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7th International Conference on Advances in Visual Informatics, IVIC 2021

作者： Muhammad, Sufri Admodisastro, Novia Osman, Hafeez Mohd Ali, Norhayati Faculty of Computer Science and Information Technology Department of Software Engineering and Information System Universiti Putra Malaysia Seri Kembangan Selangor43400 Malaysia

ISBN: (纸本)9783030902346

A great potential of various learning environment in mobile learning application can clearly be seen in current pandemic situation. The accessibility of the learning resources needs to be available from anywhere anytime despite having strong or poor internet connection. It has motivated researchers to imply context-aware capability in improving the accessibility of the learning resources. This paper presents a development process of Mudahnya BM mobile application that follows a fundamental concept of Mobile Cloud Learning (MCL). Mudahnya BM is an application to learn basic Malay language for learner 7–12 years old. The injection of extrinsic and intrinsic context-aware help the application to improve the reasoning process for finding available learning resources from service providers. Semantic-based approach is applied in the reasoning process. This study involved the end users for evaluation purposes. 33 randomized scenarios have been tested using One-Sample Wilcoxon Signed Rank test. The result shows a positive impact to the population. © 2021, Springer Nature Switzerland AG.

关键词： Semantics

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Wafer-Scale Synthesis of WS_(2)Films with In Situ Controllable p-Type Doping by Atomic Layer Deposition

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Research 2021年第1期2021卷 1424-1432页

作者： Hanjie Yang Yang Wang Xingli Zou Rongxu Bai Zecheng Wu Sheng Han Tao Chen Shen Hu Hao Zhu Lin Chen David W.Zhang Jack C.Lee Xionggang Lu Peng Zhou Qingqing Sun Edward T.Yu Deji Akinwande Li Ji State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghai 200433China State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China Microelectronics Research Center Department of Electrical and Computer EngineeringThe University of Texas at AustinAustin78758 TexasUSA

Wafer-scale synthesis of p-type TMD films is critical for its commercialization in next-generation electro/*** this work,wafer-scale intrinsic n-type WS_(2)films and in situ Nb-doped p-type WS_(2)films were synthesized through atomic layer deposition(ALD)on 8-inchα-Al_(2)O_(3)/Si wafers,2-inch sapphire,and 1 cm^(2)GaN substrate *** Nb doping concentration was precisely controlled by altering cycle number of Nb precursor and activated by ***_(2)n-FETs and Nb-doped p-FETs with different Nb concentrations have been fabricated using CMOS-compatible processes.X-ray photoelectron spectroscopy,Raman spectroscopy,and Hall measurements confirmed the effective substitutional doping with *** on/off ratio and electron mobility of WS_(2)n-FET are as high as 105 and 6.85 cm^(2)V^(-1)s^(-1),*** WS_(2)p-FET with 15-cycle Nb doping,the on/off ratio and hole mobility are 10 and 0.016 cm^(2)V^(-1)s^(-1),*** p-n structure based on n-and p-type WS_(2)films was proved with a 10^(4)rectifying *** realization of controllable in situ Nb-doped WS_(2)films paved a way for fabricating wafer-scale complementary WS_(2)FETs.

关键词： sapphire doping realization

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Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning

arXiv

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arXiv 2024年

作者： Zeng, Runhao Zhou, Dingjie Liang, Qiwei Liu, Junlin Li, Hui Huang, Changxin Li, Jianqiang Hu, Xiping Sun, Fuchun Artificial Intelligence Research Institute Shenzhen MSU-BIT University China College of Mechatronics and Control Engineering Shenzhen University China College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Computer Science and Technology Tsinghua University China

Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large language model (LLM) to generate reward functions in reinforcement learning, thereby replacing the need for manually designed rewards by experts. However, this approach, which relies on textual descriptions to define learning objectives, fails to achieve controllable and precise behavior learning with clear directionality. In this paper, we introduce a new video2reward method, which directly generates reward functions from videos depicting the behaviors to be mimicked and learned. Specifically, we first process videos containing the target behaviors, converting the motion information of individuals in the videos into keypoint trajectories represented as coordinates through a video2text transforming module. These trajectories are then fed into an LLM to generate the reward function, which in turn is used to train the policy. To enhance the quality of the reward function, we develop a video-assisted iterative reward refinement scheme that visually assesses the learned behaviors and provides textual feedback to the LLM. This feedback guides the LLM to continually refine the reward function, ultimately facilitating more efficient behavior learning. Experimental results on tasks involving bipedal and quadrupedal robot motion control demonstrate that our method surpasses the performance of state-of-the-art LLM-based reward generation methods by over 37.6% in terms of human normalized score. More importantly, by switching video inputs, we find our method can rapidly learn diverse motion behaviors such as walking and running. Copyright © 2024, The Authors. All rights reserved.

