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2023 International Conference on Cyber Management and Engineering, CyMaEn 2023

作者： Salau, Ayodeji Olalekan Abeje, Bekalu Tadele Faisal, Abeer Naser Asfaw, Tesfa Tegegne Afe Babalola University Department of Electrical/Electronics and Computer Engineering Ado-Ekiti Nigeria Haramaya University College of Computing and Informatics Department of Information Technology Ethiopia Institute of Technology Faculty of Computing Bahir Dar University Department of Computer Science Ethiopia University of Sumer College of Computer Science and Information Technology Al-Rifai Iraq

ISBN: (纸本)9781665493291

Faba bean (Vicia faba L.) is an important cash crop for animal and human consumption in many countries, especially Ethiopia due to its high protein content and high rate of production. It also improves soil fertility with the help of bacteria, which forms nodules on its roots. Ethiopia is the second largest faba bean producer;however, according to research, the yield is generally low. Among the constraints contributing to low productivity of the crop, disease is the most important. Even though there are countermeasures such as the use of chemical sprays, which is used to reduce the damage or eliminate the disease, an effective disease identification technique is still required. Chocolate spot, faba bean gal, and rust are the most common diseases of faba beans. To effectively detect the disease, in this paper, we propose an end-to-end CNN model for training before and after the dataset is preprocessed. The CNN end-to-end model is trained with raw images and achieves 92.1% training accuracy. Also, the model is trained with preprocessed data and it achieves a training accuracy of 98.14% for the end-to-end CNN classifier. The results show that the proposed approach is suitable for faba bean disease detection and can be employed to detect diseases of other crops. © 2023 IEEE.

关键词： Convolutional neural networks

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Integrated Sensing and Communications With Reconfigurable Intelligent Surfaces: From signal modeling to processing

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IEEE Signal Processing Magazine 2023年第6期40卷 41-62页

作者： Chepuri, Sundeep Prabhakar Shlezinger, Nir Liu, Fan Alexandropoulos, George C. Buzzi, Stefano Eldar, Yonina C. Indian Institute of Science Department of Electrical and Computer Engineering Bengaluru560012 India Ben-Gurion University of the Negev School of Electrical and Computer Engineering Be'er Sheva84105 Israel Southern University of Science and Technology Shenzhen518055 China School of Sciences National and Kapodistrian University of Athens Department of Informatics and Telecommunications Athens15784 Greece University of Cassino and Lazio Meridionale Cassino03043 Italy Weizmann Institute of Science Department of Mathematics and Computer Science Rehovot7610001 Israel

Integrated sensing and communications (ISAC) are envisioned to be an integral part of future wireless networks, especially when operating at the millimeter-wave (mm-wave) and terahertz (THz) frequency bands. However, establishing wireless connections at these high frequencies is quite challenging, mainly due to the penetrating path loss that prevents reliable communication and sensing. Another emerging technology for next-generation wireless systems is reconfigurable intelligent surface (RIS), which refers to hardware-efficient planar structures capable of modifying harsh propagation environments. In this article, we provide a tutorial-style overview of the applications and benefits of RISs for sensing functionalities in general, and for ISAC systems in particular. We highlight the potential advantages when fusing these two emerging technologies, and identify for the first time that 1) joint sensing and communications (S&C) designs are most beneficial when the channels referring to these operations are coupled, and that 2) RISs offer the means for controlling this beneficial coupling. The usefulness of RIS-aided ISAC goes beyond the obvious individual gains of each of these technologies in both performance and power efficiency. We also discuss the main signal processing challenges and future research directions that arise from the fusion of these two emerging technologies. © 1991-2012 IEEE.

关键词： Signal processing

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A secured GA-WPC framework for scheduling the independent tasks in cloud environment

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 13003-13015页

作者： Dubey, Kalka Sharma, S.C. Kumar, Mohit Kumar, Prashant Nasr, Aida A. Cloud Computing and Wireless Sensor Lab Indian Institute of Technology Roorkee Uttarakhand Roorkee247667 India Department of Computer Science and Engineering Rajiv Gandhi Institute of Petroleum Technology Jais Uttar Pradesh Amethi229304 India Department of Information Technology Dr BR Ambedkar National Institute of Technology Punjab Jalandhar144011 India Information Technology Department Faculty of Computers and Informatics Tanta University Tanta Egypt

Cloud computing proved itself a powerful and popular platform for providing computing services. It offers on-demand services to users with highly efficient resources over the internet. With the exponential increase in the number of internet users and due to the high acceptance rate to use the cloud services in everything, the demand for cloud platforms has also increased significantly. This leads to heavy workloads on the servers, which is a difficult task to manage due to the heterogeneity and uncertainty of the resources. However, several traditional, heuristic, and evolutionary-based approaches have been proposed to solve the problem of scheduling. Existing state-of-art techniques and frameworks have solved the problem up to a limited level. Still, these solutions have not given any effective and concrete solution for the overall resource scheduling problem. Therefore, this paper tries to overcome the bottleneck of existing solutions by presenting a new framework named Genetic Algorithm Water Pressure Change (GAWPC) to solve task scheduling problems efficiently. The GAWPC framework exploited the feature of the Genetic Algorithm (GA) and Water Pressure Change optimization (WPCO) techniques to form a new hybrid mechanism. In the proposed framework, GA has been deployed to find the optimal solution for a particular population. WPCO has been used to optimize fitness function for a fast convergence rate. The computer-based simulation has demonstrated promising benefits like improved computation cost, make-span time, and load balancing when compared with the most recent existing baseline techniques using CloudSim. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Genetic algorithms

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REX: A Realistic Time-Dependent Model for Multimodal Public Transport 22

REX: A Realistic Time-Dependent Model for Multimodal Public ...

