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Railway Track Fault Detection Using Mel Frequency Cepstral Coefficient from Acoustic Data using Chi Square

Chinese Journal of Electronics 2023年

作者： Furqan Rustam Abid Ishaq Muhammad Shadab Alam Hashmi Hafeez-Ur-Rehman Siddiqui Imran Ashraf School of Computer Science University College Dublin Faculty of Computer Science and Information Technology Khawaja Fareed University of Engineering and Information Technology Department of Information and Communication Engineering Yeungnam University

Spatial, temporal, and weather elements like ballast, loose nuts, misalignment, and cracks due to rain, snow, and earthquakes may lead to railway accidents and cause human and financial loss. Manual inspection is erroneous, labor-intensive, and *** automatic inspection provides a fast, reliable, and unbiased solution in this regard, however, ensuring high accuracy for fault detection is challenging due to the lack of public datasets, noisy data, high computer processing requirements, and inefficient models. This study presents an approach that uses Mel frequency cepstral coefficient features from the acoustic data. The dataset gathered using a customized railway cart from our previous research is used for experiments. The focus of the study is to increase the fault detection performance using selective features from the acoustic data. This study employs Chisquare(Chi2) for the selection of important features and involves performance analysis of machine learning and deep learning models using selected features. Experimental results suggest that using 60 features, 40 original features, and 20 Chi2 features, produces optimal results both regarding accuracy and computational complexity. A 100%accuracy can be obtained using the proposed approach with machine learning models. Moreover, this performance is significantly better than existing approaches.

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Preliminary Exploration on Node-To-Node Fault Tolerance Coordination in Distributed system

Preliminary Exploration on Node-To-Node Fault Tolerance Coor...

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2023 IEEE International Conference on Computing, ICOCO 2023

作者： Saadoon, Muntadher Hamid, Siti Hafizah Ab. Sofian, Hazrina Altarturi, Hamza Nasuha, Nur Azizul, Zati Hakim Khalid, Haqi Universiti Malaya Faculty of Computer Science and Information Technology Department of Software Engineering Kuala Lumpur50603 Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Department of Artificial Intelligence Kuala Lumpur50603 Malaysia Universiti Putra Malaysia Faculty of Engineering Department of Computer and Communication Selangor 43400 Malaysia

ISBN: (纸本)9798350302684

Internet of Things, edge computing devices, the widespread use of artificial intelligence and machine learning applications, and the extensive adoption of cloud computing pose significant challenges to maintaining fault tolerance in distributed systems. As the volume and complexity of systems continue to grow, the probability of system failures also grows, leading to downtime and poor performance. Fault tolerance is pivotal in modern computing systems by preventing downtime and service disruptions, even during failures. However, adopting fault tolerance comes with additional resource consumption, such as memory, CPU, disk, and network bandwidth usage, impacting system performance. Balancing fault tolerance with system performance is crucial to optimize resource utilization while minimizing the costs associated with detecting and recovering from faults. This paper introduces a node-to-node fault tolerance coordination mechanism for distributed systems to facilitate the tradeoff between fault tolerance and the cost of performance penalties and resource consumption. The proposed mechanism is preliminarily implemented on HDFS cluster. Our proposal enables opportunities to minimize the cost of the fault tolerance impact on performance and resource usage compared to the existing fault tolerance coordination mechanism. © 2023 IEEE.

关键词： Fault tolerance

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Modelling and Performance Analysis of Visible Light communication system in Industrial Implementations

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computers, Materials & Continua 2023年第11期77卷 2189-2204页

作者： Mohammed S.M.Gismalla Asrul I.Azmi Mohd R.Salim Farabi Iqbal Mohammad F.L.Abdullah Mosab Hamdan Muzaffar Hamzah Abu Sahmah M.Supa’at Faculty of Electrical Engineering Faculty of EngineeringUniversiti TeknologiMalaysiaSkudai81310Malaysia Lightwave Communications Research Group(LCRG) Faculty of Electrical EngineeringUniversiti TeknologiSkudaiJohorMalaysia Department of Communication Engineering Faculty of Electrical and Electronic EngineeringUniversiti Tun Hussein Onn Malaysia(UTHM)Parit RajaBatu PahatJohor86400Malaysia Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Department of Computer Science University of São PauloSão PauloBrazil

