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Random hyperbolic graphs in d+1 dimensions

Physical Review E 2024年第5期109卷 054131-054131页

作者： Gabriel Budel Maksim Kitsak Rodrigo Aldecoa Konstantin Zuev Dmitri Krioukov Faculty of Electrical Engineering Mathematics and Computer Science Department of Physics Network Science Institute Department of Computing and Mathematical Sciences Department of Physics Department of Mathematics Department of Electrical & Computer Engineering

We consider random hyperbolic graphs in hyperbolic spaces of any dimension d+1≥2. We present a rescaling of model parameters that casts the random hyperbolic graph model of any dimension to a unified mathematical framework, leaving the degree distribution invariant with respect to the dimension. Unlike the degree distribution, clustering does depend on the dimension, decreasing to 0 at d→∞. We analyze all of the other limiting regimes of the model, and we release a software package that generates random hyperbolic graphs and their limits in hyperbolic spaces of any dimension.

关键词： Network formation & growth Network structure

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Pix2Pix++: An Enhanced GANs Based Model for Portrait to Pencil Sketch Translation 18

Pix2Pix++: An Enhanced GANs Based Model for Portrait to Penc...

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18th International Conference on Open Source Systems and Technologies, ICOSST 2024

作者： Abbasi, Humza Fazal Abbasi, Merium Fazal Hamayat, Faizan Bahria University Department of Computer Science Islamabad Pakistan CESAT Department of Electronics Engineering Islamabad Pakistan University of Engineering and Technology Taxila Taxila Electrical Engineering Department Pakistan

ISBN: (纸本)9798331508692

The generation of sketches from portraits has been an active area of research for decades due to its applications in various sectors such as entertainment and education. However, due to numerous qualitative factors involved in sketching, programmatically generating sketches from images has been a challenging task. Recent advances in generative artificial intelligence (GAI) seem very promising in solving these challenges. In specific, generative adversarial networks (GANs) like conventional Pix2Pix, were specifically designed for accurate and efficient image-to-image translation tasks. In this research, inspired by GAI and original Pix2Pix, we proposed a GANs-based Pix2Pix++ technique for translating portrait images into sketches. We replaced U-Net with the UNet++ for generator in Pix2Pix++ GAN and trained the proposed model on a self-collected dataset for sketch generation. Furthermore, we evaluated the proposed model's performance both qualitatively and quantitively and performed a comparative analysis with existing techniques. Proposed Pix2Pix++ GAN got MS-SSIM median scores of 84%, PSNR of 21.17, and MSE median score of 495.55. Experimental results showed our proposed technique outperforms the existing techniques in terms of capturing minute details, tonal variations, realistic appearance, and generalization. © 2024 IEEE.

关键词： Generative adversarial networks

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Performance Evaluation of Coffee Bean Binary Classification Through Deep Learning Techniques 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Islamy, Fajrul Muchtar, Kahlil Arnia, Fitri Dawood, Rahmad Febriana, Alifya Elwirehardja, Gregorius Natanael Pardamean, Bens Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Master of Computer Science Program BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Coffee beans are one of the high-value commodities in Indonesia, but the sorting method for the quality of coffee beans still uses visual methods and sieves with mechanical machines. This study aims to provide an alternative to classifying coffee beans using Deep Learning algorithms, such as the ResNet-18 and MobileNetV2. The dataset used is USK-COFFEE which consists of two classes, the normal coffee bean class, and the defect coffee bean class. The models were trained using the balanced and imbalanced datasets, meaning that two scenarios were performed. From the results of this study, the accuracy value for the ResNet-18 model was 91.50% when trained on the balanced dataset and 90.87% on the imbalanced dataset. It outperformed the MobileNetV2 architecture, which only achieved 0.8125 and 0.8112 accuracy scores when trained on the balanced and imbalanced datasets, respectively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： computer vision

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Design and Development of an Intelligent Energy Management System for a Smart Grid to Enhance the Power Quality

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Energy engineering 2023年第8期120卷 1747-1761页

作者： Nisha Vasudevan Vasudevan Venkatraman A.Ramkumar T.Muthukumar A.Sheela M.Vetrivel R.J.Vijaya Saraswathi F.T.Josh Department of Electrical and Electronics Engineering Kalasalingam Academy of Research and EducationTamil NaduIndia Department of Computer Science Engineering Kalasalingam Academy of Research and EducationTamil NaduIndia Department of Electrical and Electronics Engineering Kongunadu College of Engineering and TechnologyTamil NaduIndia Department of Electrical and Electronics Engineering Kongu Engineering CollegeTamil NaduIndia Department of Electrical and Electronics Engineering Narasu’s Sarathy Institute of TechnologyTamil NaduIndia Department of Electrical and Electronics Engineering Panimalar Engineering CollegeTamil NaduIndia Department of Electrical and Electronics Engineering Karunya Institute of Technology&SciencesTamil NaduIndia

