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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Dubey, Kumar Pradyot Gnanaprakasam, C.N. Khan, Ihtiram Raza Sadik, Md Shibli Al-Farhani, Liwa H. Ray, Samrat Department of Computer and Information Science Jagadguru Ram Bhadracharya Divyanga University UP Chitrakoot India Department of Electronics and Instrumentation Engineering St. Joseph’s College of Engineering Tamilnadu Chennai India Computer Science Department Jamia Hamdard Delhi India University of Portsmouth Portsmouth United Kingdom System Analysis Control and Information Processing Dep Academy of Engineering RUDN University Moscow Russia The Institute of Industrial Management Economics and Trade Peter The Great Saint Petersburg Polytechnic University Russia

ISBN: (纸本)9781032669663

Enterprise-focused blockchain applications that offer safe, anonymous, and immutable transactions are growing as blockchain technology matures. Traditional blockchain architecture has low performance and scalability, making it unsuitable for enterpriselevel applications with high concurrency and massive data. This paper studies and proposes a simplified Byzantine fault-tolerant (SBFT) consensus algorithm to improve consensus stage efficiency, a Task parallel smart contract model to maximise multi-core system parallel efficiency, and an improved blockchain system architecture to reflect the lightweight, low coupling nature of blockchain technology. It facilitates corporate application secondary development and the ParaChain blockchain and smart contract technology. Experimental verification compares the parallelization - based ParaChain blockchain’s TPS and scalability. PBFT-based blockchain systems have been greatly improved. © 2024 The Author(s).

关键词： Smart contract

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Fine-Tuning Pre-Trained Models for Automated Analysis of Ophthalmic Imaging in Diagnosing Eye Diseases

Fine-Tuning Pre-Trained Models for Automated Analysis of Oph...

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Information Technology (ACIT)

作者： Rabia Emhamed Al Mamlook Ahmad Nasayreh Hasan Gharaibeh Mohammad Aljaidi Qais Al-Na'amneh Dalia Alzu'bi Hanin Bzizi Abdelrahman Abdeltawab Dep. of Business Administration Trine University Indiana USA Department of Industrial Engineering University Zawia Tripoli Libia Dep. Computer Science Yarmouk University Irbid Jordan Dep. of Computer Science Zarqa University Zarqa Jordan Dep. of Cyber Security Applied Science Private University Amman Jordan Dep. Information and Systems Engineering Concordia University Montreal Canada Dep of Biomedical Science Western Michigan University Kalamazoo MI USA Faculty of pharmacy Bani Sweif university Bani Suwayf Egypt

This paper searches into the convergence of such ad-vanced techniques with architectures like DenseNet201, VGG16, InceptionResNetV2, and NasNetMobile. Our focus centers on harnessing deep learning capabilities for the precise detection of eye ailments. Preliminary findings spotlight a notable uplift in diagnostic precision. Among the tested algorithms, the Nas-NetMobile architecture emerged superior, boasting an impressive accuracy rate of 92% on the chosen dataset. Through this work, we extend a significant advancement in the realm of automated eye disease diagnosis, potentially equipping medical professionals with sharper, swifter diagnostic tools. The outcomes presented herein could play a seminal role in sculpting more sophisticated and precise diagnostic approaches within ophthalmology.

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Experimental Comparison of Global Planners for Trajectory Planning of Mobile Robots in an Unknown Environment with Dynamic Obstacles

Experimental Comparison of Global Planners for Trajectory Pl...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Zehra Tüfekçi Gökhan Erdemir Department of Computer Engineering Istinye University İstanbul Turkiye Department of Computer Science and Engineering Istanbul Sabahattin Zaim University Dep. of Engineering Management & Technology University of Tennessee at Chattanooga Tennessee USA

Interacting with their workspace, detecting obstacles, and real-time path planning in the field to reach the goal in the unknown environment are current working areas of mobile robotics. Working in an unknown environment with dynamic obstacles is a challenging topic for autonomous robots, which need to protect themselves from the dynamic obstacles they encounter, not damage the obstacle, and re-plan their path according to their new position. This study performed an experimental comparison of three different global planners for trajectory planning of mobile robots in an unknown environment with dynamic obstacles. Global Planner, Carrot Planner, and NavfnROS planners in the ROS package were used as global planners in two different mazes with dynamic obstacles. The durations from the start to the goal point in the two designed environments were determined for each global planner.