关键词： Robots

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Dual-State-Driven Evolutionary Optimization for Expensive Optimization Problems with Continuous and Categorical Variables

Dual-State-Driven Evolutionary Optimization for Expensive Op...

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Data-driven Optimization of Complex systems (DOCS), International Conference on

作者： Lindong Xie Genghui Li Kangnian Lin Zhenkun Wang School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen P.R. China Department of Computer Science and Engineering School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen P.R. China

The surrogate-assisted evolutionary algorithm (SAEA) is one of the most efficient approaches for addressing expensive continuous or combinatorial optimization problems. However, it encounters significant challenges in expensive mixed-variable optimization problems (EMVOPs). To overcome this limitation, a dual-state-driven evolutionary optimization (called DSDEO), integrating a surrogate-assisted mixed-variable evolutionary optimization stage (MVEOS) and a surrogate-assisted continuous-variable evolutionary optimization stage (CVEOS), is proposed in this paper. Specifically, MVEOS employs global and local search to enhance the exploration and exploitation of the mixed-variable space. Global and local searches are alternately executed if one search fails to yield a better solution. CVEOS utilizes a continuous-improvement strategy to refine the continuous variables of the best solution obtained so far. Experimental results demonstrate the advantages of DSDEO compared to some state-of-the-art SAEAs on many benchmark problems.

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Efficient Hybrid Multi-Population Genetic Algorithm for Multi-UAV Task Assignment in Consumer Electronics Applications

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IEEE Transactions on Consumer Electronics 2025年

作者： Bai, Xiaoshan Jiang, Haoyu Li, Chao Ullah, Inam Dabel, Maryam M. Al Bashir, Ali Kashif Wu, Zongze Sam, Shuzhi Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen University Shenzhen City Joint Laboratory of Autonomous Unmanned Systems and Intelligent Manipulation Shenzhen518060 China Tashkent State University of Economics Department of Artificial Intelligence Tashkent100066 Uzbekistan University of Hafr Al Batin Department of Computer Science and Engineering College of Computer Science and Engineering Saudi Arabia Manchester Metropolitan University Manchester United Kingdom Shenzhen518060 China National University of Singapore Department of Electrical and Computer Engineering Singapore117576 Singapore

In recent years, as people’s living standards have improved and consumption concepts have been transformed, the demand for purchasing consumer electronics online has continued to grow, further stimulating the development of the logistics industry. Consequently, how to deliver consumer electronics to households at minimal cost has become a crucial factor that limits the development of the consumer technology industry. To tackle this problem, this paper studies the task assignment problem for multiple initially dispersed UAVs to deliver products to target locations while minimizing their total operation time. Each UAV can continuously provide delivery services to multiple target locations within its limited loading capacity and operation time. To solve this problem, we propose several hybrid multipopulation genetic algorithms. First, a novel crossover operator for the genetic algorithms is designed, through which a single parent chromosome can generate offspring individually. Second, two mutation mechanisms are performed to increase gene diversity. Third, multiple local search strategies are employed to enhance the populations’ fitness during each iteration of evolution. An improved 2-opt local search strategy is applied to optimize individual chromosomes when their similarity with the current best chromosome falls below a prescribed threshold. Alternatively, local search strategies are utilized for 1-opt, 2h-opt and interchange processes. Combining local search strategies, genetic operators, and the multi-population mechanism leads to several hybrid multi-population genetic algorithms. Numerical simulations and experimental tests demonstrate that the hybrid multi-population genetic algorithm, integrated with the improved 2-opt and 1-opt local search strategies, exhibits superior performance among the designed hybrid genetic algorithms, the minimum marginal cost algorithm (MMA), and the existing popular Co-evolutionary Multi-population Genetic Algorithm (CMGA). In exp

