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Collaborative learning-based inter-dependent task dispatching and co-location in an integrated edge computing system

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Digital Communications and Networks 2024年第6期10卷 1837-1850页

作者： Uchechukwu Awada Jiankang Zhang Sheng Chen Shuangzhi Li Shouyi Yang School of Software Henan Institute of Science and TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China Department of Computing and Informatics Bournemouth UniversityPoole BH125BBUK School of Electronics and Computer Science University of SouthamptonSouthampton SO171BJUK Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266100China

Recently,several edge deployment types,such as on-premise edge clusters,Unmanned Aerial Vehicles(UAV)-attached edge devices,telecommunication base stations installed with edge clusters,etc.,are being deployed to enable faster response time for latency-sensitive *** fundamental problem is where and how to offload and schedule multi-dependent tasks so as to minimize their collective execution time and to achieve high resource *** approaches randomly dispatch tasks naively to available edge nodes without considering the resource demands of tasks,inter-dependencies of tasks and edge resource *** approaches can result in the longer waiting time for tasks due to insufficient resource availability or dependency support,as well as provider ***,we present Edge Colla,which is based on the integration of edge resources running across multi-edge *** Colla leverages learning techniques to intelligently dispatch multidependent tasks,and a variant bin-packing optimization method to co-locate these tasks firmly on available nodes to optimally utilize *** experiments on real-world datasets from Alibaba on task dependencies show that our approach can achieve optimal performance than the baseline schemes.

关键词： Edge computing Collaborative learning Resource utilization Execution time Edge federation Gang scheduling

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Technology Usage for Education: Polytechnic Deaf or Hard-of-Hearing Student 6

Technology Usage for Education: Polytechnic Deaf or Hard-of-...

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6th IEEE Symposium on Computers and informatics, ISCI 2024

作者： Rahim, Rini Hafzah Abdul Nizam, Dinna Nina Mohd Naim, Nur Faraha Mohd Baharum, Aslina Universiti Malaysia Sabah User Experience Group Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia Sunway University Computing and Information System School of Engineering and Technology Selangor Malaysia

ISBN: (纸本)9798350353853

This article investigates the application of technology to enhance education for polytechnic deaf or hard-of-hearing (DHH) students. Polytechnic institutions play a crucial role in preparing students for diverse careers through hands-on, practical education. However, DHH students face unique challenges in accessing and fully participating in polytechnic programs. To provide a diverse approach, the technology focusing on visual technology, such as Augmented Reality and Virtual Reality, incorporates crucial components suitable for DHH visual learning modalities. The study uses a mixed-method approach, integrating questionnaires, interviews, and observational data to discover more about DHH lecturers' and students' preferred learning methods. 77 DHH Sijil Khas Operasi Katering student from selected three Polytechnic and Community Colleges gave their feedback from questionnaires, and five lecturers were interviewed to get a clearer picture of the current usage of technology among DHH students at polytechnic and community college. Results of the lecturer's interview suggest that DHH students need visual aids, communication tools, and focus-enhancing resources to help them learn effectively, especially in cooking classes where understanding kitchen equipment and safety is crucial to prevent injuries. Meanwhile, results from DHH students' questionnaires show students' interest and prefer to use technology, with 88% agreeing to use technology such as Games, AR, VR and AR Games for their teaching and learning process and to make their learning process more interesting, fun and enjoyable. Integrating the use of technology and information technology as part of the approach of teaching aids to deaf students is hoped to help them to understand better, focus and have more fun in learning. © 2024 IEEE.

关键词： Augmented reality

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Quantum Particle Swarm Optimization Based Convolutional Neural Network for Handwritten Script Recognition

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Computers, Materials & Continua 2022年第6期71卷 5855-5873页

作者： Reya Sharma Baijnath Kaushik Naveen Kumar Gondhi Muhammad Tahir Mohammad Khalid Imam Rahmani School of Computer Science and Engineering SMVDUJ&KIndia College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia

Even though several advances have been made in recent years,handwritten script recognition is still a challenging task in the pattern recognition *** field has gained much interest lately due to its diverse application ***,different methods are available for automatic script *** most of the reported script recognition techniques,deep neural networks have achieved impressive results and outperformed the classical machine learning ***,the process of designing such networks right from scratch intuitively appears to incur a significant amount of trial and error,which renders them *** approach often requires manual intervention with domain expertise which consumes substantial time and computational *** alleviate this shortcoming,this paper proposes a new neural architecture search approach based on meta-heuristic quantum particle swarm optimization(QPSO),which is capable of automatically evolving the meaningful convolutional neural network(CNN)*** computational experiments have been conducted on eight different datasets belonging to three popular Indic scripts,namely Bangla,Devanagari,and Dogri,consisting of handwritten characters and ***,the results imply that the proposed QPSO-CNN algorithm outperforms the classical and state-of-the-art methods with faster prediction and higher accuracy.

