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3rd International Conference on Distributed Sensing and Intelligent Systems, ICDSIS 2022

作者： Elsaeed, Nadine Y. Alshaarawy, Mariam M. Esmaiel, Abd Elrhman S. El-Deen Elmahdy, Seif Abdelhameed, Omar Fakhry, Mariam M. Ogabih, Naglaa A. Ali, Nouran M. El-Deeb, Reem Software Engineering Department Faculty of Computers and Information Mansoura University Mansoura35516 Egypt Computer Science Department Faculty of Computers and Information Mansoura University Mansoura35516 Egypt The Department of Computer Science Faculty of Computers and Information Mansoura University P.O. Box: 35516 Mansoura Egypt

ISBN: (纸本)9781839538186

In a world where nearly everything we do depends on sight;it is ever more challenging for the unsighted to cope with it and lead a normal life without being reliant on the presence of a companion. Finding a mechanism to convey visual information to the brain is the most difficult part of the research as well as the development of efficient sensory replacement and augmentation systems. In this paper, we aim to propose Brain Sight as an innovative system to help blind people identifying and discovering things in front of them using vibro-tactile display for vision sensory substitution. Brain Sight is a wearable vest-like fabric containing small vibration motors that displays pulses to map the seen images on the Lower-back of the visually impaired. A deep labeling segmentation and edge detection techniques are applied to the captured image after preprocessing. A simple prototype is implemented and tested with volunteers. Thanks to neuroplasticity and the cognitive cortex inside humans' brain, the implemented vest showed promising results. Without the need for intensive training, Brain Sight enables blind to recognize different shapes and numbers. © IET Conference Proceedings 2022.

关键词： Semantics

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A public data-set for synchronous motor electrical faults diagnosis with CNN and LSTM reference classifiers

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Energy and AI 2023年第4期14卷 221-237页

作者： Zhenglong Sun Ram Machlev Qianchao Wang Juri Belikov Yoash Levron Dmitry Baimel Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)JilinChina The Andrew and Erna Viterbi Faculty of Electrical&Computer Engineering Technion-Israel Institute of TechnologyHaifa 3200003Israel Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China Department of Software Science Tallinn University of TechnologyAkadeemia tee 15a12618 TallinnEstonia Department of Electrical and Electronics Engineering Sami Shamoon College of EngineeringBeer-Sheva84100Israel

In the last two decades,motor operation monitoring tools have become a necessity,and many studies focus on the detection and diagnosis of motor electrical ***,at present,a core obstacle that prevents the direct comparison of such classification techniques is the lack of a standard database that can be used as a *** view of this,we offer here a public experimental data-set that has beendesigned specifically for the comparison of synchronous motor electrical fault *** data-set comprises five types of motor electrical faults:open phase between inverter and motor;short circuit/leakage current between two phases;short circuit/leakage current in phase-to-neutral;rotor excitation voltage disconnection;and variation of rotor excitation *** addition,each fault has been recorded as a four-dimensional signal:three phase voltages;three phase currents;motor speed;and motor *** package includes two deep-learning reference classifiers that are based on a convolutional neural network(CNN)and long short term memory(LSTM).Due to the good performance of these classifiers,we suggest that they can be used by the community as benchmarks for the development of new and better motor electrical fault classification *** database and the reference classifiers are examined and insights regarding different combinations of features and lengths of recording points are *** developed code is available online,and is free to use.

关键词： Motor faults Synchronous motors Public data-set Classification Deep-learning CNN LSTM

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Mimd Programs Execution Support on Simd Machines

SSRN

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SSRN 2023年

作者： Mustafa, Dheya Alkhasawneh, Ruba Obeidat, Fadi Shatnawi, Ahmed S. Department of Computer Engineering Faculty of Engineering The Hashemite University Zarqa13133 Jordan Department of Communication and Computer Engineering Faculty of Engineering Al-Ahliyya Amman University Amman19111 Jordan Synopsys Inc. AustinTX United States Department of Software Engineering Jordan University of Science and Technology Irbid21110 Jordan

Single Instruction Multiple Data (SIMD) architecture, supported by various high-performance computing platforms, efficiently utilizes data-level parallelism. SIMD model is used in traditional CPUs, dedicated vector systems, and accelerators such as GPUs, vector extensions, and Xeon Phi. It provides performance throughput in computation-intensive and data-parallel applications. Despite the similarity of data-processing principles between these architectures, porting various programming models between the reviewed platforms is challenging. Furthermore, enhancing the programmability of these architectures is an important feature for utilizing their emerging computing power, and simplifying programming complexity. This paper reviews the basic principles of optimization techniques to run asynchronous Multiple Instruction Multiple Data (MIMD) on SIMD accelerators. It also surveys several GPU programming paradigms and application programming interfaces (API) and classifies these frameworks into different groups based on their criteria. In addition, a review of studies that performed a comparison of collaborative execution of GPUs with CPUs and XeonPhi is presented in this paper. It is believed that this study will be beneficial for developers and researchers in the field of computer architecture and parallel computing-intensive scientific applications, specifically for early-stage high-performance computing researchers to obtain a brief of performance optimization opportunities as well as challenges of existing SIMD platforms. © 2023, The Authors. All rights reserved.