关键词： Genetic algorithms

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User Satisfaction Analysis Model of Google Classroom for Online Lectures in COVID-19 Pandemic 4

User Satisfaction Analysis Model of Google Classroom for Onl...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Syafi’ah, Nailis Nambo, Hidetaka Tahyudin, Imam Deptartment of Information System Universitas Amikom Purwokerto Purwokerto Indonesia NST Department Division of Electrical Engineering and Computer Science Kanazawa University Japan

ISBN: (纸本)9781665433945

Google Classroom is one of e-learning platform used for online lectures in COVID-19 (Coronavirus Disease) pandemic at Amikom Purwokerto University. As one of the most widely used e-learning platform, so it is interesting to evaluate the satisfaction of Google Classroom user for improvement purpose in the future. The methods used in this research are End User Computing Satisfaction (EUCS), Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Acceptance Model (TAM), and Human Organization Technology (HOT FIT). These methods used to determine user satisfaction level and compare the accuracy of four methods in measuring user satisfaction of Google Classroom application. The test analysis used is validity test, reliability, user satisfaction test, and Multiple linear regression test. The performances present that they are satisfied with Google Classroom application, the percentage of average value obtained from each method: EUCS of 77.57%, TAM by 80.33%, UTAUT by 72.35%, and HOT FIT by 78.34%. The accuracy comparison of four methods results shows that the best method used in measuring the user satisfaction level of Google Classroom applications is using Human Organization Technology (HOT FIT) method with average results of R-Square value is 28.22%. © 2021 IEEE

关键词： COVID-19

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Performance Analysis of Energy and Secure Efficient Routing for Wireless Sensor Networks

Performance Analysis of Energy and Secure Efficient Routing ...

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Decision Aid sciences and Application (DASA), International Conference on

作者： Amjed Abbas Ahmed Zainab Mohammed Hussein Ali Hamza Najim Khattab M. Ali Alheeti Nurhizam Safie Mohd Satar Aisha Hassan Abdallah Hashim Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Imam AlKadhum College (IKC) Baghdad Iraq Department of Computer Science Information System University of Technology Imam AIKadhum College (IKC) Baghdad Iraq Department of Computer Technical Engineering Imam Al-Kadhum College (IKC) Al-Diwaniyah Iraq Computer Networking Systems Department College of Computer and Information Technology University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Bangi Malaysia Department of Electrical and Computer Engineering Faculty of Engineering International Islamic University Malaysia Selangor Malaysia

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

Wireless Sensor Networks (WSNs) are essential for various applications, but their architecture makes them vulnerable to attacks. While traditional security methods like authentication and encryption offer some protection, they often fall short against specific node attacks. This paper introduces the Secure Energy Aware Routing (SEAR) strategy, which uses trust-based assessments to exclude malicious nodes while optimizing energy consumption. SEAR factors in node trust, hop time, and residual energy to ensure reliable data transmission through trustworthy nodes. MATLAB simulations on networks of varying sizes (100–500) compare SEAR with existing methods (EAD and EASER), demonstrating SEAR's superior performance. Results show significant improvements in packet delivery ratio (13-16%), network throughput (19–24 %), energy consumption (32-36 % ), packet loss (16-190/0), and end-to-end latency (21-26 % ), proving SEAR's effectiveness in enhancing WSN security, energy efficiency, and performance.

关键词： Wireless communication Wireless sensor networks Energy consumption Packet loss Routing Throughput Routing protocols Energy efficiency Encryption Security

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Decision support system for handling intervention on toddlers stunting cases in Indonesia using the certainty factor method 10

Decision support system for handling intervention on toddler...