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22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems, ATMOS 2022

作者： Kontogiannis, Spyros Machaira, Paraskevi-Maria-Malevi Paraskevopoulos, Andreas Zaroliagis, Christos Computer Science & Engineering Department University of Ioannina Greece Computer Technology Institute & Press "Diophantus" Rion Greece Department of Computer Engineering & Informatics University of Patras Greece

ISBN: (纸本)9783959772594

We present the non-FIFO time-dependent graph model with REalistic vehicle eXchange times (REX) for schedule-based multimodal public transport, along with a novel query algorithm called TRIP-based LAbel-correction propagation (TRIPLA) algorithm that efficiently solves the realistic earliest-arrival routing problem. The REX model possesses all strong features of previous time-dependent graph models without suffering from their deficiencies. It handles non-negligible exchanges from one vehicle to another, as well as supports non-FIFO instances which are typical in public transport, without compromising space efficiency. We conduct a thorough experimental evaluation with real-world data which demonstrates that TRIPLA significantly outperforms all state-of-the-art query algorithms for multimodal earliest-arrival routing in schedule-based public transport. © Spyros Kontogiannis, Paraskevi-Maria-Malevi Machaira, Andreas Paraskevopoulos, and Christos Zaroliagis.

关键词： Graph theory

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XMeta-OS: A Conceptual Framework for Unified Resource Management in Distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

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3rd International Conference on Advances in Computing Research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

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Automated Indonesian Essay Scoring and Holistic Feedback Using Bidirectional Encoder Representations for Transformers 8

Automated Indonesian Essay Scoring and Holistic Feedback Usi...

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8th International Conference on Electrical, Telecommunication and computer Engineering, ELTICOM 2024

作者： Amalia, Amalia Lydia, Maya Silvi Kadir, Rabiah Abdul Utami Tanjung, Faradhila Aulia Br Ginting, Dewi Sartika Gunawan, Dani Universitas Sumatera Utara Department of Computer Science Medan Indonesia Institute of Visual Informatics Universiti Kebangsaan Malaysia Selangor Malaysia Universitas Sumatera Utara Department of Information Technology Medan Indonesia

ISBN: (纸本)9798331531249

Developing an effective and accurate Automated Essay Scoring (AES) system for Indonesian essays involves overcoming several challenges, including limited datasets and issues related to grading efficiency and feedback generation. This study addresses these challenges by proposing an automated Indonesian essay grading and feedback system utilizing Bidirectional Encoder Representations from Transformers (BERT). The research employed a thorough process, including the translation of the ASAP dataset from the Kaggle competition titled 'The Hewlett Foundation' into Indonesian, analysis and refinement of the dataset to include only relevant features, and fine-tuning using the pre-trained IndoBERT embeddings. To assess the relevance between the essay prompts and student responses, text similarity methods were applied outside the fine-tuning process. The final score is derived from the combination of the fine-tuned score and the relevance score. The model achieved a perfect accuracy of 1 and a strong kappa score of 0.82 during training. The alignment of the final score predictions with human feedback is validated by a Quadratic Weighted Kappa (QWK) score of 0.9, indicating a high level of agreement. This demonstrates that the automated scoring system effectively matches human judgment, highlighting its efficacy in evaluating essay quality. © 2024 IEEE.

关键词： Feedback

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An Attention-Based Deep Network for Plant Disease Classification

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Machine Graphics and Vision 2024年第1期33卷 47-67页

作者： Bera, Asish Bhattacharjee, Debotosh Krejcar, Ondrej Department of Computer Science and Information Systems Birla Institute of Technology and Science Rajasthan Pilani India Department of Computer Science and Engineering Jadavpur University West Bengal Kolkata India Center for Basic and Applied Science Faculty of Informatics and Management University of Hradec Králové Czech Republic Škoda Auto University Mladá Boleslav Czech Republic Universiti Teknologi Malaysia Kuala Lumpur Malaysia

