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ACDD: Automated COVID Detection using Deep Neural Networks

IEIE Transactions on Smart Processing and Computing 2023年第6期12卷 518-525页

作者： Raza, Ghulam Musa Shoaib, Muhammad Kim, Byung-Seo Department of Software and Communications Engineering Hongik University Sejong Korea Republic of School of Electrical Engineering and Computer Science National University of Science and Technology Islamabad Pakistan

December 2019 witnessed the outbreak of a novel coronavirus, thought to have started in the Chinese city of Wuhan. The situation worsened owing to its quick spread across the globe, leading to a worldwide pandemic that became known as COVID-19. To suppress the pandemic, early detection of positive COVID-19 patients has become highly important. There is a lack of precise automated tool kits available for use in diagnosing medical conditions, so auxiliary diagnostic tools are in high demand. Important information about this virus can be extracted from X-ray images, which can be used in conjunction with advanced artificial intelligence. This study addresses the unavailability of physicians in remote areas, and the complex algorithm proposed in this study can find potential matches for patients in rural areas who need care. This could help to improve access to care for those who need it most. The purpose of this study is to develop a novel model that can automatically detect COVID-19 by utilizing chest X-ray images. The proposed model incorporates binary and multi-class classification and can be employed by radiologists for timely detection of the COVID-19 virus in an effective manner. © 2023 The Institute of Electronics and Information Engineers.

关键词： COVID-19

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Improved Quasi-Random Designs with Constant Pool Sizes for Group Testing 18

Improved Quasi-Random Designs with Constant Pool Sizes for G...

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18th International Symposium on Information Theory and Its Applications, ISITA 2024

作者： Hamada, Ryouji Lu, Xiao-Nan Graduate School of Informatics and Engineering The University of Electro-Communications Department of Computer and Network Engineering Chofu-shi Tokyo Japan Gifu University Faculty of Engineering Department of Electrical Electronics and Computer Engineering Gifu-shi Gifu Japan

ISBN: (纸本)9784885523519

Group testing is a well-studied approach for identifying defective items among a large amount of items by conducting a relatively small number of tests on pools of items. In this paper, we propose a novel method for generating quasi-random designs with constant pool sizes for noiseless non-adaptive group testing. Our approach incorporates insights from combinatorial properties to optimize the distribution of Hamming distances in pooling designs. Simulations with established practical decoding algorithms show that our quasi-random designs outperform existing random and quasi-random methods in both identification accuracy and stability. These improved designs have the potential to provide significant benefits for real-world applications of group testing, such as PCR testing in large populations and network security. © 2024 The Institute of Electronics, Information and Communication Engineers.

关键词： Hamming distance

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The Algorithm and VLSI Architecture of High-Throughput and Highly Efficient Tensor Decomposition Engine

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IEEE Transactions on Circuits and Systems I: Regular Papers 2024年第7期71卷 3134-3145页

作者： Tsai, Ting-Yu Shen, Chung-An Wu, Tsung-Lin Huang, Yuan-Hao National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei106335 Taiwan MediaTek Corporation Hsinchu300 Taiwan National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu300 Taiwan

Tensor decomposition is critical for compressing data and extracting key features in novel high-dimensional signal processing systems. However, due to the enormous amount of data and the highly complicated computations, designing an efficient tensor decomposition processor is very challenging. This paper presents the algorithm and VLSI architecture design of a low-latency and high-throughput tensor decomposition processor. A parallel higher-order orthogonal iteration (P-HOOI) algorithm is proposed where multiple updated matrices are computed concurrently. Thus, a low-latency tensor decomposition is achieved. Furthermore, a novel VLSI architecture is presented so that the efficiency of the component utilization is improved and the hardware complexity is greatly reduced. Therefore, the proposed tensor decomposition processor enhances the processing throughput with minimum employment of hardware components. Performance evaluations based on the post-layout estimations in the ASIC flow and based on the FPGA platform are reported in this paper. Compared with state-of-the-art designs in the literature the proposed tensor decomposition engine greatly enhances the throughput and hardware efficiency. © 2004-2012 IEEE.

