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arXiv 2020年

作者： Tang, Yutian Zhou, Hao Xu, Zhou Luo, Xiapu Cai, Yan Zhang, Tao Department of Computing Hong Kong Polytechnic University Hong Kong School of Big Data and Software Engineering Chongqing University China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China Faculty of Information Technology Macau University of Science and Technology China

software reuse enables developers to reuse architecture, programs and other software artifacts. Realizing a systematical reuse in software brings a large amount of benefits for stakeholders, including lower maintenance efforts, lower development costs, and time to market. Unfortunately, currently implementing a framework for large-scale software reuse in Android apps is still a huge problem, regarding the complexity of the task and lacking of practical technical support from either tools or domain experts. Therefore, proposing a feature location benchmark for apps will help developers either optimize their feature location techniques or reuse the assets created in the benchmark for reusing. In this paper, we release a feature location benchmark, which can be used for those developers, who intend to compose software product lines (SPL) and release reuse in apps. The benchmark not only contributes to the research community for reuse research, but also helps participants in industry for optimizing their architecture and enhancing modularity. In addition, we also develop an Android Studio plugin named caIDE for developers to view and operate on the benchmark. Copyright © 2020, The Authors. All rights reserved.

关键词： computer software reusability

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Electromyography-driven exergaming in wheelchairs on a mobile platform: Bench and pilot testing of the WOW-mobile fitness system

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JMIR Rehabilitation and Assistive Technologies 2021年第1期8卷 e16054页

作者： Enciso, James Variya, Dhruval Sunthonlap, James Sarmiento, Terrence Lee, Ka Mun Velasco, James Pebdani, Roxanna N. de Leon, Ray D. Dy, Christine Keslacy, Stefan Won, Deborah Soonmee Department of Electrical and Computer Engineering California State University Los Angeles Los Angeles CA United States Rufus Labs Los Angeles CA United States Siemens PLM Software Los Angeles CA United States University of Sydney Sydney Australia School of Kinesiology and Nutritional Science California State University Los Angeles Los Angeles CA United States

Background: Implementing exercises in the form of video games, otherwise known as exergaming, has gained recent attention as a way to combat health issues resulting from sedentary lifestyles. However, these exergaming apps have not been developed for exercises that can be performed in wheelchairs, and they tend to rely on whole-body movements. Objective: This study aims to develop a mobile phone app that implements electromyography (EMG)-driven exergaming, to test the feasibility of using this app to enable people in wheelchairs to perform exergames independently and flexibly in their own home, and to assess the perceived usefulness and usability of this mobile health system. Methods: We developed an Android mobile phone app (Workout on Wheels, WOW-Mobile) that senses upper limb muscle activity (EMG) from wireless body-worn sensors to drive 3 different video games that implement upper limb exercises designed for people in wheelchairs. Cloud server recordings of EMG enabled long-term monitoring and feedback as well as multiplayer gaming. Bench testing of data transmission and power consumption were tested. Pilot testing was conducted on 4 individuals with spinal cord injury. Each had a WOW-Mobile system at home for 8 weeks. We measured the minutes for which the app was used and the exergames were played, and we integrated EMG as a measure of energy expended. We also conducted a perceived usefulness and usability questionnaire. Results: Bench test results revealed that the app meets performance specifications to enable real-time gaming, cloud storage of data, and live cloud server transmission for multiplayer gaming. The EMG sampling rate of 64 samples per second, in combination with zero-loss data communication with the cloud server within a 10-m range, provided seamless control over the app exergames and allowed for offline data analysis. Each participant successfully used the WOW-Mobile system at home for 8 weeks, using the app for an average of 146 (range 89-267)

关键词： Exergaming Gamercising Mobile health Mobile phone Wheelchair exercises Wireless electromyography

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Fabricating PVDF hollow fiber microfiltration membrane with a tenon-connection structure via the thermally induced phase separation process to enhance strength and permeability

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European Polymer Journal 2019年 111卷 49-62页

作者： Cui, Zhenyu Li, Wei Zeng, Haiyi Tang, Xiuxiu Zhang, Jing Qin, Shuhao Han, Na Li, Jianxin State Key Laboratory of Separation Membranes and Membrane Processes/National Center for International Joint Research on Separation Membranes School of Material Science and Engineering Tianjin Polytechnic University Tianjin 300387 China School of Computer Science and Software Engineering Tianjin Polytechnic University Tianjin 300387 China National Engineering Research Canter for Compounding and Modification of Polymer Materials Guiyang 550014 China