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Studying Risks of Hybrid Reengineering on Air-Transportation Systems Management “A Case Study on Jordanian Civil Aviation Regulatory Commission (CARC)”

Studying Risks of Hybrid Reengineering on Air-Transportation...

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Information Technology (ACIT)

作者： Al Refai Mohammed N. Taani M.K. K. Ahmed Ali Otoom Ghassan Samara Hanandeh E. S Hayel Khafajeh Software Engineering Dep. Zarqa University Zarqa Jordan Cybersecurity and Cloud Computing Dep. Applied Science Private University Amman Jordan Department of Computer Science Zarqa University Zarqa Jordan Artificial Intelligence Dep. Zarqa University Zarqa Jordan

This study examines decision-making in software re-engineering within businesses, focusing on the challenges and considerations involved. Financial constraints, time, and staff efforts are critical factors in these decisions. The study identifies difficulties faced by top-level management with legacy systems, existing systems, underused systems, and packaged software due to user resistance and customer dissatisfaction. The primary goal of the study is to assess the importance of software quality factors, especially from the users' perspective, in making re-engineering decisions. It uses the ISO 9126 Model to analyze quality elements in the case study software, aiming to provide guidance for deciding whether to proceed with re-engineering. The study explores functionality, reliability, usability, efficiency, maintainability, and portability as factors influencing re-engineering decisions, based on the ISO 9126 model. To understand user interactions and program performance, the study used unstructured participant observation in the case study software, highlighting the challenges faced by top management due to user resistance. These findings were further confirmed through face-to-face interviews with software users and department employees, offering insights into their perspectives on software quality elements. The results reveal that, despite some flaws, the system has valuable features and capabilities. Most employees express a desire to undergo re-engineering to enhance service quality, align with ISO 9126 standards, and leverage the expertise of competent staff for re-engineering activities.

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Fault-Tolerant FPGA-Based System for Mitigating SEUs in Configuration and User Bits

Fault-Tolerant FPGA-Based System for Mitigating SEUs in Conf...

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International Conference on Microelectronics, ICM

作者： O.T. Amer G.I. Alkady F.Y. Mohamed A.W. Mahmoud H.H. Amer R.M. Daoud Communication & Computer Eng. Dep. Faculty of Engineering Cairo University Cairo Egypt Electronics & Communications Engineering Department SEAD Group American University in Cairo Cairo Egypt

ISBN: (数字)9798350379396

ISBN: (纸本)9798350379402

This paper addresses two issues. First, in the context of factory automation, a low-cost fault-tolerant sensor system is proposed along with its FPGA-based voter. Second, the voter itself is designed to recover from failures affecting its own circuitry. The sensor system consists of one high-quality sensor used for measurement along with two functionally identical, but lower cost sensors used for monitoring purposes. A biased voter circuit is designed and implemented on the same Field Programmable Gate Array (FPGA) used to house the controller. It is shown that the voter can detect and recover from Single Event Upsets (SEUs) which often occur in the harsh factory environments. Both FPGA configuration and user bits are protected. It was shown that the proposed design requires less resources and power than some other designs presented in the literature. Focusing next on recovering from SEUs in both user and configuration FPGA bits, another use case is investigated, namely an I2C master; it is shown that the proposed design again requires less resources than some other commonly used techniques. Both proposed designs were implemented on the Xilinx Zynq-7000 (xc7z020clg400-1).

关键词： Power demand Fault tolerant systems Single event upsets Logic gates Reliability engineering Sensor systems Production facilities Field programmable gate arrays Monitoring Manufacturing automation

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Solving the vehicle routing problem with deep reinforcement learning

arXiv

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arXiv 2022年

作者： Foà, Simone Coppola, Corrado Grani, Giorgio Palagi, Laura Sapienza University of Rome Dep. of Computer Science Control and Management Engineering Rome Italy Sapienza University of Rome Dep. of Statistical Science Rome Italy

