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26th IEEE Latin American Test Symposium, LATS 2025

作者： Biondani, Francesco Tosoni, Francesco Dall’Ora, Nicola Fraccaroli, Enrico Vinco, Sara Cheng, Dong Seon Fummi, Franco Department of Engineering for Innovation Medicine Section of Engineering and Physics University of Verona Italy Department of Engineering Sciences Guglielmo Marconi University Italy Department of Control and Computer Engineering Politecnico di Torino Italy

ISBN: (纸本)9781665477635

With the growing presence of semiconductor devices in healthcare, automotive, and consumer electronics, Automatic Test Equipment (ATE) systems play an increasingly vital role in ensuring quality and reliability during validation. Despite their importance, ATE systems often operate in isolation from other manufacturing processes, limiting interoperability and integration potential. Consequently, fully incorporating ATE systems within the Industry 4.0 framework remains a largely unaddressed challenge. To bridge this gap, we propose adopting Open Platform Communications Unified Architecture (OPC UA), the industry de-facto standard communication protocol for machines, with an accompanying specification tailored to ATE systems. We developed and validated our information model on an advanced ATE system, demonstrating its practical application. The results showcase the successful integration of the ATE system into a fully-fledged Industrial computer engineering (ICE) laboratory demonstrator. This study validates the effectiveness of our model in a real-world scenario and highlights the significance of our integration approach within the context of Industry 4.0. © 2025 IEEE.

关键词： Automatic testing

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Data Replication Methods in Cloud, Fog, and Edge Computing: A Systematic Literature Review

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Wireless Personal Communications 2024年第1期135卷 531-561页

作者： Karamimirazizi, Fatemeh Jameii, Seyed Mahdi Rahmani, Amir Masoud Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Computer Engineering Shahr-e-Qods Branch Islamic Azad University Tehran Iran Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan

Nowadays, a large amount of data is being generated and these data are usually stored in distributed environments such as cloud, fog, and edge environments. Data replication, which is commonly used to manage large amounts of data, improves overall accessibility and availability. Due to the importance of data replication, a lot of research has been done on replication methods in these environments. In this paper, a systematic review has been conducted to analyze the existing studies on data replication methods in cloud, fog, edge, and edge-cloud environments. The advantages, disadvantages, and some of the main challenges of the existing methods are explained and a taxonomy of data replication methods is provided. The selected papers are analyzed based on various criteria related to data replication, such as recovery, storage cost, load balancing, replica consistency, security, mobility, and data migration. Finally, the open issues and future research directions are discussed. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Fog

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UAV detection technology research based on deep learning 7

UAV detection technology research based on deep learning

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7th International Conference on computer Network, Electronic and Automation, ICCNEA 2024

作者： Wang, Yu Bai, Xiaojun Di, Liuhua Zhao, Shifeng School of Computer Science and Engineering Xi’an Technological University Xi’an China East China Section TechnoPro China Wuxi China

In the process of UAV target recognition, the target is small, the feature is not obvious, and the recognition accuracy is low, a UAV target detection method called YOLOv8-UD is proposed based on YOLOv8. This method replaces downsampling layers with SPD convolutions to mitigate fine-grained feature loss issues. It employs a BiFPN structure to get information which is multi-scale, enhancing representation of global semantic message and Improve awareness of small goals. As a result, to target detection, it significantly enhances the correctness and effectiveness. Additionally, to address difficulty of detecting low-resolution small targets, the network structure was modified by adding a detection head, for small target, thereby enhancing capability to detect it. Combining an improved loss function based on Inner-IoU accelerated model convergence and improved detection accuracy of samples at high IoU thresholds. We can tell by experiments that The algorithm proposed in this paper have 0.805 and 0.334 in mAP(0.5) and mAP(0.5:0.95) metrics, respectively. Compared to YOLOv8, improvements of 4.6% and 7% are achieved in mAP(0.5) and mAP (0.5:0.95) metrics. The experiments validate that the proposed way significantly enhances accuracy to UAV small target detection. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Automated Attendance Management System: Leveraging computer Vision for Efficient Tracking and Monitoring 9

Automated Attendance Management System: Leveraging Computer ...