In this work, thermally induced phase separation (TIPS) method was adopted to manufacture polyvinylidene fluoride (PVDF) blend hollow fiber microfiltration membrane with tenon-connection structure, which is used to fasten in Chinese traditional building by the stronger friction between rabbet and mortise, for water treatment by blending polyvinyl butyral (PVB). In this microstructure formation process, the distribution of PVB within the matrix and its regulatory role were investigated. Especially, the comprehensive effect of rabbeting and PVB adhesion on strength (The maximum breaking strength reached 17.08 MPa) was discussed. The results showed that a suitable PVB will markedly reduce the thickness of skin-layer close to the outside surface even for the solid-liquid (S-L) phase separation while the excessive PVB result in a thick skin-layer. Besides the strength, PVB markedly improved the hydrophilicity and permeability of the membrane. The breaking strength is more than 8 MPa, the maximum pure water flux is as high as 929.23 L m⁻² h⁻¹ and the rejection rate of carbon particles is nearly 100% even the polymer content is only 22%. In addition, the membrane showed a β-phase and an improved anti-fouling capacity. The investigation presented a simple way to regulate microstructure, enhance mechanical strength, flux and anti-fouling capacity of the membrane via the TIPS process for water treatment. © 2018

关键词： Adhesion effect Permeability Strengthening Tenon-connection Thermally induced phase separation

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Batch reverse osmosis:a new research direction in water desalination

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science Bulletin 2020年第20期65卷 1705-1708页

作者： Mingheng Li Yi Heng Jiu Luo Department of Chemical and Materials Engineering California State Polytechnic UniversityPomonaCA 91768USA School of Data and Computer Science Sun Yat-sen UniversityGuangzhou 510006China Guangdong Province Key Laboratory of Computational Science Guangzhou 510006China National Supercomputing Center in Guangzhou(NSCC-GZ) Guangzhou 510006China School of Materials Science and Engineering Sun Yat-sen UniversityGuangzhou 510275China

Water scarcity is one of the grand challenges across the world[1].Spiral wound reverse osmosis(RO)desalination is the most popular industrial technology to produce portable water from saline water *** terms of flow pattern,it falls into the category of cross-flow filtration where feed flows tangentially along the membrane surface while filtrate permeates across the membrane.

关键词： flow tangential category

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Using Behavior Data to Predict User Success in Ontology Class Mapping - An Application of Machine Learning in Interaction Analysis

Using Behavior Data to Predict User Success in Ontology Clas...

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International Conference on Semantic Computing

作者： Bo Fu Ben Steichen Computer Engineering and Computer Science California State University Long Beach USA Computer Science California State Polytechnic University Pomona USA

Ontology visualization has played an important role in human data interaction by offering clarity and insight for complex structured datasets. Recent usability evaluations of ontology visualization techniques have added to our understanding of desired features when assisting users in the interactive process. However, user behavior data such as eye gaze and event logs have largely been used as indirect evidence to explain why a user may have carried out certain tasks in a controlled environment as opposed to direct input that informs the underlying visualization system. Although findings from usability studies have contributed to the refinement of ontology visualizations as a whole, the visualization techniques themselves remain a one-size-fits-all approach where all users are presented with the same visualizations and interactive features. By contrast, this paper investigates how user behavior data may offer real time indications as to how appropriate or effective a given visualization may be for a specific user at a moment in time, which in turn may inform the adaptation of the given visualization to the user on the fly. To this end, we apply established predictive modeling techniques in Machine Learning to predict user success using gaze data and event logs. We present a detailed analysis and demonstrate such predictions can be significantly better than a baseline classifier during visualization usage. These predictions can then be used to drive the adaptations of visual systems in providing ad hoc visualizations on a per user basis, which in turn may increase individual user success and performance.

关键词： Ontologies Data visualization Visualization Usability Task analysis Machine learning Real-time systems