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10th International Seminar on New Paradigm and Innovation of Natural sciences and itsApplication, ISNPINSA 2020

作者： Sutoyo, I.W. Widodo, A.P. Rochim, A.F. Department of Information System Post Graduated School Diponegoro University Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Indonesia Department of Computer Engineering Faculty Engineering Diponegoro University Indonesia

Stunting is a condition of failure to thrive in children under five caused by lack of nutritional intake for a long time and the occurrence of repeated infections. The causative factor is influenced by inadequate parenting, especially in the first 1,000 days of life. This study applies a decision support system with an expert system as an intervention for handling stunting by providing solutions using the Certainty Factor method. This expert system is implemented using the PHP programming language, and the use of expert systems will be easier when implemented into web-based applications. The test results are acceleration in reducing the number of stunting cases, thus providing the right percentage and solution in handling and increasing supervision of government efforts to combat stunting. Stunting intervention research can see the results of the percentage value of sensitive and specific interventions for pregnant women, nursing mothers, and adolescent girls. Testing uses black-box validation and accuracy. The validation results are in the form of 100%, which shows the system functionality can run well and according to the list of requirements. The accuracy result is 83% which shows that the expert system can function quite well according to the Certainty Factor method. © Published under licence by IOP Publishing Ltd.

关键词： Decision support systems

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Heuristic evaluation and analytical network process for analyzing the role of websites in higher education 10

Heuristic evaluation and analytical network process for anal...

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10th International Seminar on New Paradigm and Innovation of Natural sciences and itsApplication, ISNPINSA 2020

作者： Yani, F. Nurhayati, O.D. Widodo, A.P. Department of Information System Post Graduated School Diponegoro University Indonesia Department of Computer Engineering Faculty of Engineering Diponegoro University Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Indonesia

It is currently thought that university websites play important roles in maintaining communication with stakeholders. The evidence shows that the usability aspect of the website positively correlates with governance support. This paper presents a new approach to identify, assess and evaluate usability aspect base on ten Heuristic Evaluation principles by implementing the ANP method. This method works by determining the weight of the best site criteria according to Webometric version ranking. The initial questionnaire was tested for validity and reliability using total item correlation analysis, the r-value was obtained in the range 0.706-0.919 (valid) and the reliability value in the range 0.861-0.939 (reliable). It was also found that by implementing expert judgment tests, some questionnaires are required more editorial adjustment. Interestingly, the layout of the websites hit the usability criteria. Another ten HE aspects run well while some light improvements were required for error prevention, recognition rather than recall, help users recognize, diagnose, and recover from errors aspects. The most remarkable result to emerge from the data was that visibility of system status, match between system and the real world, and consistency standards shown good result. © Published under licence by IOP Publishing Ltd.

关键词： Heuristic methods

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STMAE: Spatial Temporal Masked Auto-Encoder for Traffic Forecasting 27th

STMAE: Spatial Temporal Masked Auto-Encoder for Traffic For...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Wu, Xing Cai, Chengyou Wang, Xiaoxiao Wang, Jianjia Yao, Junfeng Qian, Quan Song, Jun School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai China Shanghai Shentong Metro Co. Ltd. Shanghai China School of AI and Advanced Computing XJTLU Entrepreneur College Xi’an Jiaotong-Liverpool University Suzhou China CSSC Seago System Technology Co. Ltd. Shanghai China Department of Geography Hong Kong Baptist University Hong Kong

ISBN: (纸本)9783031781681

The advancement of intelligent transportation systems underscores the importance of data-driven approaches in traffic forecasting, which plays a crucial role in tasks such as traffic signal control and route guidance, among others. However, the inherent uncertainty stemming from regional traffic dynamics, coupled with intricate spatio-temporal correlations, poses formidable challenges to accurate traffic prediction. Moreover, the complexities inherent in sequence forecasting across varying scales further exacerbate the accuracy dilemma. Recognizing the need for integrating information across spatial and temporal dimensions to enhance forecasting precision, a novel solution termed Spatial Temporal Masked Autoencoder (STMAE) is introduced. The STMAE framework addresses these challenges through a two-stage learning process. In the pre-training phase, an autoencoder architecture is employed to extract spatio-temporal features from the data. In the fine-tuning phase, the pre-trained encoder of the STMAE model undergoes further refinement to specifically target traffic forecasting tasks. Extensive evaluations validate the effectiveness of the proposed STMAE model. Notably, STMAE demonstrates competitive performance, achieving 3.32 Vehs MAE for long-term (60 min) traffic forecasting while operating within a reduced computational budget. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Budget control

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