关键词： Neuro-evolution quantum particle swarm optimization deep learning convolutional neural networks handwriting recognition

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An Effective Hybrid Metaheuristic Algorithm for Solving Global Optimization Algorithms

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Multimedia Tools and Applications 2024年第37期83卷 85103-85138页

作者： Seyyedabbasi, Amir Tareq Tareq, Wadhah Zeyad Bacanin, Nebojsa Computer Engineering Deptartment Faculty of Engineering and Natural Sciences Istinye University Istanbul Turkey Department of Mathematics Saveetha School of Engineering SIMATS Thandalam Tamilnadu India Faculty of Informatics and Computing Singidunum University Belgrade Serbia MEU Research Unit Middle East University Amman Jordan

Recently, the Honey Badger Algorithm (HBA) was proposed as a metaheuristic algorithm. Honey badger hunting behaviour inspired the development of this algorithm. In the exploitation phase, HBA performs poorly and stagnates at the local best solution. On the other hand, the sand cat swarm optimization (SCSO) is a very competitive algorithm compared to other common metaheuristic algorithms since it has outstanding performance in the exploitation phase. Hence, the purpose of this paper is to hybridize HBA with SCSO so that the SCSO can overcome deficiencies of the HBA to improve the quality of the solution. The SCSO can effectively exploit optimal solutions. For the research conducted in this paper, a hybrid metaheuristic algorithm called HBASCSO was developed. The proposed approach was evaluated against challenging CEC benchmark instances taken from CEC2015, CEC2017, and CEC2019 benchmark suites The HBASCSO is also evaluated concerning the original HBA, SCSO, as well as several other recently proposed algorithms. To demonstrate that the proposed method performs significantly better than other competitive algorithms, 30 independent runs of each algorithm were evaluated to determine the best, worst, mean, and standard deviation of fitness functions. In addition, the Wilcoxon rank-sum test is used as a non-parametric comparison, and it has been found that the proposed algorithm outperforms other algorithms. Hence, the HBASCSO achieves an optimum solution that is better than the original algorithms. © The Author(s) 2024.

关键词： Benchmarking

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A Quantum Abacus for Teaching Quantum Algorithms 53

A Quantum Abacus for Teaching Quantum Algorithms

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： German, Dan-Adrian Pias, Marcelo Xiang, Qiao Kuruvadi, Sreesha Srinivasan Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Rio Grande do Sul Brazil Xiamen University School of Informatics Fujian Xiamen China

ISBN: (纸本)9798350336429

At the time of this writing more than 60 (sixty) companies in the world are building quantum computers. These computers, based on quantum physics principles, are radically different from those that operate according to the more familiar principles of classical physics. A quantum algorithm takes a number of classical bits as its input, manipulates them so as to create a superposition of all their possible states, further manipulates this exponentially large superposition to obtain the final quantum result, and then measures the result to get (with the appropriate probability distribution) the same number of output bits as in its input. For the middle phase, there are elementary operations which count as one step and yet manipulate all the exponentially many amplitudes of the superposition. The natural language of these quantum gates is that of linear algebra in a complex (Hilbert) vector space. Since 2017 it is known that it is possible to replace the linear algebra with some string-rewriting rules which are no more complicated than the basic rules of arithmetic. The original system was introduced by Terry Rudolph and has been promoted and disseminated in large-scale outreach projects (among others) by Diana Franklin (University of Chicago) and Sofia Economou and Ed Barnes (Virginia Tech) as well as several other educators at the high-school level. In this paper we show how a slightly modified (though still very elementary) system can be used to communicate a visual and entirely operational understanding of key quantum computation concepts such as: superposition, probability, entanglement, phase, interference and unitary state evolution, as they occur in well-known quantum algorithms. We give concrete examples of proving properties for quantum gates and quantum circuits without resorting at all to complex numbers or matrix multiplication. Only simple, abacus-like operations are used-hence the title of the paper. The system we present allows a novice learner to actual