关键词： Engines

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R3 - Rescale, Rotate, and Randomize: A Novel Image Cryptosystem Utilizing Chaotic and Hyper-Chaotic Systems

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IEEE Access 2023年 11卷 119284-119312页

作者： Gabr, Mohamed Korayem, Yousef Chen, Yen-Lin Yee, Por Lip Ku, Chin Soon Alexan, Wassim Faculty of Media Engineering and Technology Computer Science Department Cairo11835 Egypt National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia Faculty of Information Engineering and Technology Communications Department Cairo11835 Egypt New Administrative Capital Mathematics Department Cairo13507 Egypt

This work proposes a novel image encryption algorithm that integrates unique image transformation techniques with the principles of chaotic and hyper-chaotic systems. By harnessing the unpredictable behavior of the Chua system and the hyper-chaotic nature of the Chen system, the algorithm carries out rescaling, rotation, and randomization on the target image. The intrinsic unpredictability and sensitivity to initial conditions of these chaotic systems endow the encryption algorithm with an expansive key space of 25208. This feature not only bolsters its resilience against brute-force attacks but also magnifies its overall security profile. The algorithm's efficiency is evident in its rapid computational speed and lean resource consumption, making it suitable for real-time applications. To gauge its robustness, a battery of rigorous tests and analyses, spanning differential attacks, statistical attacks, and brute-force assaults, were employed. The results validate its ability to resist a diverse spectrum of threats. With its expansive key space, exceptional efficiency, and sturdy defenses, the proposed algorithm emerges as a potential cornerstone for safeguarding digital images in arenas like secure communication, data storage, and multimedia transmission. In sum, this research pushes the boundaries of high-security image encryption methodologies, catering to the burgeoning demands of the digital age. © 2013 IEEE.

关键词： Cryptography

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Deep Reinforcement Learning Algorithms for Location Optimization in Multi-RAT UAV-Assisted Heterogeneous Networks 5

Deep Reinforcement Learning Algorithms for Location Optimiza...

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5th International IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2023

作者： Anany, M.G. Elmesalawy, Mahmoud M. Ibrahim, Ibrahim I. El-Haleem, Ahmed M. Abd Department of Electronics and Communications Cairo Egypt Helwan University Communications and Computer Faculty of Engineering Department of Electronics Cairo Egypt

ISBN: (纸本)9798350381030

Due to the unprecedented growth in wireless mobile connectivity, the next generations of wireless networks are required to meet the different requirements of the diverse devices. One of the promising solutions for the wireless network design is the Unmanned Aerial Vehicles (UAVs), which provide flexibility and dynamic mobility, that can be exploited to extend capacity for unexpected and unplanned increases in demand. In this paper, different Deep Reinforcement Learning (DRL) approaches along with different reward functions are compared, to optimize the 3D location of an Unmanned Aerial Vehicle (UAV) carrying Multiple Radio AccessTechnologies (Multi-RAT) base stations in a Multi-RAT Heterogeneous Network (HetNet) environment, based on the network conditions and users' demands. The idea of deploying Multi-RAT base stations on a UAV will increase the system capacity by exploiting the same resources, however, it will be more challenging to optimize the complex UAV's 3D location to maximize the users' experience. Extensive simulations are conducted to evaluate and compare the performance of the different DRL approaches, and the different reward functions, which revealed that the instantaneous reward function and the Double Deep Q-Network (DDQN) algorithm are more effective in terms of average user satisfaction and stability in solving the proposed optimization problem. © 2023 IEEE.

关键词： Heterogeneous networks

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Enhancing Agricultural Efficiency with Blockchain-Orchestrated Drone Swarms and Kubernetes 6

Enhancing Agricultural Efficiency with Blockchain-Orchestrat...

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6th IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2024

作者： Soliman, Shebl Bendary, Ahmed Dahshan, Hisham Military Technical College Communications Engineering Department Cairo Egypt Future University Computer Science Department Cairo Egypt

ISBN: (纸本)9798350378511

Integrating advanced technologies in agriculture is essential for secure, transparent, and efficient data management. In this paper, we propose a blockchain-based smart agriculture architecture that leverages Hyperledger Fabric deployed on a Kubernetes cluster to support drone swarm operations in agricultural applications. The proposed architecture comprises a multi-organization blockchain network, where each organization operates a peer and multiple orderer nodes. Utilizing the chaincode-as-a-service model enables dynamic updates of smart contracts, ensuring adaptability and flexibility. Robust communication between drones and the blockchain network is facilitated through APIs, enabling real-time data collection and decision-making. In addition, a custom chaincode is developed to cater to agricultural needs, offering functions such as drone registration, data updates, and querying based on parameters such as location and battery status. The performance of the chaincode is evaluated using Hyperledger Caliper with various transaction rates, including fixed and linear scenarios. The results demonstrate that our blockchain-based architecture significantly enhances the reliability, security, and scalability of agricultural drone applications, providing a robust framework for future advancements. © 2024 IEEE.