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The 2D Materials Roadmap

arXiv

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arXiv 2025年

作者： Ren, Wencai Bøggild, Peter Redwing, Joan Marie Novoselov, Kostya Sun, Luzhao Qi, Yue Jia, Kaicheng Liu, Zhongfan Burton, Oliver Alexander-Webber, Jack Hofmann, Stephan Cao, Yang Long, Yu Yang, Quan-Hong Li, Dan Choi, Soo Ho Kim, Ki Kang Lee, Young Hee Li, Mian Huang, Qing Gogotsi, Yury Clark, Nicholas Carl, Amy Gorbachev, Roman Olsen, Thomas Rosen, Johanna Thygesen, Kristian Sommer Efetov, Dmitri K. Jessen, Bjarke S. Yankowitz, Matthew Barrier, Julien Kumar, Roshan Krishna Koppens, Frank H.L. Deng, Hui Li, Xiaoqin Dai, Siyuan Basov, D.N. Wang, Xinran Das, Saptarshi Duan, Xiangfeng Yu, Zhihao Borsch, Markus Ferrari, Andrea C. Huber, Rupert Kira, Mackillo Xia, Fengnian Wang, Xiao Wu, Zhong-Shuai Feng, Xinliang Simon, Patrice Cheng, Hui-Ming Liu, Bilu Xie, Yi Jin, Wanqin Nair, Rahul Raveendran Xu, Yan Zhang, Qing Katiyar, Ajit K. Ahn, Jong-Hyun Aharonovich, Igor Hersam, Mark C. Roche, Stephan Hua, Qilin Shen, Guozhen Ren, Tianling Zhang, Hao-Bin Koo, Chong Min Koratkar, Nikhil Pellegrini, Vittorio Young, Robert J. Qu, Bill Lemme, Max Pollard, Andrew J. Shenyang National Laboratory for Materials Science Institute of Metal Research Chinese Academy of Sciences 72 Wenhua Road Shenyang110016 China Technical University of Denmark Denmark The Pennsylvania State University United States University of Manchester United Kingdom Institute for Functional Intelligent Materials National University of Singapore Singapore Beijing Graphene Institute China University of Cambridge United Kingdom Department of Chemical Engineering The University of Melbourne Victoria Australia Nanoyang Group Tianjin Key Laboratory of Advanced Carbon and Electrochemical Energy Storage School of Chemical Engineering and Technology Tianjin University Tianjin300072 China The Hong Kong University of Science and Technology Hong Kong Center for Integrated Nanostructure Physics Institute for Basic Science Suwon16419 Korea Republic of Sungkyunkwan University Suwon16419 Korea Republic of Zhejiang Key Laboratory of Data-Driven High-Safety Energy Materials and Applications Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences China Drexel University United States Linköping University Sweden Ludwig-Maximilians-Universität München Germany University of Washington United States ICFO The Institute of Photonic Sciences Castelldefels Barcelona08860 Spain University of Michigan United States University of Texas Austin United States Auburn University United States Columbia University United States State Key Laboratory of Catalysis Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian China University of California Los Angeles United States Suzhou Laboratory Suzhou China School of Integrated Circuit Science and Engineering Nanjing University of Posts and Telecommunications Nanjing210023 China Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States University of Regensburg Germany Department of Electrical and Computer Engineering Yale University New Have

Over the past two decades, 2D materials have rapidly evolved into a diverse and expanding family of material platforms. Many members of this materials class have demonstrated their potential to deliver transformative impact on fundamental research and technological applications across different fields. In this roadmap, we provide an overview of the key aspects of 2D material research and development, spanning synthesis, properties and commercial applications. We specifically present roadmaps for high impact 2D materials, including graphene and its derivatives, transition metal dichalcogenides, MXenes as well as their heterostructures and moiré systems. The discussions are organized into thematic sections covering emerging research areas (e.g., twisted electronics, moiré nano-optoelectronics, polaritronics, quantum photonics, and neuromorphic computing), breakthrough applications in key technologies (e.g., 2D transistors, energy storage, electrocatalysis, filtration and separation, thermal management, flexible electronics, sensing, electromagnetic interference shielding, and composites) and other important topics (computational discovery of novel materials, commercialization and standardization). This roadmap focuses on the current research landscape, future challenges and scientific and technological advances required to address, with the intent to provide useful references for promoting the development of 2D materials. © 2025, CC BY.

关键词： Integrated optoelectronics

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A reinforcement learning approach for the autonomous assembly of in-space habitats and infrastructures in uncertain environments 70

A reinforcement learning approach for the autonomous assembl...

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70th International Astronautical Congress, IAC 2019

作者： Moser, Joshua Cooper, John Neilan, James Chapin, Liam Glassner, Samantha Komendera, Erik Department of Mechanical Engineering Virginia Polytechnic Institute State University United States Autonomous Integrated Systems Research Branch NASA Langley Research Center Flight Software System Branch NASA Langley Research Center Department of Computer Science Virginia Polytechnic Institute State University United States Department of Mechanical Engineering Northeastern University

NASA Langley Research Center has developed a robotic unit, the Assembler, for use in the domain of autonomous in-space assembly, capable of reconfiguration and collaboration. A known part of space mission scheduling and the autonomous collaborative assembly problem is task assignment. This problem can be thought of as a Markov decision process framing of a job shop scheduling problem which allows for a reinforcement learning solution to approximate the optimal policies for task assignment. The research presented here initiates the evaluation of reinforcement learning to that end. Simulation results show that the policies determined through reinforcement learning performed better than random and greedy policies. These promising results will support further research into the applicability and optimality of reinforcement learning in increasingly complex scenarios. Copyright © 2019 by the International Astronautical Federation (IAF). All rights reserved.

关键词： Reinforcement learning

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Development of mobile applications to study engineering students’ patterns of learning

Development of mobile applications to study engineering stud...