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Can Language Models Identify Use of PII Data Types in Code

SSRN

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SSRN 2024年

作者： Aniruddha Gurjar, Ambarish Jean, L. Camp Ringenberg, Tatiana Ma, Xinyao Anesu, Chaora Luddy School of Informatics Computing and Engineering United States School of Informatics and Computing United States Indiana University Bloomington School of Informatics and Computing United States

Developers regularly rely on third party code obtained from collaborative software platforms and code management systems. Despite the benefits and efficiency, this introduces potential security and privacy risks. The identification of security vulnerabilities and security risks in dependencies has received more attention than the identification of privacy risks, which we address here. Specifically, we focus on the privacy risks created with the inclusion of data which has been identified as private or personally identifiable. The challenge of identifying privacy risk is amplified by the overlapping but disjoint definitions of privacy across jurisdictions, so that that code developed in one region or for one use context may inadvertently result in compliance and privacy risks in another regulatory context. We describe the feasibility of using a range of approaches, from string matching through different types of Natural Language Processing (NLP), to automate the detection of privacy sensitive source code references. We leverage the categorical definitions in the General Data Privacy Regulation (GDPR) and California Consumer Privacy Act (CCPA) to define sensitivity. We argue that current commercial methods are insufficient to capture the nuanced nature of privacy risks in code. To test the potential of NLP approaches, we developed a modest labeled corpus of 97 code snippets from GitHub, encompassing both sensitive and non-sensitive control data. We report on the effectiveness of different NLP-based models, including fine-tuned BERT-based models such as CodeBERT and GraphCodeBERT, and large language models such as ChatGPT and Google BARD. Our analysis reveals that advanced systems do not necessarily offer superior accuracy, with fine-tuned models reaching 86% accuracy, and larger language models not exceeding 72%. These findings provide insights into potential areas for enhancing the automation of privacy-sensitive information detection in code, given the challenges un

关键词： Data privacy

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Comparative Analysis of Filtering Techniques in Eye Landmark Tracking: Kalman, Savitzky-Golay, and Gaussian 4

Comparative Analysis of Filtering Techniques in Eye Landmark...

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4th International Conference on Electrical, Communication and Computer engineering, ICECCE 2023

作者： Nugroho, Muhammad Arief Abdurohman, Maman Erfianto, Bayu Sulistiyo, Mahmud Dwi Kasim, Anita Ahmad School of Computing Telkom University Bandung Indonesia Department of Informatics Faculty of Engineering Tadulako University Palu Indonesia

ISBN: (纸本)9798350369694

This study benchmarks Kalman, Savitzky-Golay, and Gaussian filters to improve eye landmark detection crucial for online proctoring systems. Using eye-tracking video data, we evaluated filters on Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), computation time, and jitter reduction. The Kalman filter emerged superior with an MSE of 0.49, MAE of 0.48, RMSE of 0.70, and MAPE of 15.56%, alongside a 2.39% reduction in standard deviation, 4.73% in variance, and the quickest computation time of 0.02 milliseconds. The Gaussian filter reported an MSE of 0.49, MAE of 0.45, RMSE of 0.70, and MAPE of 14.48%, with modest jitter reductions of 0.96% in standard deviation and 1.90% in variance. In contrast, the Savitzky-Golay filter, with an MSE and MAE of 0.70, increased jitter, shown by a -1.50% change in standard deviation and -3.03% in variance, and took the longest computation time at 1.44 milliseconds. The results solidify the Kalman filter’s suitability for real-time, precision-demanding eye-tracking, while the Gaussian filter serves well for scenarios with relaxed accuracy needs. The Savitzky-Golay filter’s applicability seems limited due to its propensity to amplify noise under the conditions tested. © 2023 IEEE.

