan is tracked by the system, represented by a more realistic, higher dimensional tracking model. We precompute the tracking error bound (TEB) due to mismatch between the two models and due to external disturbances. We also obtain the corresponding tracking controller used to stay within the TEB. The precomputation does not require prior knowledge of the environment. We demonstrate FaSTrack using Hamilton-Jacobi reachability for precomputation and three different real-time trajectory planners with three different tracking-planning model pairs. © 1963-2012 IEEE.

关键词： Real time systems

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Scientometric Research Assessment of IEEE CSCWD Conference Proceedings: An Exploratory Analysis from 2001 to 2019

Scientometric Research Assessment of IEEE CSCWD Conference P...

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International Conference on computer Supported Cooperative Work in Design

作者： António Correia Dennis Paulino Hugo Paredes Benjamim Fonseca Shoaib Jameel Daniel Schneider Jano Moreira de Souza INESC TEC and University of Trás-os-Montes e Alto Douro UTAD Vila Real Portugal School of Computer Science and Electronic Engineering Colchester Campus University of Essex UK Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil

ISBN: (纸本)9781728165981

It has been a quarter of a century since the publication of the first edition of the IEEE International Conference on computer Supported Cooperative Work in Design (CSCWD) held in 1996 in Beijing, China. Despite some attempts to empirically examine the evolution and identity of the field of CSCW and its related communities and disciplines, the scarcity of scientometric studies on the IEEE CSCWD research productivity is noteworthy. To fill this gap, this study reports on an exploratory quantitative analysis of the literature published in the IEEE CSCWD conference proceedings with the purpose of visualizing and understanding its structure and evolution for the 2001-2019 period. The findings offer valuable insights into the paper and author distribution, country and citation-level productivity indicators, degree of collaboration, and collaboration index. Through this analysis we also expect to get an initial overview of the IEEE CSCWD conference concerning the main topics being presented, most cited papers, and variances in the number of keywords, full-text views, and references.

关键词： Productivity Visualization Statistical analysis Conferences Bibliometrics Collaboration Collaborative work

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Scalable and efficient neural speech coding: A hybrid design

arXiv

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arXiv 2021年

作者： Zhen, Kai Sung, Jongmo Lee, Mi Suk Beack, Seungkwon Kim, Minje Department of Computer Science and Cognitive Science Program Indiana University BloomingtonIN47408 United States Electronics and Telecommunications Research Institute Daejeon34129 Korea Republic of Dept. of Intelligent Systems Engineering Indiana University United States

We present a scalable and efficient neural waveform coding system for speech compression. We formulate the speech coding problem as an autoencoding task, where a convolutional neural network (CNN) performs encoding and decoding as a neural waveform codec (NWC) during its feedforward routine. The proposed NWC also defines quantization and entropy coding as a trainable module, so the coding artifacts and bitrate control are handled during the optimization process. We achieve efficiency by introducing compact model components to NWC, such as gated residual networks and depthwise separable convolution. Furthermore, the proposed models are with a scalable architecture, cross-module residual learning (CMRL), to cover a wide range of bitrates. To this end, we employ the residual coding concept to concatenate multiple NWC autoencoding modules, where each NWC module performs residual coding to restore any reconstruction loss that its preceding modules have created. CMRL can scale down to cover lower bitrates as well, for which it employs linear predictive coding (LPC) module as its first autoencoder. The hybrid design integrates LPC and NWC by redefining LPC’s quantization as a differentiable process, making the system training an end-to-end manner. The decoder of proposed system is with either one NWC (0.12 million parameters) in low to medium bitrate ranges (12 to 20 kbps) or two NWCs in the high bitrate (32 kbps). Although the decoding complexity is not yet as low as that of conventional speech codecs, it is significantly reduced from that of other neural speech coders, such as a WaveNet-based vocoder. For wide-band speech coding quality, our system yields comparable or superior performance to AMR-WB and Opus on TIMIT test utterances at low and medium bitrates. The proposed system can scale up to higher bitrates to achieve near transparent performance. © 2021, CC BY.

关键词： Convolution

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FaNDOM: Fast Nested Distance-Based Seeding of Optical Maps

SSRN

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SSRN 2021年

作者： Dehkordi, Siavash Raeisi Luebeck, Jens Bafna, Vineet Department of Computer Science & Engineering University of California San Diego San diegoCA92093 United States Bioinformatics & Systems Biology Graduate Program University of California San Diego San diegoCA92093 United States

Optical mapping provides single-molecule readouts of the locations of fluorescently labeled sequence motifs on long fragments of DNA, resolved to nucleotide-level coordinates. With the advent of microfluidic technologies for manipulating large numbers of individual molecules, and advances in the imaging of fluorescent DNA tags, it is possible to inexpensively generate high coverage and long OM molecules (>150Kbp). In addition to its use in scaffolding for de novo assembly, optical map data can also be mapped to a reference for identifying genetic structural variants implicated in Mendelian diseases and cancer. To address the computational challenge, we introduce FaNDOM (Fast Nested Distance seeding of Optical Maps) - an optical map alignment tool which greatly reduces the search space of the alignment process. On 4 benchmark human data-sets, FaNDOM was significantly (4-14X) faster than competing tools while maintaining comparable sensitivity and specificity. We used FaNDOM to map variants in 3 cancer cell-lines and identified many structural variations, including deletion of tumor-suppressor genes, duplications, gene fusions and gene-disrupting rearrangements. FaNDOM is publicly available at (https://***/jluebeck/FaNDOM). © 2021, The Authors. All rights reserved.

关键词： Genes

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Whole-body phase plane analysis for standard maximum vertical jump assessment

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Gait & Posture 2021年 90卷 203-204页

作者： Rodrigues, C. Correia, M. Abrantes, J. Rodrigues, B. Nadal, J. INESC TEC - Institute for Systems and Computer Engineering- Technology and Science C-BER - Centre for Biomedical Engineering Research Porto Portugal University of Porto Faculty of Engineering Porto Portugal Lusófona University CICANT Centre for Research in Applied Communication Culture and New Technologies - MovLab Laboratory of Technologies for Interactions and Interfaces Lisbon Portugal Federal University of Pernambuco Department of Electronic and Systems Recife Brazil Federal University of Rio de Janeiro Biomedical Engineering Program Rio de Janeiro Brazil

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