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TechRxiv 2020年

作者： Brohi, Sarfraz Nawaz Jhanjhi, N.Z. Brohi, Nida Nawaz Brohi, Muhammad Nawaz School of Computer Science and Engineering Taylor’s University Selangor Malaysia Faculty of Medicine and Biomedical Sciences MAHSA University Selangor Malaysia Department of Creative Computing Bath Spa University Ras Al Khaimah United Arab Emirates

COVID-19 has stunned the global economy and threatened human life. Due to rapidly emerging fatalities and enormous cases appearing every day, researchers across the globe are producing significant contributions to mitigate this pandemic. Besides the race for discovering a vaccine and treatment for COVID-19, there is utmost focus on flattening the curve by undertaking appropriate measures. The remarkable role of frontline medical practitioners, who are eagerly treating the affected people will be penned in the history books. The efforts of scientists and technologists will be remembered for their extraordinary contributions to assist healthcare professionals and governments in mitigating the threats of COVID-19. Leading technology firms have formed consortiums and research groups, which provide funding and free access to supercomputers for solving complex computational problems to eliminate COVID-19. In this research, we have unveiled five state-of-the-art technologies and their remarkable applications that can be used to mitigate and eliminate the problems of COVID-19. These technologies include Artificial Intelligence (AI), 3D Printing Technology (3DPT), Big Data Analytics (BDA), High Performance computing (HPC) and Telecommunication Technology (TT). This research investigates the use of technology to encounter COVID-19 and aims to serve as the primary reference for promoting future research as well as developments to produce solutions for COVID-19 using AI, 3DPT, BDA, HPC and TT. © 2020, CC BY-NC-SA.

关键词： COVID-19

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The enhanced light extraction Top-emitting Organic Light-emitting Diode based on metallic grating anode

The enhanced light extraction Top-emitting Organic Light-emi...

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第9届纳米操纵、制造与测量国际会议

作者： Dun Qiao Kang Li Nigel Copner Yongkang Gong Faculty of Computing Engineering and ScienceUniversity of SouthwalesUK School of Physics and Astronomy Cardiff UniversityUK

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Framing in computational creativity - A survey and taxonomy 10

Framing in computational creativity - A survey and taxonomy

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10th International Conference on Computational Creativity, ICCC 2019

作者： Cook, Michael Colton, Simon Pease, Alison Llano, Maria Theresa School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom SensiLab Faculty of Information Technology Monash University Australia Department of Computing University of Dundee United Kingdom Goldsmiths University of London United Kingdom

ISBN: (纸本)9789895416011

The notion of framing computationally created artefacts - by providing a narrative context for the actions and motivations of the software - is an important part of building computationally creative software. In this paper we provide the first survey of framing in computational creativity;we provide a taxonomy of framing elements, covering motivation, implementation and rendering;and we look at future directions for framing, as well as its importance for the field's future. © ICCC 2019.

关键词： Taxonomies

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Enhanced PEMFC parameter estimation using a hybrid gorilla troops optimizer and honey badger algorithm

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Computers and Chemical engineering 2025年 201卷

作者： Aljaidi, Mohammad Agrawal, Sunilkumar P. Agrawal, Toshika R. Pandya, Sundaram B. Parmar, Anil Jangir, Pradeep Arpita Gulothungan, G. Alshammari, Muteb Jangid, Reena Department of Computer Science Faculty of Information Technology Zarqa University Zarqa 13110 Jordan Department of Electrical Engineering Government Engineering College Gujarat Gandhinagar 382028 India Department of Civil Engineering Government Polytechnic for Girls Ahmedabad 380009 India Department of Electrical Engineering Shri K.J. Polytechnic Bharuch 392 001 India Department of Electrical and Electronics Engineering J.J. College of Engineering and Technology Tamilnadu Tiruchirappalli India Innovation Center for Artificial Intelligence Applications Yuan Ze University Taoyuan 320315 Taiwan Applied Science Research Center Applied Science Private University Amman 11937 Jordan Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602 105 India Jadara University Research Center Jadara University Irbid Jordan Department of Electronics and Communication Engineering SRM Institute of Science and Technology SRM Nagar Kattankulathur Tamilnadu Chengalpattu 603203 India Department of Information Technology Faculty of Computing and Information Technology Northern Border University Arar Saudi Arabia Department of CSE Graphic Era Hill University Dehradun 248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun 248002 India Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India