关键词： Program processors

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Digital Platform to Empower the Self-Employment in Sri Lanka 6

Digital Platform to Empower the Self-Employment in Sri Lanka

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6th International Conference on Information Technology Research, ICITR 2021

作者： Wickramasinghe, H.C.P. Thebuwana, T.D. Wijesinghe, G.K.H.S. Dissanayake, U.N. Kodagoda, Nuwan Suriyawansa, Kushnara Faculty of Computing Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Sri Lanka

ISBN: (纸本)9781665420006

Unemployment is a huge problem around the world because a lack of job opportunities. People are unable to find the job opportunities according to their preferences and qualifications. As a solution for this, many countries are attempting to empower self-employment. Most of current world problems have been solved using modern technologies. Therefore, the development of self-employment also can be achieved through modern technology. The objective of our proposed platform, HIRELANCER, is empowering self-employment using modern technologies. HIRELANCER is bringing the consumers, service providers, and suppliers into the same platform. HIRELANCER will consist of innovative features that go beyond comparatively to other platforms such as an advanced mechanism to find best suitable service providers/suppliers for the service, handling the virtual front-desk, cost estimation for the services prior to contacting a service provider, and advanced facility to find a suitable career path for the people who are seeking career guidance. This research paper discusses how the innovative features of HIRELANCER will be beneficial for consumers, service providers, and suppliers and ultimately achieve our main objective, which is empowering self-employment in Sri Lanka. © 2021 IEEE.

关键词： Employment

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Impact of Artificial Intelligence on software engineering Phases and Activities (2013–2024): A Quantitative Analysis Using Zero- Truncated Poisson Model

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IEEE Access 2025年 13卷 95535-95547页

作者： Durrani, Usman Khan Akpinar, Mustafa Bektas, Hakan Saleh, Mohammed Higher Colleges of Technology Faculty of Computer and Information Sciences Abu Dhabi United Arab Emirates Sakarya University Software Engineering Department Sakarya54050 Turkey Istanbul University Department of Econometrics Istanbul34452 Turkey

This paper presents the results of a quantitative analysis derived from data collected in our earlier systematic literature review, focusing on integrating Artificial Intelligence (AI) techniques across various phases of software engineering (SE). Employing a Zero-Truncated Poisson (ZTP) model, we analyzed 120 selected research papers to assess the impact of AI methodologies on SE phases. The findings indicate significant improvements attributable to AI in different phases of SE. Specifically, AI techniques have been found to enhance the accuracy of the planning, requirement engineering, and development phases and improve the efficiency of the requirement engineering and design phases. Notably, AI’s integration has markedly improved the accuracy and efficiency of the requirement engineering phase, underscoring AI’s critical role in advancing SE practices. This study contributes to a deeper understanding of the quantitative impact of AI on SE, providing valuable insights for practitioners and researchers in understanding AI technologies to enhance SE phases. © 2013 IEEE.

关键词： software design

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Data Transmission with Priority Service and Limited Capacity Storage in Unstationary Flow and High Load

Data Transmission with Priority Service and Limited Capacity...

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Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex (TIRVED)

作者： S. Z. Lygdenov I. Z. Lygdenova Faculty of Software Engineering and Computer Engineering ITMO University Saint-Petersburg Russia Medical Faculty First St. Petersburg University named after Academician Pavlov Saint-Petersburg Russia

Subject of research. The influence of priority service in a multichannel data transmission system with drives of limited capacity and high load with a non-stationary nature of the intensity of packets entering the system and service time in channels. Method. Calculation and analysis of the functional characteristics of a multichannel system is realized using simulation methods and mathematical statistics. Main results. A simulation model of a multichannel system with priority service is proposed to calculate the functional characteristics of a multichannel system with a high load. A number of experiments were carried out on the influence of priority maintenance on the efficiency and reliability of the system. Dependencies between stationary and non-stationary functional quantities have been identified. Practical significance. The presented research results can be used in the design of real multithreaded data transmission systems with a highly heterogeneous load.

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Fault Detection and Mitigation in Vehicle Platooning

Fault Detection and Mitigation in Vehicle Platooning

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Najeebuddin Ahmed Hassan Naser Amir Ameli Faculty of Engineering Lakehead University Thunder Bay Canada Department of Software Engineering Lakehead University Thunder Bay Canada Department of Electrical and Computer Engineering Lakehead University Thunder Bay Canada

This paper addresses the challenges posed by faults in the complex systems of autonomous vehicles within vehicle platoons. It presents a state-space model tailored for vehicle platoons, incorporating an Unknown Input Observer (UIO) to estimate internal states for each vehicle. By monitoring discrepancies between measured and estimated states, the framework effectively detects faults affecting a vehicle's position, velocity, and acceleration, often stemming from malfunctions in its control and navigation components. The paper also introduces fault detection and identification UIOs to pinpoint faulty parameters and estimate associated fault inputs. To validate its effectiveness, the proposed method undergoes MATLAB simulations across diverse scenarios, confirming its capability to mitigate faults within the vehicle platoon.