Recently, the applications of the methodologies of Reinforcement Learning (RL) to NP-Hard Combinatorial optimization problems has become a popular topic. This is essentially due to the nature of the traditional combinatorial algorithms, often based on a trial-and-error process. RL aims at automating this process. At this regard, this paper focuses on the application of RL for the Vehicle Routing Problem (VRP), a famous combinatorial problem that belongs to the class of NP-Hard problems. In this work, as first, the problem is modeled as a Markov Decision Process (MDP) and then the PPO method (which belongs to the Actor-Critic class of Reinforcement learning methods) is applied. In a second phase, the neural architecture behind the Actor and Critic has been established, choosing to adopt a neural architecture based on the Convolutional neural networks, both for the Actor and the Critic. This choice resulted effective to address problems of different sizes. Experiments performed on a wide range of instances show that the algorithm has good generalization capabilities and can reach good solutions in a short time. Comparisons between the algorithm proposed and the state-of-the-art solver OR − TOOLS show that the latter still outperforms the Reinforcement learning algorithm. However, there are future research perspectives, that aim to upgrade the current performance of the algorithm *** Codes 90-08 © 2022, CC BY.

关键词： Reinforcement learning

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PUSH: a primal heuristic based on Feasibility PUmp and SHifting

arXiv

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arXiv 2022年

作者： Agasucci, Valerio Coppola, Corrado Grani, Giorgio Sapienza University of Rome Dep. of Computer Science Control and Management Engineering Rome Italy Sapienza University of Rome Dep. of Statistical Sciences Rome Italy

This work describes PUSH, a primal heuristic combining Feasibility Pump and Shifting. The main idea is to replace the rounding phase of the Feasibility Pump with a suitable adaptation of the Shifting and other rounding heuristics. The algorithm presents different strategies, dep.nding on the nature of the partial rounding obtained. In particular, we distinguish when the partial solution is feasible, infeasible with potential candidates and infeasible without candidates. We used a threshold to indicate the percentage of variables to round with our algorithm and which other to round to the nearest integer. Most importantly, our algorithm tackles directly equality constraints without duplicating rows. We select the parameters of our algorithm on the 19 instances provided for the Mip Competition 2022. Finally, we compared our approach to other start heuristics, like Simple Rounding, Rounding, Shifting and Feasibility Pump on the first 800 MIPLIB2017 instances ordered by the number of non *** Codes 90-08 Copyright © 2022, The Authors. All rights reserved.

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A Three-Phase Totem-Pole AC-DC Converter Based Off-Board Charger for Electric Vehicles

A Three-Phase Totem-Pole AC-DC Converter Based Off-Board Cha...

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International Youth Conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Tony Mamdouh Ibrahim Abdelsalam Mostafa I. Marei Electrical and Control Engineering Dep. College of Engineering & Technology. Arab Academy for Science Technology & Maritime Transport Cairo Egypt Electrical Power and Machines Department Faculty of Engineering Ain Shams University Cairo Egypt

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

This paper presents the design, implementation, and performance evaluation of a three-phase bridgeless totem-pole off-board charger specifically developed for electric vehicles (EVs). The charger is characterized by a modular architecture that allows for scalability, consisting of three single-phase parallel bridgeless totem-pole AC-DC converters, each capable of supplying one-third of the total rated power. The control system of the charger employs three cascaded control loops to ensure stable operation and facilitate a seamless transition from current control mode to voltage control mode throughout the battery charging process, accommodating a wide range of EV battery configurations. Furthermore, the charger is engineered to support and improve grid power quality, ensuring a sinusoidal grid current waveform and unity power factor, thereby enhancing efficient power transfer while minimizing grid disturbances. The performance of this level ‘3’ charger was assessed and validated through MATLAB/Simulink simulations, with testing conducted on battery bank voltages of 400V, 800V, and lOOOV for three electric vehicles.

关键词： Reactive power Scalability Power quality Process control Electric vehicles Batteries MATLAB Voltage control Vehicle dynamics Testing

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Improved Distance (Sensitivity) Oracles with Subquadratic Space

Improved Distance (Sensitivity) Oracles with Subquadratic Sp...