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9th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2023

作者： Nizam, Nabeel Wahid, Abdul Khan, Akbar Elahi, Faizan Kadir, Kushsairy Nadeem, Zain Saad, Muhammad Nasir, Haidawati Buitems Dept. of Electronic Engineering Quetta Pakistan Buitems Deptt. of Computer Engineering Quetta Pakistan British Malaysian Institute Electrical Section UniKL Kuala Lumpur Malaysia Malaysian Institute of Technology Computer Engineering Section UniKL Kuala Lumpur Malaysia

ISBN: (纸本)9798350343380

Face recognition is a bio-metric technology that has been widely adopted for security, authentication, and identification. In recent years, face recognition systems have also been used for attendance management in educational institutions and offices. This paper presents a face recognition-based attendance management system that is designed to replace the time-consuming and error-prone manual attendance process. The system comprises four key phases: database creation, face detection, face recognition, and attendance updating. The initial phase involves the creation of a comprehensive database of images of the students in the class. Subsequently, the system employs the HAAR-Cascade classifier for face detection and the Local Binary Pattern Histogram algorithm for face recognition. The system accurately detects and recognizes faces in real time by analyzing the live video stream from the classroom. Finally, at the conclusion of each session, the attendance records are compiled and stored in a CSV file. The presented system has been validated on a dataset of 100 students. The results show that the system can achieve an accuracy of over 90%. The system is also able to handle variations in lighting and facial expressions. The implementation of this face recognition-based attendance management system can enhance operational efficiency, reduce administrative burdens, and ensure more accurate attendance tracking. © 2023 IEEE.

关键词： Local binary pattern

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Distributed Big Data Clustering using MapReduce-based Fuzzy C-Medoids

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Journal of The Institution of Engineers (India): Series B 2022年第1期103卷 73-82页

作者： Sardar, Tanvir H. Ansari, Zahid School of Computer Science & Engineering Jain University Bangalore India Electrical Engineering Section University Polytechnic Aligarh Muslim University Aligarh India

Efficient big data clustering is a requirement for massive data generating in this digitalized connected world. The traditional clustering algorithms do not scale over massively sized and highly unstructured big data. Thus, to obtain efficiency in clustering big data new architecture and programming paradigm is required. In this work, a novel MapReduce-based Fuzzy C-Medoids clustering algorithm is designed and experimented with to cluster big data repository of documents datasets. The performance of the proposed algorithm is experimentally evaluated for different-sized Hadoop cluster sizes and different-sized document datasets. The algorithm is found to be scalable and efficient in performing clustering jobs. © 2021, The Institution of Engineers (India).

关键词： MapReduce

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MapReduce-based Fuzzy C-means Algorithm for Distributed Document Clustering

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Journal of The Institution of Engineers (India): Series B 2022年第1期103卷 131-142页

The clustering of big data is a challenging task. The traditional clustering algorithms are inefficient for clustering big data. The recent researches in this field suggest that the traditional clustering algorithms needed to be redesigned for the modern architecture of computing. This wok has proposed a novel MapReduce-based fuzzy C-means algorithm for big document data clustering. The algorithm is extensively experimented with using different sizes of document datasets and executed over the Hadoop cluster of different sizes. The proposed algorithm’s efficiency is compared against serial traditional fuzzy C-means and MapReduce-based K-means algorithms. The proposed design of the fuzzy C-means algorithm is scaled well with the Hadoop platform and documents big datasets and resulted in a performance gain. © 2021, The Institution of Engineers (India).

关键词： MapReduce

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Optimizing Cloud Data Centers for Environment Sustainability through Performance-Aware Virtual Machine Allocation 7

Optimizing Cloud Data Centers for Environment Sustainability...

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7th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2023

作者： Kumar, Vaneet Jindal, Balkrishan Chandigarh University Department of Computer Science and Engineering Gharuan140413 India Punjabi University Guru Kashi Campus Computer Engineering Section YCoE Talwandi Sabo151302 India

ISBN: (纸本)9798350305517

Cloud computing faces challenging issues concerning high-energy consumption and service-level agreement (SLA) violations, particularly as the demand for computational power continues to grow, necessitating large-scale cloud data centers. Existing energy-aware approaches tend to focus on performance optimization during VM migration phases but it can be effectively maintained at VM allocation level as preprocessing. Thereby, this paper proposed Energy Efficient SLA-aware virtual machine Allocation approach using a metaheuristic Firefly algorithm (FFO-EESA). The experimental findings showcase promising outcomes in the context of dynamic workloads and varying numbers of VMs (ranging from 1 to 290) allocated on individual hosts. The proposed method's experimental results were obtained through computer-based simulations conducted in MATLAB version 2017(a). The outcomes showed that, there was a reduction of 12.34% in migrations and a saving of 4.36% in idle hosts with the FFO-EESA approach. proposed algorithm resulted in an average energy savings of 4.39% compared to the FF and MBFD techniques. © 2023 IEEE.