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Comparison of Standard and Modified Ant Colony Algorithm with Fuzzy system for Path Planning of Robot in Complex Environment

Comparison of Standard and Modified Ant Colony Algorithm wit...

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International Conference on Intelligent Systems: Theories and Applications (SITA)

作者： Sudeep Sharan Anh Tong Ngoc Minh Peter Nauth Juan José Domínguez-Jiménez Faculty of Computer Science and Engineering Frankfurt University of Applied Sciences Frankfurt am Main Germany UCASE Software Engineering Group School of Engineering University of Cádiz Cádiz Spain

The requirements of optimizing path planning for the autonomous robot are in high demand in such industrial communities, especially in manufacturing and caring social support. The application of meta-heuristic methods in autonomous problems is considered because of their adaptivity and robustness. Ant Colony Optimization (ACO) is one of the researchers’ approaches because of its effectiveness in the ant community. However, some constraints are making this method less productive. Therefore, this paper is to generate a modified ACO combined with Fuzzy logic (ACOFL) to minimize its drawbacks and maximize the robustness of path planning. This study presents the role of ACO algorithms in Path Planning, especially in the complex aspect, through the theoretical background of ACO and the other combination with other algorithms. The improved mathematics model evaluation demonstrates the upgrade steps in the path-finding process. Simulation results shows that the modified ACO algorithm is effective for complex environment compare to standard ACO algorithm. Moreover, the comparison results are presented in this paper between the standard ACO and modified ACO algorithm.

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Smart Farmer Education System for Disease Identification, Severity Assessment and Infestation Management (Brinjal) 17

Smart Farmer Education System for Disease Identification, Se...

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17th IEEE International Conference on Industrial and Information Systems, ICIIS 2023

作者： Bandara, Keshara Vidhanaarachchi, Samitha Nanayakkara, A.A.E. Kulasinghe, Kavindu Rajapakshe, Sanka Wickramasinghe, Asela Yapa, Kanishka Sri Lanka Institute of Information Technology Department of Information Technology New Kandy Road Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka University of Ruhuna Faculty of Agriculture Department of Soil Science Mapalana Kamburupitiya Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350323634

The agriculture industry is one of the most significant sources of foreign exchange and employment in the Sri Lankan market. Therefore, small crops play a crucial role in ensuring the food security of the population as they are integral components of Sri Lankan cuisine. However, industry experts have identified inefficient disease and pest management as a hindrance to production. This issue requires immediate attention and proper action, which can be effectively addressed through the utilization of ICT technologies. Consequently, this research paper proposes a smart system that aims to assist farmers and agriculture professionals by providing them with farmer education, disease and infestation management tools, as well as progression level calculations. The implementation of this system aims to uplift the agriculture industry in Sri Lanka. The developed 'AI-based mobile application system for Brinjal Diseases,' which is based on analyzing the eating patterns of leafhopper damage, presents an innovative approach to identify the most significant threats to Brinjal, specifically focusing on leafhopper damage. This proposed system effectively informs various stakeholders, including the Area Agricultural Research Officer, Seed Certification and Plant Protection Center (SCPPC), Agricultural Service Center, Office of the Register of Pesticides (ROP), Plant Protection Service (PPS), as well as farmers, regarding the dispersion and prevention of brinjal diseases and pest infections. © 2023 IEEE.

关键词： Crowdsourcing

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From Learning Agents to Agile software: Reinforcement Learning's Transformative Role in Requirements engineering

From Learning Agents to Agile Software: Reinforcement Learni...

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IEEE Southeastcon

作者： Faraz Frank Parsa Amir Ali Amiri Moghadam Turaj Ashuri Department of Computer and Software Engineering Faculty of Artificial Inteligence Karaj Azad University Karaj Persian Department of Robotics and Mechatronics Engineering Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University Marietta GA USA Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University Marietta GA USA

This paper studies the trans formative role of Reinforcement Learning for Requirements engineering in the context of software development. The integration of Reinforcement Learning, with its adaptive decision-making capabilities, and Requirements engineering, focused on systematic requirement analysis, offers a promising interaction to address challenges in dynamic project environments. The paper discusses the potential benefits, including adaptive decision-making, optimization in uncertainty, and intelligent requirement prioritization. However, challenges such as complexity, interpretability, data availability, resource intensiveness, and ethical concerns are identified. The conclusion highlights the trans formative potential of this integration while emphasizing the importance of addressing challenges through interdisciplinary collaboration and responsible adoption in different environments. The paper serves as a broad study of the intersection of Reinforcement Learning and Requirements engineering, providing insights for practitioners, researchers, and stakeholders in the field of software development.

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