关键词： Kalman filters

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Segmentation of Seabed Sediment Images Based on Convolutional Neural Network

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Journal of Marine Environmental engineering 2024年第2期11卷 173-189页

作者： Liu, Yanchang Du, Ke Shan, Liqun Zhu, Lei Jiang, Hanyu Wang, Yan Hei, Xiali School of Physical and Electrical Engineering Northeast Petroleum University Daqing163318 China School of Computing and Informatics University of Louisiana at Lafayette LafayetteLA70503 United States No.5 Production Plant of Daqing Oil Field Company Daqing163513 China

The analysis of particle sizes in seabed sediments plays an important role in various fields. However, acquiring digital sediment images has been challenging due to the characteristics of sediment particles and the complexity of the seabed exploration environment. The goal of this study is to address the issue of particle segmentation in sediment images and propose an innovative network called SAMU-Net. Innovations are as follows. Firstly, SAMU-Net combines spatial attention modules with the traditional U-Net model, which allows for contextual information extraction and adaptive perception of feature variations. Secondly, the model adopts the idea of multi-scale fusion, enabling networks to better understand the structural and semantic information of the images by fusing feature maps at different scales. In addition, using the drop blocks and normalization, we speed up the training convergence of the model and avoid the overfitting phenomenon. The results show that the segmentation results predicted by the SAMU-Net network are highly similar to the ground truth and have a better segmentation performance compared to the existing algorithms. At the same time, it provides a new solution idea to uneven illumination and other noise interference problems in the digital imaging information of sediments. © 2024 Old City Publishing, Inc.

关键词： Particle size

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Cascaded PFLANN Model for Intelligent Health informatics in Detection of Respiratory Diseases from Speech Using Bio-inspired Computation

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Journal of Artificial Intelligence and Technology 2024年第2期4卷 124-131页

作者： Jagannath Dayal Pradhan L.V.Narasimha Prasad Tusar Kanti Dash Manisha Guduri Ganapati Panda Electronics and Communications Engineering C V Raman Global UniversityBhubaneswarIndia Department of Computer Science and Engineering Institute of Aeronautical EngineeringHyderabadIndia School of Computing and Informatics University of LouisianaLafayetteLAUSA

Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-inspired computation,and the Internet of Medical *** has helped in knowledge sharing and scaling ability between patients,doctors,and clinics for effective treatment of ***-based respiratory disease detection and monitoring are crucial in this direction and have shown several promising *** the subject’s speech can be remotely recorded and submitted for further examination,it offers a quick,economical,dependable,and noninvasive prospective alternative detection ***,the two main requirements of this are higher accuracy and lower computational complexity and,in many cases,these two requirements do not correlate with each *** problem has been taken up in this paper to develop a low computational complexity-based neural network with higher accuracy.A cascaded perceptual functional link artificial neural network(PFLANN)is used to capture the nonlinearity in the data for better classification performance with low computational *** proposed model is being tested for multiple respiratory diseases,and the analysis of various performance matrices demonstrates the superior performance of the proposed model both in terms of accuracy and complexity.

关键词： AI-ML ASR FLANN health informatics neural network PFLANN

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A Review of Deep Convolutional Neural Networks in Mobile Face Recognition

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第23期17卷 4-19页

作者： Chi, Jing On, Chin Kim Zhang, Haopeng Chai, Soo See Faculty of Computing and Informatics University Malaysia Sabah Sabah Malaysia School Information and Electrical Engineering Hebei University of Engineering Hebei China Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Sarawak Malaysia

With the emergence of deep learning, Convolutional Neural Network (CNN) models have been proposed to advance the progress of various applications, including face recognition, object detection, pattern recognition, and number plate recognition. The utilization of CNNs in these areas has considerably improved security and surveillance capabilities by providing automated recognition solutions, such as traffic surveillance, access control devices, biometric security systems, and attendance systems. However, there is still room for improvement in this field. This paper discusses several classic CNN models, such as LeNet-5, AlexNet, VGGNet, GoogLeNet, and ResNet, as well as lightweight models for mobile-based applications, such as MobileNet, ShuffleNet, and EfficientNet. Additionally, deep CNN-based face recognition models, such as DeepFace, DeepID, FaceNet, and SphereFace, are explored, along with their architectural characteristics, advantages, disadvantages, and recognition accuracy. The results indicate that many scholars are researching lightweight face recognition, but applying it to mobile devices is impractical due to high computational costs. Furthermore, noise label learning is not robust in actual scenarios, and unlabeled face learning is expensive in manual labeling. Finally, this paper concludes with a discussion of the current problems faced by face recognition technology and its potential future directions for development. © 2023 by the authors of this article. Published under CC-BY. All Rights Reserved.

关键词： Neural network models

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