The optimization of proton exchange membrane fuel cell (PEMFC) parameters is crucial for improving performance, durability, and efficiency across various applications. However, existing metaheuristic algorithms face limitations such as slow convergence, susceptibility to local optima, and high computational costs. To address these issues, this study proposes a hybrid Artificial Gorilla Troops Optimizer and Honey Badger Algorithm (GTOHBA) to enhance PEMFC parameter estimation. The proposed algorithm integrates the efficient global search of GTO with the adaptive foraging behavior of HBA, ensuring better exploration-exploitation balance. The performance of GTOHBA was evaluated on six different PEMFC models: BCS 500 W, SR-12, Horizon H-12, Nedstack 600 W PS6, STD 250 W and Ballard Mark V. The results demonstrate that GTOHBA achieved the lowest sum of squared errors (SSEmin = 0.025493) with an exceptionally low standard deviation (SSESD = 8.35×10⁻⁶), outperforming other state-of-the-art optimization methods. Moreover, GTOHBA exhibited superior computational efficiency with the shortest runtime (0.179909 s), significantly reducing the computational burden compared to PSO and MFO. The theoretical analysis confirms that GTOHBA effectively mitigates issues of premature convergence and enhances parameter extraction accuracy through its hybrid structure. Practically, the algorithm enables precise modeling of PEMFC behavior, improving power output predictions with minimal absolute error (AE = 0.012913) and percentage relative error ( %RE = 0.061363 %). The key benefit for readers is the demonstration of a robust, fast, and highly accurate optimization framework for PEMFC parameter estimation. However, further research is needed to assess GTOHBA's adaptability under dynamic real-time conditions and large-scale fuel cell stacks.

关键词： Artificial gorilla troops optimizer (GTO) Honey badger algorithm (HBA) Metaheuristic optimization Parameter estimation Proton exchange membrane fuel cell (PEMFC) Sum of squared errors (SSE)

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Comparative evaluation of the performance properties of resin-infused plain-woven jute reinforced thermoset composites for energy infrastructure: Experimental analysis, finite element modelling and statistical validation

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Results in engineering 2025年 26卷

作者： Owen, Macaulay M. Wong, Leong Sing Achukwu, Emmanuel O. Romli, Ahmad Zafir Ametefe, Divine Senanu Shuib, Solehuddin Institute of Energy Infrastructure IEI Universiti Tenaga Nasional UNITEN Jalan IKRAM-UNITEN Selangor Kajang 43000 Malaysia Department of Polymer and Textile Technology Yaba College of Technology Lagos 101212 Nigeria Department of Civil Engineering College of Engineering Universiti Tenaga Nasional UNITEN Jalan IKRAM-UNITEN Selangor Kajang 43000 Malaysia School of Computing Engineering and Technology Robert Gordon University Sir Ian Wood Building Garthdee Road Aberdeen AB10 7GJ United Kingdom Department of Polymer and Textile Engineering Faculty of Engineering Ahmadu Bello University Zaria Nigeria Centre of Chemical Synthesis and Polymer Composites Research & Technology Institute of Science IOS Universiti Teknologi MARA UiTM Selangor Shah Alam 40450 Malaysia Faculty of Applied Science Universiti Teknologi MARA UiTM 40450 Shah Alam Selangor Malaysia School of Electrical Engineering College of Engineering Universiti Teknologi MARA UiTM Selangor Shah Alam 40450 Malaysia School of Machanical Engineering College of Engineering Universiti Teknologi MARA UiTM Selangor Shah Alam 40450 Malaysia

This study presents a comprehensive experimental and numerical evaluation of resin-infused plain-woven jute fiber composites reinforced with thermoset epoxy and polyester matrices in 2-, 4-, and 6-ply configurations, produced via vacuum-assisted resin infusion. The aim is to assess the influence of matrix type and ply architecture on the mechanical, thermal, and microstructural behavior of sustainable composites for renewable energy infrastructure. Mechanical characterization involved tensile, flexural, impact, and hardness tests, while thermal and microstructural properties were evaluated using thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). Finite Element Analysis (FEA) was used to simulate stress distribution, and Analysis of Variance (ANOVA) determined the statistical significance of ply count and matrix effects. The 6-ply epoxy composite exhibited the highest structural performance, achieving tensile and flexural strengths of 76.85 MPa and 90.48 MPa with improvements of 19.3 % and 31.8 % over polyester counterparts. Although polyester-based composites exhibited lower strength, they showed higher impact resistance (1.15 J, +33.9 %). Peak hardness (114.4 HRB) was recorded in 4-ply epoxy laminates, and density increased with ply count, with polyester showing slightly higher values. TGA confirmed enhanced thermal stability in epoxy systems, with onset degradation at 341.5 °C versus 304.3 °C in polyester. SEM revealed superior fiber–matrix bonding and fewer voids in epoxy composites. FEA predictions were within 5 % of experimental results, and ANOVA confirmed statistically significant effects (p ≤ 0.05) of matrix and ply count. These findings position 6-ply epoxy laminates as promising candidates for structural applications in renewable energy systems. © 2025 The Author(s)