关键词： Decision making

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Building an interoperable space for smart agriculture

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Digital communications and Networks 2023年第1期9卷 183-193页

作者： Ioanna Roussaki Kevin Doolin Antonio Skarmeta George Routis Juan Antonio Lopez-Morales Ethel Claffey Manuel Mora Juan Antonio Martinez Institute of Communications and Computer Systems AthensGreece Walton Institute WaterfordIreland Department of Information and Communications Engineering University of MurciaMurciaSpain School of Business Waterford Institute of TechnologyWaterfordIreland R&D Department Odin SolutionsMurciaSpain

The digital transformation in agriculture introduces new challenges in terms of data,knowledge and technology adoption due to critical interoperability issues,and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be ***(Building an Interoperable,Data-Driven,Innovative and Sustainable European Agri-Food Sector)addresses these challenges by providing an overarching solution that integrates various heterogeneous hardware and software resources(e.g.,devices,networks,platforms)and enables the seamless sharing of data and knowledge throughout the agri-food *** paper introduces the main concepts of DEMETER and its reference architecture to address the data sharing and interoperability needs of farmers,which is validated via two rounds of 20 large-scale pilots along the DEMETER *** paper elaborates on the two pilots carried out in region of Murcia in Spain,which target the arable crops sector and demonstrate the benefits of the deployed DEMETER reference architecture.

关键词： Smart agriculture Internet of things(IoT) DEMETER Reference architecture Interoperability Agricultural information model(AIM) Pilot validation

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection Systems

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computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa Sami Khafaga El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Rashid Amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of System Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing SMOTE

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Software design and FPGA implementation of optimized medical image fusion techniques

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Multimedia Tools and Applications 2025年 1-31页

作者： Elshazly, E.A. El-Shafai, Walid El-Hoseny, Heba El-Rabaie, El-Sayed M Zahran, O. Abdelwahab, Safey A. S. El-Halawany, M.M. Fikry, R.M. Elaraby, S.M. Faragallah, Osama S. Mohamed, Wael A. Mahmoud, Korany R. Abd El-Samie, Fathi E. Cairo Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Faculty of Computer Studies Arab Open University 11681 Riyadh Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif University 11099 Taif21944 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Benha University Benha Egypt Electronics and Communications Engineering Department Faculty of Engineering Helwan University Helwan Egypt Giza Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Nowadays, medical image fusion plays a crucial role in enhancing the diagnosis accuracy and the clinical decision-making process in various healthcare applications. This research work presents a comprehensive study of the design and implementation of optimized medical image fusion techniques using a combination of software and Field-Programmable Gate Array (FPGA) technologies. The proposed medical image fusion strategy is based on the utilization of Discrete Wavelet Transform (DWT) and Modified Central Force Optimization (MCFO). The implementation of the proposed technique as well as the traditional medical image fusion techniques is considered using an appropriate software design and FPGA. The presented techniques aim to overcome the limitations of traditional fusion techniques by integrating advanced image processing algorithms, optimization algorithms, and parallel computing capabilities offered by FPGA platforms. The first step in the proposed framework is to match the histogram of one of the images with that of the other, so that both images will have the same dynamic range. After that, the DWT is used to decompose the images that should be fused together. Based on some constraints, the MCFO optimization algorithm is used to evaluate the optimum level of decomposition and the optimum parameters for the best fusion quality. Finally, to improve the obtained visual quality and reinforce the information in the fusion result, an additional contrast enhancement step using adaptive histogram equalization is applied to the fusion result. Comparative study between the proposed optimized DWT-based fusion framework, the traditional Principal Component Analysis (PCA), Additive Wavelet Transform (AWT), and DWT-based fusion techniques is presented. Various metrics of fusion quality are considered, including average gradient, standard deviation, local contrast, entropy, edge strength, Peak Signal-to-Noise Ratio (PSNR), Qab/f, and processing time. The proposed optimized DWT-ba

关键词： MATLAB

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A low-cost buoyant force measurement device for monitoring sugar concentration in water solution

A low-cost buoyant force measurement device for monitoring s...

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2023 International Conference on Electrical, computer, communications and Mechatronics engineering, ICECCME 2023

作者： Kaučić, Luka Kovačević, Ivana Aleksi, Ivan Keser, Tomislav Zidar, Josip Rimac-Drlje, Snježana Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Computer Engineering and Automation Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Communications Osijek Croatia

ISBN: (纸本)9798350322972

Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs. © 2023 IEEE.

关键词： Fermentation

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