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2023 Human-Centered Cognitive Systems, HCCS 2023

作者： Akhtar, Raybal Safyan, Muhammad Iqbal, Muddesar Sarwar, Sohail University of Management and Technology Department of Informatics and Systems Lahore Pakistan Government College University Lahore Department of Computer Science Lahore Pakistan Prince Sultan University Department of Communication & Network Engineering Riyadh Saudi Arabia Bahria University Islamabad Department of Computer Science Islamabad Pakistan

ISBN: (纸本)9798350359183

Online examination evaluation methods are used as an alternative to the traditional examination's way of evaluation methods. They offer a number of advantages while addressing issues associated with outdated conventional approaches. Online evaluation methods are mainly used for objective and short answers based exams but may not suitable for assessing the depth knowledge in candidates. So, candidate's descriptive examinations are conducted to assess their depth of knowledge. Descriptive evaluation methods have been put into practice for quite some time but they greatly rely on keyword-matching techniques between the questions and answers. Due to this limitation, the semantic meanings of these answers are ignored. In current research, the deficiencies in prevalent systems have been addressed by calculating the semantic and syntactic similarity between answers. Moreover, the repetitive words and similarity between counteractive answers has also been considered. We have used SQuAD1 dataset in current research. Our model has achieved a value of 0.88 in terms of accuracy for while computing similarity among listed items. © 2023 IEEE.

关键词： Semantics

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An Evaluation of Meteorological Variables Impact on Photovoltaic Power Generation Estimation Based on Deep Learning Model

An Evaluation of Meteorological Variables Impact on Photovol...

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Computing and Information Technology (ICCIT-1441), 2020 International Conference on

作者： Husein Mauladdawilah E.J. Gago M.C. Pegalajar Mohammed Balfaqih School of Civil Engineering University of Granada Granadea Spain Department of Computer Science and Artificial Intelligence University of Granada Granadea Spain Department of Computer and Network Engineering University of Jeddah Jeddah Saudi Arabia

ISBN: (数字)9798350353839

ISBN: (纸本)9798350353846

Accurate forecasting of photovoltaic (PV) power generation is essential for efficient grid integration and operation of solar energy systems. This study assesses a PV station in Scotland, UK, by analyzing the correlation between meteorological variables and power output. Two methods are employed: Pearson Correlation Coefficient and deep learning forecasting using Long Short-Term Memory (LSTM) networks. The study uses four datasets, each incorporating a different meteorological variable alongside historical PV power data. Evaluation metrics include Mean Squared Error (MSE), Normalized Root Mean Squared Error (NRMSE), R-squared (R2), and Mean Absolute Percentage Error (MAPE). The analysis reveals that global total irradiance has the strongest positive correlation (0.92) with PV output, followed by temperature (0.66). Wind speed and relative humidity show negative correlations (−0.35 and -0.74, respectively). The LSTM model, trained with a 10-day input window, demonstrates the highest coefficient of determination with temperature range variable (99.48 % ) and the lowest NRMSE (1.77 % ). These findings highlight the significance of meteorological factors in optimizing PV power generation in Scotland.

关键词： Photovoltaic systems Deep learning Temperature distribution Correlation Meteorological factors Wind speed Solar energy Predictive models Forecasting Long short term memory

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Facial Image Recognition Using Transfer Learning: A Brief Review

Facial Image Recognition Using Transfer Learning: A Brief Re...