关键词： Optimization

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Lane and Platoon Assignment in Intelligent Transportation System: A Novel Heuristic Approach

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International Journal of Intelligent Transportation Systems Research 2024年第2期22卷 298-315页

作者： Mahini, Hamidreza Asadi, Mehrdad Mahini, Alireza Rahmani, Amir Masoud Fathy, Mahmood Department of Computer Engineering Gorgan Branch Islamic Azad University Gorgan Iran Vrije Universiteit Brussel Brussels Belgium Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Department of Computer Engineering Iran University of Science and Technology Tehran Iran

The right lane and platoon assignment to a vehicle significantly impacts achieving the desired driving goals to improve occupants’ safety or reduce pollution. Preparing an intelligent assistant to address this issue has exposed researchers’ attention, especially in intelligent transportation systems. Implementing such a system is complex and challenging to design, mainly because of conflicting driving goals possibility and the mixed traffic of autonomous and human-driven vehicles. This paper presents a multi-tier computational architecture to utilize the cloud, fog, and edge computational resources and formulate the lane/platoon assignment as an optimization problem subject to safety combined with any other secondary goal. The problem is then solved by the meta-heuristic Genetic Algorithm. By evaluating the proposed method by real data gathering, machine learning, and numerical experiments, the results show that the proposed method satisfies the minimization of overlapping collision areas during vehicles’ lane/platoon changes and harmonizes the traffic in all lanes and each platoon. © The Author(s), under exclusive licence to Intelligent Transportation Systems Japan 2024.

关键词： Genetic algorithms

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The Critical Role of Industrial Eco-Parks in Preserving the Environment of the Western Balkans

The Critical Role of Industrial Eco-Parks in Preserving the ...

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International Conference of Experimental and Numerical Investigations and New Technologies, CNNTech 2024

作者： Mitrovic, Aleksandra Vuruna, Mladen Mutavči, Vjačeslav Faculty of Information Technology and Engineering University "Union – Nikola Tesla" Belgrade Serbia Computer-Mechanical Engineering Section The Academy of Applied Technical Studies Belgrade Belgrade Serbia

ISBN: (纸本)9783031786341

The Western Balkans, a region characterized by rich biodiversity and natural resources, face substantial environmental challenges due to industrial activities. Industrial eco-parks offer a sustainable solution to these issues, playing a crucial role in preserving the environment while fostering economic development. These eco-parks employ advanced technologies and sustainable practices to significantly reduce air, water and soil pollution. By optimizing resource use through recycling, reuse, and waste reduction, they conserve natural resources and lower operational costs for businesses. Moreover, the integration of green spaces and sustainable landscaping within eco-parks supports local biodiversity and maintains ecological balance. Beyond environmental benefits, industrial eco-parks contribute to economic and social development. They create job opportunities, attract investments, and drive regional economic growth. Additionally, eco-parks enhance the quality of life for surrounding communities by reducing pollution-related health risks and providing green recreational areas. They also serve as hubs for innovation and education, promoting collaboration between businesses, academic institutions, and governments. Strategically, industrial eco-parks support the Western Balkans’ sustainable development goals and align with regional strategies to achieve environmental and economic objectives. For countries aspiring to join the European Union, adopting eco-parks demonstrates compliance with EU environmental standards, facilitating the integration process. Furthermore, the development of eco-parks promotes cross-border cooperation, strengthening regional stability and shared environmental responsibility. It is particularly important to emphasize that industrial eco-parks are essential for the environmental and economic future of the Western Balkans. Their adoption can lead to significant pollution reduction, resource conservation, and biodiversity protection while offering

关键词： Sustainable development goals

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Classification of Stakeholders of an Information System using Fuzzy based Adjusted Cosine Similarity Measure during Requirements Elicitation Process 3

Classification of Stakeholders of an Information System usin...

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3rd International Conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

作者： Akram, Faiz Ahmad, Tanvir Sadiq, Mohd Department of Computer Engineering Faculty of Engineering and Technology Jamia Millia Islamia New Delhi25 India Software Engineering Laboratory Computer Engineering Section UPFET Jamia Millia Islamia New Delhi25 India

Requirements elicitation process is employed for the identification of stakeholders of an information system. A large number of stakeholders from different domains across the globe participate during the requirements elicitation process. Based on our review, we found that existing methods for the analysis of stakeholders do not support how to classify the stakeholders based on the similarity measures. These measures play an important role for the recommendation of an item/user in a recommendation system. Thus, the objective of this paper is to classify the stakeholders of an information system using fuzzy-based adjusted cosine similarity measure. We have identified the stakeholders of library information system and their opinions for different requirements are recorded. The identified stakeholders have been classified and analysed based on the following similarity measures under fuzzy environment, i.e., Cosine similarity measure, Euclidean distance, Pearson coefficient correlation etc., so that stakeholders having similar requirements can be recommended to strengthen the requirements elicitation process. © 2023 Elsevier B.V.. All rights reserved.

关键词： Recommender systems

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