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Frontiers in Education (FIE) Conference

作者： David S. Janzen Ryan Chang John Chen California Polytechnic State University San Luis Obispo Computer Science and Software Engineering California USA Education Research and Outreach University of Oregon Eugene OR USA Mechanical Engineering California Polytechnic State University San Luis Obispo California USA

ISBN: (数字)9781728117461

ISBN: (纸本)9781728117478

This Research Work in Progress Paper presents a novel mobile software application created to perform ecological momentary assessment in two longitudinal studies with undergraduate engineering students. The studies collect learning activity data from first and second-year mechanical engineering students to examine the correlation of active learning with grit growth and student success and retention, and the possible associations between these factors. The software system consists of native Android and iOS mobile applications and a REST-based server application for prompting and collecting learning activity data from student participants. The system utilizes personalized student schedule data to push notifications to students on their smartphones as they complete each class or lab section. Students then submit the amount of time they spent in each class doing different types of activities including interactive, constructive, active, and passive. Students also receive notification reminders to enter out-of-class study activities. The system also includes automated daily audits and notifications to ensure consistent data entry activity. This paper will discuss the research context, early study results, software architecture, and the software development experience including institutional challenges, rationale for technology choices, strategies for developing research software with student developers, and lessons learned.

关键词： software Androids Humanoid robots Schedules Databases Education software architecture

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Earthworm - Automated decomposition suggestions 18

Earthworm - Automated decomposition suggestions

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18th Koli Calling Conference on Computing Education Research, Koli Calling 2018

作者： Garg, Nupur Keen, Aaron W. Computer Science and Software Engineering California Polytechnic State University San Luis ObispoCA United States

ISBN: (纸本)9781450365352

Functional decomposition is the process of breaking a larger problem into smaller subproblems so that each component implements only a single task. Although functional decomposition is integral to computer science, it is often overlooked in introductory computer science education due to the challenges of teaching and assessing it given limited resources. Earthworm is a tool that leverages static analysis techniques to generate suggestions on how to improve the decomposition of Python programs. Each suggestion includes the lines of code that can be refactored into a new function, the arguments that must be passed to this function and the variables returned from the function. The tool is intended to be used in introductory computer science courses to help students develop decomposition skills. © 2018 Copyright held by the owner/author(s).

关键词： Static analysis

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Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at (Formula presented.) TeV with the ATLAS detector

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Journal of High Energy Physics 2024年第4期2024卷 26页

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Abusleme Hoffman, A.C. Acharya, B.S. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Allendes Flores, C.A. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Alviggi, M.G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Amor Dos Santos, S.P. Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Appelt, C. Apyan, A. Aranzabal, N. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Bakalis, C. Baker, O.K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. Bandieramont Department of Physics University of Adelaide Department of Physics University of Alberta Department of Physics Ankara University Division of Physics TOBB University of Economics and Technology LAPP Université Savoie Mont Blanc CNRS/IN2P3 APC Université Paris Cité CNRS/IN2P3 High Energy Physics Division Argonne National Laboratory Department of Physics University of Arizona Department of Physics University of Texas at Arlington Physics Department National and Kapodistrian University of Athens Physics Department National Technical University of Athens Department of Physics University of Texas at Austin Institute of Physics Azerbaijan Academy of Sciences Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Institute of High Energy Physics Chinese Academy of Sciences Physics Department Tsinghua University Department of Physics Nanjing University School of Science Shenzhen Campus of Sun Yat-sen University University of Chinese Academy of Science (UCAS) Institute of Physics University of Belgrade Department for Physics and Technology University of Bergen Physics Division Lawrence Berkeley National Laboratory University of California Institut für Physik Humboldt Universität zu Berlin Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern School of Physics and Astronomy University of Birmingham Department of Physics Bogazici University Department of Physics Engineering Gaziantep University Department of Physics Istanbul University Facultad de Ciencias y Centro de Investigaciónes Universidad Antonio Nariño Departamento de Física Universidad Nacional de Colombia Dipartimento di Fisica e Astronomia A. Righi Università di Bologna INFN Sezione di Bologna Physikalisches Institut Universität Bonn Department of Physics Boston University Department of Physics Brandeis University Transilvania University of Brasov Horia Hulubei National Institute of Physics and Nuclear Engineering Department of Physics Alexandru

This paper presents the measurement of fiducial and differential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W^±W^±jj) using 139 fb⁻¹ of proton-proton collision data recorded at a centre-of-mass energy of s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity difference. The measured fiducial cross sections for electroweak and inclusive W^±W^±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.) fb and 3.38 ± 0.22 (stat.) ± 0.19 (syst.) fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confidence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H^±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H^±± mass near 450 GeV, with a global significance of 2.5 standard deviations. © The Author(s) 2024.

关键词： Hadron-Hadron Scattering Vector Boson Production

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