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International Conference on Information and Communication Systems (ICICS)

作者： Omar Banimelhem Baghdad Al-Khateeb Department of Network Engineering and Security Jordan University of Science and Technology Irbid Jordan Department of Computer Engineering Jordan University of Science and Technology Irbid Jordan

ISBN: (数字)9798331540760

ISBN: (纸本)9798331540777

Accurate image recognition plays a pivotal role in a wide range of industrial applications. One domain of these applications is facial image recognition. Recently, deep learning (DL) models, which provides high efficiency and accuracy, have been utilized in facial image recognition applications. However, DL-based solutions in such applications need huge amount of data for training the model which will result in increasing the learning duration. Recently, the emergence of transfer learning (TL) has become an innovative solution in enhancing and improving the learning process in developing the machine learning (ML) models for facial image recognition-based applications. optimization of such *** is a kind of DL models which guarantee enhancements in the learning process where the TL-based models don’t need to start the training process from scratch. Moreover, TL ensures effective use of limited data by leveraging pre-trained models and start the learning process from a certain level. Therefore, TL developers can create accurate and powerful AI solutions faster and with fewer resources. This paper presents a brief review for the recently published works in the field of facial image recognition based on transfer learning. The review shows a description of the dataset used in the training process, methodology, and the performance results of each work. Moreover, it highlights the challenges of using TL in facial image recognition-based applications. Some future work directions are also presented in the paper.

关键词： Training Surveys Analytical models Image recognition Accuracy Reviews Face recognition

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High Gain and Efficiency Triple U-shaped Slots Microstrip Patch Antenna for 5G Applications 3

High Gain and Efficiency Triple U-shaped Slots Microstrip Pa...

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3rd International Conference on Computing and Information Technology, ICCIT 2023

作者： Almohammedi, Akram A. Raad, Ahmad Darshi, Sam Shepelev, Vladimir Mohd Yusof, Mohammad Hafiz Balfaqih, Mohammed Karabük University Electrical & Electronics Department Karabük Turkey South Ural State University Automobile Transportation Department Chelyabinsk Russia Karabük University Electrical & Electronics Engineering Department Karabük Turkey Indian Institute of Technology Ropar Department of Electrical Engineering Punjab India Universiti Teknologi Mara Faculty of Computer and Mathematical Sciences Perak Malaysia University of Jeddah Department of Computer and Network Engineering Jeddah23218 Saudi Arabia

ISBN: (纸本)9798350321487

The 28 GHz band is a frequency band that has been allocated for use in 5G mobile communication networks. It is part of the millimeter wave spectrum, which is a range of frequencies between 30 GHz and 300 GHz. This study proposes and investigates the 28 GHz 5G networks. A modified single element patch antenna with three grooved U-shaped holes is shown and is used to indicate a high gain and Efficiency for 28 GHz 5G antenna. The proposed antenna consists of the radiation element on a RTRogers 5880 laminate and is actuated by a microstrip feedline. The proposed work includes the most desirable characteristics, such as small size, light weight, low-cost fabrication and wide operation up to 1.4 GHz (27.1 - 28.5 GHz). The proposed antenna design also offers a high efficiency up to 89.73 %, high gain up to 8.14 dBi, and return loss up to -30 dB, resulting in attractive performance. The results obtained show that the antenna is a viable candidate for 5G applications at 28 GHz. © 2023 IEEE.

关键词： 5G mobile communication systems

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Validating Perception of Hyperspectral Textures in Virtual Reality Systems

Validating Perception of Hyperspectral Textures in Virtual R...

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24th Eurographics Conference on Visualization, EuroVis 2022

作者： Díaz-Barrancas, F. Cwierz, H. Gil-Rodríguez, R. Pardo, P.J. Department of Psychology Justus-Liebig Universität Germany Department of Computer and Network Systems Engineering University of Extremadura Spain

ISBN: (纸本)9783038681854

Virtual reality (VR) environments are increasingly offering higher quality content. They use different computing techniques to improve the final user experience. In this work, we create different light sources and introduce hyperspectral textures for the object reflectance to boost the VR environment's quality. In addition, we perform a quantitative study to demonstrate that hyperspectral textures improve the final quality of the content in virtual reality systems. © 2022 The Author(s) Eurographics Proceedings © 2022 The Eurographics Association.