MigroGrid(MG)has emerged to resolve the growing demand for *** because of its inconsistent output,it can result in various power quality(PQ)*** is a problem that is becoming more and more important for the reliability of power systems that use renewable energy ***,the employment of nonlinear loads will introduce harmonics into the system and,as a result,cause distortions in the current and voltage waveforms as well as low power quality issues in the supply ***,this research focuses on power quality enhancement in the MG using hybrid shunt ***,the performance of the filter mainly depends upon the design,and stability of the *** efficiency of the proposed filter is enhanced by incorporating an enhanced adaptive fuzzy neural network(AFNN)*** performance of the proposed topology is examined in a MATLAB/Simulink environment,and experimental findings are provided to validate the effectiveness of this ***,the results of the proposed controller are compared with Adaptive Fuzzy Back-Stepping(AFBS)and Adaptive Fuzzy Sliding(AFS)to prove its superiority over power quality improvement in *** the analysis,it can be observed that the proposed system reduces the total harmonic distortion by about 1.8%,which is less than the acceptable limit standard.

关键词： Artificial intelligence resistive inductive load shunt hybrid filter smart grid adaptive fuzzy back-stepping power factor

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Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

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computer Systems science & engineering 2022年第9期42卷 935-948页

作者： M.Manikandan R.Subramanian M.S.Kavitha S.Karthik Department of Computer Science&Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatore641035India Department of Computer Science&Engineering SNS College of TechnologyCoimbatore641035India

In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located inremote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and taskscheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud isemployed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the currentresearch work develops a Cost-Effective Optimal Task Scheduling Model(CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) modelis used in the proposed work for hybrid clouds. Moreover, the algorithm workson the basis of multi-intentional task completion process with optimal resourceallocation. The model was successfully simulated to validate its effectivenessbased on factors such as processing time, make span and efficient utilization ofvirtual machines. The results infer that the proposed model outperformed theexisting works and can be relied in future for real-time applications.

关键词： Cost effectiveness hybrid cloud optimal task scheduling virtual machine resource allocation make span

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Developing a Test Suite for Evaluating IEC 61499 Application Portability 32

Developing a Test Suite for Evaluating IEC 61499 Application...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Xavier, Midhun Laikh, Tatiana Patil, Sandeep Vyatkin, Valeriy Lulea Tekniska Universitet Computer and Space Engineering Department of Computer Science Sweden Aalto University Department of Electrical Engineering and Automation Espoo Finland

ISBN: (纸本)9798350399714

This paper presents the creation of a series of function blocks with the specific aim of testing the portability of IEC 61499 applications across diverse development and runtime environments. These function blocks have been developed to cover a wide range of test scenarios, including basic data types, functions, boundary conditions, and adapter features. The function blocks can be conveniently exported or imported through the use of XML files, thus facilitating seamless testing. By testing the runtime environment of different IEC 61499 systems, these function blocks help to identify and highlight any possible issues that may arise related to portability. © 2023 IEEE.

关键词： IEC 61499 Industrial Control System Portability Testing

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A Yet Powerful Routing Protocol for Vehicular Ad-hoc Networks (VANETs) Utilizing Software Defined Network (SDN) and Fog Computing 8

A Yet Powerful Routing Protocol for Vehicular Ad-hoc Network...

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8th International Conference on Information Technology, Information Systems and electrical engineering, ICITISEE 2024

作者： Darabkh, Khalid A. Al-Mistarihi, Mamoun F. Al-Maaitah, Mera Ismail School of Engineering The University of Jordan Computer Engineering Department Amman11942 Jordan Jordan University of Science and Technology Faculty of Engineering Electrical Engineering Department Irbid22110 Jordan

ISBN: (纸本)9798350368970

In this article, we propose a novel protocol that employs different technologies together, such as Software Defined Network (SDN) for the purpose of offering scalability, programmability, and global network information, and Fog computing for the reason of providing location services that meet V ANET standards. Additionally, we propose a novel cluster head selection algorithm for the purpose of enhancing the efficiency of the protocol by considering three different dimensions, namely, lifetime, average distance, and signal-to-interference noise ratio. The novelty of this proposed algorithm comes from reducing the number of control overheads, reducing long-distance communications, and reducing packet loss due to collisions and contentions inside each cluster, respectively. The proposed protocol has been assessed using N s3 simulator whereas its results are so promising and worth publishing. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Designing Optimal Parameters for Single-Axis Solar-Tracker through Analysis of Sun-Path and Tracking Vector Dynamics 6

Designing Optimal Parameters for Single-Axis Solar-Tracker t...