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Annual IEEE Symposium on Foundations of computer Science

作者： Davide Bilò Shiri Chechik Keerti Choudhary Sarel Cohen Tobias Friedrich Martin Schirneck Dep. of Inf. Eng. CS and Mathematics University of L'Aquila Department of Computer Science Tel Aviv University Dep. of CS and Engineering Indian Institute of Technology Delhi School of Computer Science The Academic College of Tel Aviv-Yaffo Hasso Plattner Institute University of Potsdam Faculty of Computer Science University of Vienna

ISBN: (数字)9798331516741

ISBN: (纸本)9798331516758

A distance oracle (DO) for a graph $G$ is a data structure that, when queried with vertices $s,t$ , returns an estimate $\widehat{d}(s,t)$ of their distance in $G$ . The oracle has stretch $(\alpha, \beta)$ if the estimate satisfies $d(s,t)\leqslant \widehat{d}(s,t)\leqslant \alpha\cdot d(s,t)+\beta$ . An $f-\mathbf{edge}$ fault-tolerant distance sensitivity oracle $(f-\mathbf{DSO})$ additionally receives a set $F$ of up to $f$ edges and estimates the distance in $G-F$ . Our first contribution is the design of new distance oracles with subquadratic space for undirected graphs. We show that introducing a small additive stretch $\beta > 0$ allows one to make the multiplicative stretch $\alpha$ arbitrarily small. This sidesteps a known lower bound of $\alpha\geqslant 3$ (for $\beta=0$ and subquadratic space) [Thorup & Zwick, JACM 2005]. We present a DO for graphs with edge weights in $[0, W]$ that, for any positive integer $\ell$ and any $c\in(0,\ell/2]$ , has stretch $(1+\frac{1}{\ell},2W)$ , space $\widetilde{O}(n^{2-\frac{c}{\ell}})$ , and query time $O(n^{c})$ , generalizing results by Agarwal and Godfrey [SODA 2013] to arbitrarily dense graphs. Our second contribution is a framework that turns an $(\alpha,\beta)- \mathbf{stretch}$ DO for unweighted graphs into an $(\alpha(1+\varepsilon),\beta)-\mathbf{stretch}. f-\mathbf{DSO}$ with sensitivity $f=o(\log(n)/\log\log n)$ retaining sub-quadratic space. This generalizes a result by Bilò, Chechik, Choudhary, Cohen, Friedrich, Krogmann, and Schirneck [TheoretiCS 2024]. Combining the framework with our new DO gives an $f-\mathbf{DSO}$ that, for any $\gamma\in(0, (\ell+1)/2]$ , has stretch $((1+\frac{1}{\ell})(1+\varepsilon), 2)$ , space $n^{2-\frac{\gamma}{(t+1)(f+1)}+o(1)}/\varepsilon^{f+2}$ , and query time $\widetilde{O}(n^{\gamma}/\varepsilon^{2})$ . This is the first $f-\mathbf{DSO}$ with subquadratic space, n

关键词： computer science Fault tolerance Sensitivity Additives Fault tolerant systems Data structures

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Genetic Optimization Techniques for Enhancing Web Attacks Classification in Machine Learning

Genetic Optimization Techniques for Enhancing Web Attacks Cl...

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IEEE International Symposium on dep.ndable, Autonomic and Secure Computing (DASC)

作者： Ameera S. Jaradat Ahmad Nasayreh Qais Al-Na'amneh Hasan Gharaibeh Rabia Emhamed Al Mamlook Dep. of Computer Science Yarmouk University Irbid Jordan Dep. of Cyber Security and Cloud Computing Applied Science Private University Amman Jordan Dep. of Business Administration Trine University Indiana USA Department of Industrial Engineering University Zawia Tripoli Libia

Web-based applications are now the preferred approach for delivering a variety of services via the Internet. As a result of the globalization of commerce, web applications have been growing quickly and becoming increasingly complicated. Such applications have a significant security vulnerability in the online environment since they were developed with little experience and without testing or validation. Numerous attackers use this security vulnerability to take control of the program, modify the data, and steal the most crucial information. They may also access all internal, unauthorized items. This work presents a hybrid model that classifies website attacks as benign through the integration of four machine learning algorithms: gradient boost (GB), multilayer perceptron (MLP), logistic regression (LR) and K nearest neighbor (KNN). The work dep.oyed Tree-based Pipeline Optimization Tool (TPOT) that utilizes the Genetic algorithm (GA) to extract the optimal parameter and consequently enhance the model performance. The model underwent evaluation utilizing a data set from the Canadian Institute 2023 that contains various types of attacks. Among these algorithms, GB achieved the best accuracy scores of 95%, 94% and 95% for accuracy, recall and F1-score, respectively.

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