Plant disease classification using machine learning in a real agricultural field environment is a difficult task. Often, an automated plant disease diagnosis method might fail to capture and interpret discriminatory information due to small variations among leaf sub-categories. Yet, modern Convolutional Neural Networks (CNNs) have achieved decent success in discriminating various plant diseases using leave images. A few existing methods have applied additional pre-processing modules or sub-networks to tackle this challenge. Sometimes, the feature maps ignore partial information for holistic description by part-mining. A deep CNN that emphasizes integration of partial descriptiveness of leaf regions is proposed in this work. The efficacious attention mechanism is integrated with high-level feature map of a base CNN for enhancing feature representation. The proposed method focuses on important diseased areas in leaves, and employs an attention weighting scheme for utilizing useful neighborhood information. The proposed Attention-based network for Plant Disease Classification (APDC) method has achieved state-of-the-art performances on four public plant datasets containing visual/thermal images. The best top-1 accuracies attained by the proposed APDC are: PlantPathology 97.74%, PaddyCrop 99.62%, PaddyDoctor 99.65%, and PlantVillage 99.97%. These results justify the suitability of proposed method. © 2024 institute of Information technology, Warsaw University of Life Sciences - SGGW. All rights reserved.

关键词： Convolutional neural networks

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Private Computation of Boolean Functions Using Single Qubits 15th

Private Computation of Boolean Functions Using Single Qubit...

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15th International Conference on Parallel Processing and Applied Mathematics, PPAM 2024

作者： Rahmani, Zeinab Pinto, Armando N. Barbosa, Luis S. Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal Instituto de Telecomunicações Aveiro Portugal International Iberian Nanotechnology Laboratory Braga Portugal Department of Computer Science University of Minho Braga Portugal Institute of Systems and Computer Engineering Technology and Science Braga Portugal

ISBN: (纸本)9783031856990

Secure Multiparty Computation (SMC) facilitates secure collaboration among multiple parties while safeguarding the privacy of their confidential data. This paper introduces a two-party quantum SMC protocol designed for evaluating binary Boolean functions using single qubits. Complexity analyses demonstrate a reduction of 66.7% in required quantum resources, achieved by utilizing single qubits instead of multi-particle entangled states. However, the quantum communication cost has increased by 40% due to the amplified exchange of qubits among participants. Furthermore, we bolster security by performing additional quantum operations along the y-axis of the Bloch sphere, effectively hiding the output from potential adversaries. We design the corresponding quantum circuit and implement the proposed protocol on the IBM Qiskit platform, yielding reliable outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Qubits

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Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak 14

Electricity Power Consumption Prediction With The Monte Carl...

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14th International Conference on Information and Communication technology and System, ICTS 2023

作者： Hoendarto, Genrawan Saikhu, Ahmad Ginardi, Raden Venantius Hari Institute Technology of Sepuluh Nopember Department of Information Technology Surabaya Indonesia Universitas Widya Dharma Pontianak Indonesia Institute Technology of Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Department of Information Technology Surabaya Indonesia Institute Technology of Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Department of Computer Science Surabaya Indonesia

ISBN: (纸本)9798350312164

Predicting electricity consumption for buildings has been a concern lately, as it accounts for 39% of total electricity consumption. One of the buildings that uses a lot of electricity is the campus building. Various methods are being developed and carried out in response to the fossil energy crisis to save electricity consumption. Before taking steps to reduce the use of electricity, it is necessary to predict its use. Monte Carlo simulation is a good option for predicting electricity consumption. The dataset used in this study was collected over the past year and recorded several times a day. According to the lecture days, the data used is only from Monday to Friday. Since the recording is done randomly over a day, we preprocess the data using tree regression. After the data pre-processing stage produces data in minutes, the last stage is the quartile search process to find the hourly average. © 2023 IEEE.

关键词： Forecasting

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Two Layer Symmetric Cryptography Algorithm for Protecting Data from Attacks

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computers, Materials & Continua 2023年第2期74卷 2625-2640页

作者： Muhammad Nadeem Ali Arshad Saman Riaz Syeda Wajiha Zahra Shahab SBand Amir Mosavi Department of Computer Science Abasyn UniversityIslamabad44000Pakistan Department of Computer Science National University of TechnologyIslamabad44000Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliuYunlin64002Taiwan Institute of Information Society University of Public ServiceBudapest1083Hungary John Von Neumann Faculty of Informatics Obuda UniversityBudapestHungary Institute of Information Engineering Automation and MathilticsSlovak University of Technology in BratislavaSlovakia

Many organizations have insisted on protecting the cloud server from the outside,although the risks of attacking the cloud server are mostly from the *** are many algorithms designed to protect the cloud server from attacks that have been able to protect the cloud server ***,the attackers have designed even better mechanisms to break these security *** cryptography is the best data protection algorithm that exchanges data between authentic *** this article,one symmetric cryptography algorithm will be designed to secure cloud server data,used to send and receive cloud server data securely.A double encryption algorithm will be implemented to send data in a secure ***,the XOR function will be applied to plain text,and then salt technique will be ***,a reversing mechanism will be implemented on that data to provide more data *** decrypt data,the cipher text will be reversed,salt will be removed,andXORwill be *** the end of the paper,the proposed algorithm will be compared with other algorithms,and it will conclude how much better the existing algorithm is than other algorithms.

关键词： Cryptography symmetric algorithm encryption decryption cipher text cloud security asymmetric algorithm

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