关键词： Textures

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Satellite-UAV networks for 6G Control: A Sensing-Communication-Computing-Control Closed Loop Perspective

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IEEE network 2025年

作者： Lei, Chengleyang Fang, Xinran Feng, Wei Chen, Yunfei Xiao, Ming Ge, Ning Mao, Shiwen The Department of Electronic Engineering State Key Laboratory of Space Network and Communications Tsinghua University Beijing100084 China The Department of Engineering University of Durham DurhamDH1 3LE United Kingdom The Department of Information Science and Engineering School of Electrical Engineering and Computer Science Royal Institute of Technology Sweden The Department of Electrical and Computer Engineering Auburn University AuburnAL36849 United States

The future sixth-generation (6G) networks are envisioned to support machines and robots besides human beings. In order to efficiently support machines and robots working in remote and post-disaster areas, satellites and unmanned aerial vehicles (UAVs) can be utilized. In this article, we investigate how satellite-UAV networks can serve robots for their control tasks. We introduce the typical use cases of the satellite-UAV networks for control and outline the relevant challenges. The control process usually involves sensing, communication, computing, and control components, which forms a sensing-communication-computing-control (SC3) closed loop. In analogy with the reflex arc structure of humans, we reveal the indivisibility of the SC3 closed loops and propose a closed-loop-oriented system design framework. Within this framework, we take the closed-loop control performance as the design target, and highlight the holistic consideration of sensing, communication, computing, and control components in the SC3 closed loop. Furthermore, we discuss the extended SC3 closed loop with multiple sensors and robots to decompose complex control systems. A case study is provided to show the performance gain of the proposed closed-loop-oriented system design. Finally, we outline open issues in designing more efficient satellite-UAV networks for control. ©1986-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Optimizing network Resilience with Segment Routing: A Comparative Study of SR TI-LFA and rLFA

Optimizing Network Resilience with Segment Routing: A Compar...

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Sciences and Techniques of Automatic Control and computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Adel Ali Eluheshi Mahmud Mansour Najia Ben Saud Department of Electrical Engineering and Computer Libyan Academy Tripoli Libya Department of Network University of Tripoli Tripoli Libya

ISBN: (数字)9798350372632

ISBN: (纸本)9798350372649

network operators are confronted with the demanding requirements resulting from the evolution of IP networks. As a result, it has become necessary to provide rigorous Service Level Agreements (SLAs) that are in line with these requirements. However, traditional IP networks lack the necessary flexibility, scalability, and manageability to meet these demands. In order to address these limitations, the Segment Routing (SR) architecture has been developed. SR is based on source-routing and tunneling paradigms, which enable IP/MPLS and IPV6 networks to operate in a simplified and more scalable manner. The focus of this paper is on network protection (resiliency) using Topology Independent Loop-Free Alternatives Fast Re-Route (TI-LFA FRR) using MPLS as underly technology. SR overcomes the limitations of previous network protection mechanisms in terms of coverage and optimal path selection. To show the effectiveness of SR TI-LFA in comparison to its predecessor, Remote Loop-Free Alternate (rLFA), we have implemented various scenarios. These scenarios are designed to highlight the superior capabilities of TI-LFA.

关键词： Scalability Maintenance engineering Tunneling Routing Routing protocols Topology IP networks

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Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games

Conjectural Online Learning with First-order Beliefs in Asym...

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IEEE Conference on Decision and Control

作者： Tao Li Kim Hammar Rolf Stadler Quanyan Zhu Department of Electrical and Computer Engineering New York University USA Division of Network and Systems Engineering KTH Royal Institute of Technology Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Asymmetric information stochastic games (AISGs) arise in many complex socio-technical systems, such as cyberphysical systems and IT infrastructures. Existing computational methods for AISGs are primarily offline and can not adapt to equilibrium deviations. Further, current methods are limited to particular information structures to avoid belief hierarchies. Considering these limitations, we propose conjectural online learning (COL), an online learning method under generic information structures in AISGs. COL uses a forecaster-actorcritic (FAC) architecture, where subjective forecasts are used to conjecture the opponents’ strategies within a lookahead horizon, and Bayesian learning is used to calibrate the conjectures. To adapt strategies to nonstationary environments based on information feedback, COL uses online rollout with cost function approximation (actor-critic). We prove that the conjectures produced by COL are asymptotically consistent with the information feedback in the sense of a relaxed Bayesian consistency. We also prove that the empirical strategy profile induced by COL converges to the Berk-Nash equilibrium, a solution concept characterizing rationality under subjectivity. Experimental results from an intrusion response use case demonstrate COL’s faster convergence over state-of-the-art reinforcement learning methods against nonstationary attacks.