关键词： Finite element analysis Plain-woven jute Statistical analysis Thermoset resin Vacuum-assisted resin infusion

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Vision, challenges, roles and research issues of Artificial Intelligence in Education

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Computers and Education: Artificial Intelligence 2020年 1卷

作者： Hwang, Gwo-Jen Xie, Haoran Wah, Benjamin W. Gašević, Dragan Graduate Institute of Digital Learning and Education National Taiwan University of Science and Technology Taiwan Department of Computing and Decision Sciences Lingnan University Hong Kong Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Faculty of Information Technology Monash University Australia

The rapid advancement of computing technologies has facilitated the implementation of AIED (Artificial Intelligence in Education) applications. AIED refers to the use of AI (Artificial Intelligence) technologies or application programs in educational settings to facilitate teaching, learning, or decision making. With the help of AI technologies, which simulate human intelligence to make inferences, judgments, or predictions, computer systems can provide personalized guidance, supports, or feedback to students as well as assisting teachers or policymakers in making decisions. Although AIED has been identified as the primary research focus in the field of computers and education, the interdisciplinary nature of AIED presents a unique challenge for researchers with different disciplinary backgrounds. In this paper, we present the definition and roles of AIED studies from the perspective of educational needs. We propose a framework to show the considerations of implementing AIED in different learning and teaching settings. The structure can help guide researchers with both computers and education backgrounds in conducting AIED studies. We outline 10 potential research topics in AIED that are of particular interest to this journal. Finally, we describe the type of articles we like to solicit and the management of the submissions. © 2020 The Author(s)

关键词： Application programs

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The Impact and Modelling of Concentrated Butt-Joints on Vertically Laminated Bamboo-Timber Hybrid Bio-Flitch Beams

Research Square

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Research Square 2021年

作者： Zhang, Hexin Gharavi, Niaz Wong, Simon H.F. Deng, Yu Bahadori-Jahromi, Ali Limkatanyu, Suchart Qiao, Yao Kuang, J.S. School of Engineering and the Built Environment Edinburgh Napier University 10 Colinton Road Edinburgh ScotlandEH10 5DT United Kingdom Department of Construction Technology and Engineering Technological Higher Education Institute of Hong Kong 20A Tsing Yi Road Tsing Yi Island New Territories Hong Kong School of Civil Engineering and Architecture Guangxi University of Science and Technology Liuzhou545006 China Department of Civil Engineering and Built Environment School of Computing and Engineering University of West London LondonW5 5RF United Kingdom Department of Civil Engineering Faculty of Engineering Prince of Songkla University Songkla Thailand Pacific Northwest National Laboratory RichlandWA99354 United States Department of Civil and Environmental Engineering Hong Kong University of Science and Technology Kowloon Hong Kong

This paper presents the experimental and analytical studies to investigate the impact of concentrated laminated bamboo butt-joints on the flexural properties of vertically laminated bamboo-timber hybrid beams (VLHBs, or flitch beam). The experimental results reveal that the concentrated butt-joints significantly reduce the flexural strength of the VLHB. They also suggest that the failure mechanism of the VLHBs with or without concentrated butt-joints are completely different. In addition, laminated bamboo lumber with concentrated butt-joints was found to be unsuitable for structural applications. The analytical estimations show close agreement with the experimental results. However, due to the layout of the sample VLHB, the experimental study cannot confirm the impact of the butt-joints on the modulus of elasticity in bending. © 2021, CC BY.