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6th International Conference on electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Akhtaruzzaman, M. Islam, Md Shofiqul Shahryer, Fahim Arif, Muammer Din Mollik, Md. Sazib Rahman, Muhammad Towfiqur Rahman, Md. Mahbubur Hasan, Mohammad Kamrul Ahmed, Shugata Ashrafuzzaman, Md. Department of Computer Science and Engineering Dhaka1216 Bangladesh Department of Mechanical Engineering Dhaka1216 Bangladesh Department of Electrical and Electronic Engineering Dhaka Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh Faculty of Information Science and Technology Bangi Malaysia Department of Robotics and Mechatronics Engineering Bangladesh Sdn. Bhd. Cyberjaya Malaysia

ISBN: (纸本)9798350385779

The persistent challenges faced by sun-tracking systems include inefficient power production, wastage of energy, ineffective control, and high costs. Most of the existing systems are either static or dual-axis tracking which lead to inefficient output or increasing energy wastage and cost overheads. Though, single-axis tracking system has some benefits over the static or dual-axis tracking, most of the systems do not analyze the selection of optimal sun-path which again leads to inefficient and inadequate absorption of sunlight. Addressing the issues, this article presents a design of optimal parameters for single-axis solar-tracking by analyzing the sun-path and tracking vector dynamics. The study mainly focuses on analyzing solar-tracking dynamics, variations in sunray angles, Azimuth and Elevation dynamics throughout the day for the twelve months, Sun-vector calculation for local coordinates, joint rotational-axis, and joint motion control using a Proportional-Derivative controller. Additionally, the article outlines a conceptual architecture for automated control, monitoring, and power distribution for the potential development of a sustainable smart city. The proposed strategy addresses the issues of the optimal design of a single-axis solar-tracker, thus ensuring the reduction of cost overhead and energy wastage. © 2024 IEEE.

关键词： Dynamics

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Development of Automotive-mobility Training in the TRIREME project 30

Development of Automotive-mobility Training in the TRIREME p...

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30th IEEE International Symposium for Design and Technology in Electronic Packaging, SIITME 2024

作者： Medgyes, Balint Farkas, Csaba Spanyik, Marek Danieli, Stefano Cantiani, Elena Stolfa, Jakub Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Electronics Technology Budapest Hungary VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Department of Computer Science Ostrava Czech Republic Mylia-Adecco Formazione Milan Italy

ISBN: (纸本)9798331539511

To achieve climate neutrality by 2050, the consistent transformation of the mobility sector is one of the most important pillars of the European Green deal. As a result of green and sustainable approaches, novel automotive concepts and massive digitalisation in the mobility ecosystem is undergoing a continuous development towards eco-friendly solutions and novel business models, and the changing landscape of automotive industry comes with a significant social impact as well. The overall horizontal collaboration on skills agenda in the Automotive-Mobility Ecosystem is assured throughout the Automotive Skills Alliance (ASA) [1], which is the Large-scale Pact for Skills Partnership. The latest strategic project of the partnership to support its activities is the Digital & Green Skills Towards Future of the Mobility Ecosystem (TRIREME) which promotes a collaboration between industry stakeholders and training providers including Vocational education Trainings (VETs), Higher Educations (HEs) and universities), moreover, also emphasizing the widespread public representation of different project segments and evaluating the social impacts and regional impact of the changes in the Automotive-Mobility Ecosystem. In parallel to the development of sectoral skills strategy, our department (department of Electronics Technology-ETT) is contributing to deliver specific training materials and courses within Work Package 4 (WP4), which is based on the gathered and processed intelligence from previous desk research, survey activity and participation in professional events. The methodology of course development relies on the concept of modularity, our professional competences in the field of Automotive-mobility, and the fulfillment of requirements to cover the needed skills, the competence and the occupational profile subsets. © 2024 IEEE.

关键词： Automotive Mobility Modular Courses Skills Training Development

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Energy-Efficient and Latency-Aware Task Offloading for Industrial Cloud-Edge Systems with Heterogeneous CPUs and GPUs

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IEEE Internet of Things Journal 2025年第13期12卷 25757-25772页

作者： Zhai, Jiahui Bi, Jing Yuan, Haitao Zhang, Jia Buyya, Rajkumar Beijing University of Technology College of Computer Science Beijing100124 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Southern Methodist University Department of Computer Science DallasTX75206 United States Lab School of Computing and Information Systems MelbourneVIC3010 Australia

The unprecedented prosperity of the Industrial Internet of Things has significantly driven the transition from traditional manufacturing to intelligent one. In industrial environments, resource-constrained industrial equipments (IEs) often fail to meet the diverse demands of numerous compute-intensive and latency-sensitive tasks. Mobile edge computing has emerged as an innovative paradigm to reduce latency and energy consumption for IEs. However, the increasing number of IEs in industrial settings relies on heterogeneous platforms integrated with different processing units, i.e., CPUs and GPUs. To address this challenge, we propose a software-defined networking-based equipment-edge-cloud architecture with three-stage heterogeneous computing. This architecture accurately models the multi-task processing of both scientific and concurrent workflows in real industrial environments. We formulate a joint optimization problem to simultaneously minimize task completion time and energy consumption for IEs. To solve this problem, we design an Improved Two-stage Multi-Objective Evolutionary Algorithm (IT-MOEA). IT-MOEA employs a novel multi-objective grey wolf optimizer based on manta ray foraging and associative learning to accelerate convergence in the early evolution stages and adopts a diversity-enhancing immune algorithm to enhance diversity in the later stages. Simulation results with various benchmarks demonstrate that IT-MOEA outperforms several state-of-the-art single-objective optimization algorithms by an average of 24.7% and multi-objective algorithms by 41.0% in terms of delay and energy consumption. © 2025 IEEE.

关键词： Mobile edge computing

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