关键词： Learning systems Sociotechnical systems Games Reinforcement learning computer architecture Cyber-physical systems Cost function Bayes methods Convergence

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A Systematic Review of the Future of Education in Perspective of Block Chain

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Journal of Mobile Multimedia 2025年第5期19卷 1221-1254页

作者： Shams Tabrez Siddiqui Haneef Khan Md Imran Alam Kamal Upreti Sarika Panwar Sheela Hundekari Department of Computer Science Jazan University Saudi Arabia Department of Computer and Network Engineering Jazan University Saudi Arabia CHIRST (Deemed to be University) Ghaziabad India Department of Electronics and Telecommunication Engineering AISSMS's Institute of Information Technology Pune India MIT ADT University Pune India

Blockchain is one of the most revolutionary technologies in the past decade due to its decentralisation, data integrity, reliability, and security. Blockchain technology is the next popular topic, and it has the potential to significantly alter the educational environment in many ways. Blockchain technology must be used in the education sector despite its challenges. Education is one of the sectors where blockchain-based solutions are still in use. Many academics possess extensive knowledge of the societal benefits blockchain technology might bring. The vast potential of blockchain can only be realised if education expands its knowledge of the technology. The primary goal of this research is to identify current problems related to educational institutions and identify blockchain features that could assist in addressing them. This research article will provide an overview of existing activities and address several perspectives on how blockchain can revolutionize the education sector. In prolongation, this article investigates the categories of blockchain technology applications, especially in the field of education. An in-depth discussion on the benefits and impact that blockchain brings to education is explored. Further, deliberate the abundant challenges of adopting blockchain in education. This study will direct the organizations/institutions to decide which blockchain application will benefit the most based on their requisites. The analysis will also provide information about other educational fields that may benefit from blockchain technology.

关键词： Privacy Electronic learning Federated learning Scalability Education Blockchains Security Reliability Secure storage Systematic literature review

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Continual learning with Bayesian model based on a fixed pre-trained feature extractor

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Visual Intelligence 2023年第1期1卷 1-14页

作者： Yang, Yang Cui, Zhiying Xu, Junjie Zhong, Changhong Zheng, Wei-Shi Wang, Ruixuan School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Department of Network Intelligence Peng Cheng Laboratory Shenzhen China Key Laboratory of Machine Intelligence and Advanced Computing MOE Guangzhou China

Deep learning has shown its human-level performance in various applications. However, current deep learning models are characterized by catastrophic forgetting of old knowledge when learning new classes. This poses a challenge such as in intelligent diagnosis systems where initially only training data of a limited number of diseases are available. In this case, updating the intelligent system with data of new diseases would inevitably downgrade its performance on previously learned diseases. Inspired by the process of learning new knowledge in human brains, we propose a Bayesian generative model for continual learning built on a fixed pre-trained feature extractor. In this model, knowledge of each old class can be compactly represented by a collection of statistical distributions, e.g., with Gaussian mixture models, and naturally kept from forgetting in continual learning over time. Unlike existing class-incremental learning methods, the proposed approach is not sensitive to the continual learning process and can be additionally well applied to the data-incremental learning scenario. Experiments on multiple medical and natural image classification tasks reveal that the proposed approach outperforms state-of-the-art approaches that even keep some images of old classes during continual learning of new classes. © The Author(s) 2023.

关键词： Bayesian model Continual learning Fixed feature extractor Generative approach

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