关键词： Bamboo

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Correction: Hand drawn capacitive proximity/touch sensors

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Journal of Materials science: Materials in Electronics 2025年第12期36卷 1-1页

作者： Srivatava, Vinit Thakur, Abhay Singh Vaish, Rahul Rajpurohit, Bharat Singh Awwad, Nasser S. Ibrahium, Hala A. kebaili, Imen Boukhris, Imed School of Computing and Electrical Engineering Indian Institute of Technology Mandi Mandi India School of Mechanical and Materials Engineering Indian Institute of Technology Mandi Mandi India Central Labs King Khalid University Abha Saudi Arabia Chemistry Department Faculty of Science King Khalid University Abha Saudi Arabia Biology Department Faculty of Science King Khalid University Abha Saudi Arabia Department of Physics Faculty of Science King Khalid University Abha Saudi Arabia Laboratoire de Physique Appliquée Groupe de Physique des matériaux luminescents Faculté des Sciences de Sfax Département de Physique Université de Sfax Sfax Tunisia Laboratoire des matériaux composites céramiques et polymères (LaMaCoP) Département de Physique Faculté des sciences de Sfax Université de Sfax Sfax Tunisia

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A Scalable Color-Based Caching Scheme in Telco-CDNs 15

A Scalable Color-Based Caching Scheme in Telco-CDNs

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15th International Conference on Network and Service Management, CNSM 2019

作者： Tran, Anh-Tu Ngoc Diep, Thanh-Dang Nakajima, Takuma Yoshimi, Masato Thoai, Nam Ho Chi Minh City University of Technology VNUHCM High Performance Computing Laboratory Faculty of Computer Science and Engineering Viet Nam Service Strategy Sector Strategic Technology Center TIS Inc. Shinjuku-ku Japan

ISBN: (纸本)9783903176249

Internet traffic is growing quickly, and it is majorly contributed by the proliferation of video services. Content Delivery Networks (CDNs) reduce the video traffic by storing replicas of videos in their cache servers. Nonetheless, the cache servers are usually located outside Internet Service Providers (ISPs). This implies that CDNs cannot reduce the video traffic inside ISP networks. To mitigate this issue, many ISPs build their own CDNs called Telco-CDNs. Genetic Algorithm-based caching is deemed the best approach in terms of traffic reduction. However, it is not practical since its computation time to generate content allocations is extremely long even when using a cluster. A color-based approach was devised to help overcome the drawback at the expense of its increase in traffic. Nevertheless, in case the number of content categories or requests proliferates quickly, the approach also has the same limitation like the Genetic Algorithm-based caching. To resolve the limitation, we propose two novel techniques to hamper the increase in the computation time. One is able to cope with the situation when the number of content categories increases while the other can deal with the circumstance when the number of requests rises. The empirical results show that the computation time is reduced 5x for the former and 7x for the latter at the expense of 1% and 12% increase in traffic for a problem of 5,000 contents, respectively. © 2019 IFIP.

关键词： Internet service providers

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Mobile-based skin lesions classification using convolution neural network

Annals of Emerging Technologies in Computing

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Annals of Emerging Technologies in computing 2020年第2期4卷 26-37页

作者： Hameed, Nazia Shabut, Antesar Hameed, Fozia Cirstea, Silvia Harriet, Sorrel Hossain, Alamgir School of Computer Science University of Nottingham Jubilee Campus Nottingham United Kingdom School of School of Arts and Communication Leeds Trinity University Leeds United Kingdom Computer Science Department King Khalid University Abha Saudi Arabia Faculty of Science and Engineering Anglia Ruskin University Cambridge United Kingdom School of Computing and Digital Technology Teesside University Middlesbrough United Kingdom

Received: 25th January 2020;Accepted: 7th March 2020;Published: 1st April 2020 Abstract: This research work is aimed at investing skin lesions classification problem using Convolution Neural Network (CNN) using cloud-server architecture. Using the cloud services and CNN, a real-time mobile-enabled skin lesions classification expert system "i-Rash" is proposed and developed. i-Rash aimed at early diagnosis of acne, eczema and psoriasis at remote locations. The classification model used in the "i-Rash" is developed using the CNN model "SqueezeNet". The transfer learning approach is used for training the classification model and model is trained and tested on 1856 images. The benefit of using SqueezeNet results in a limited size of the trained model i.e. only 3 MB. For classifying new image, cloud-based architecture is used, and the trained model is deployed on a server. A new image is classified in fractions of seconds with overall accuracy, sensitivity and specificity of 97.21%, 94.42% and 98.14% respectively. i-Rash can serve in initial classification of skin lesions, hence, can play a very important role early classification of skin lesions for people living in remote areas. © 2020 by the author(s).

关键词： Expert systems

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