Visible light communication(VLC)has a paramount role in industrial implementations,especially for better energy efficiency,high speed-data rates,and low susceptibility to ***,since studies on VLC for industrial implementations are in scarcity,areas concerning illumination optimisation and communication performances demand further *** such,this paper presents a new modelling of light fixture distribution for a warehouse model to provide acceptable illumination and communication *** proposed model was evaluated based on various semi-angles at half power(SAAHP)and different height levels for several parameters,including received power,signal to noise ratio(SNR),and bit error rate(BER).The results revealed improvement in terms of received power and SNR with 30 Mbps data *** modulations were studied to improve the link quality,whereby better average BER values of 5.55×10^(−15) and 1.06×10^(−10) had been achieved with 4 PAM and 8 PPM,*** simulation outcomes are indeed viable for the practical warehouse model.

关键词： Visible light communication(VLC) industrial applications warehouse model light fixtures bit error rate(BER)

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An empirical intelligent water irrigation system using soft computing and IoT

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International Journal of Information Technology (Singapore) 2024年第6期16卷 3983-3989页

作者： Patel, Warish Sangeetha, Y. Gopagoni, Deepa Rani Mallik, D. M. Arvind Agrawal, Rakshal Mishra, Saket Sunil, M.P. Kolandaisamy, Raenu Department of Computer Science and Engineering Faculty of Engineering and Technology Parul University Gujarat India Department of Information Technology VR Siddhartha Engineering College Andhra Pradesh Vijayawada India Department of Computer Science and Engineering Vardhaman College of Engineering Hyderabad India PES Institute of Technology and Management Karnataka Shivamogga India Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Maharashtra Nagpur India Centre of Interdisciplinary Research in Business and Technology Chitkara Institute of Engineering and Technology Chitkara University Punjab Rajpura India Department of Electronics and Communication Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Karnataka Bengaluru India Institute of Computer Science and Digital Innovation UCSI University Kuala Lumpur Malaysia

Water loss from fruit and vegetable production is mostly caused by leakage in the transportation system and handling of land, as well as by using traditional processing techniques. In order to increase the wellness of plants, save power, and optimize consumption of water, information should be widely applied in designing intelligent irrigation systems, which is possible with the help of the Internet of Things (IoT). In the given paper, an IoT-based soft computing recommendation framework is proposed for performing irrigation in a smarter way. The system works in such a way that IoT devices are positioned in the field to gather information about crops and groundwater levels. The acquired data is then fed to a cloud repository, which makes use of soft computing techniques such as neural networks for analysing and providing effective recommendations to farmers on their smartphones. In this way, the framework is tuned and the farmers are also updated from time to time regarding judicious irrigation processes. Lastly, the performance of the proposed system is validated against traditional techniques by taking crop datasets into consideration. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Efficient water management Intelligent devices IoT Smart irrigation Soft computing

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Deployment of Polar Codes for Mission-Critical Machine-Type communication Over Wireless Networks

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computers, Materials & Continua 2022年第4期71卷 573-592页

作者： Najib Ahmed Mohammed Ali Mohammed Mansoor Rodina Binti Ahmad Saaidal Razalli Bin Azzuhri Department of Software Engineering Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala Lumpur Malaysia 2Department of Computer System&TechnologyFaculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia

Mission critical Machine-type communication(mcMTC),also referred to as Ultra-reliable Low Latency communication(URLLC),has become a research *** is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected *** the reduction in physical(PHY)layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability,the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper *** mcMTC has a significant technical impact on the design of all layers of the communication protocol *** this paper,an innovative bottom-up approach has been proposed for mcMTC applications through PHY layer targeted at improving the transmission reliability by implementing ultra-reliable channel coding scheme in the PHY layer of IEEE 802.11a standard bearing in mind short packet transmission *** achieve this aim,we analyzed and compared the channel coding performance of convolutional codes(CCs),low-density parity-check(LDPC)codes,and polar codes in wireless network on the condition of short data packet *** Viterbi decoding algorithm(VA),logarithmic belief propagation(Log-BP)algorithm,and cyclic redundancy check(CRC)successive cancellation list(SCL)(CRC-SCL)decoding algorithm were adopted to CC,LDPC codes,and polar codes,***,a new PHY layer for mcMTC has been *** reliability of the proposed approach has been validated by simulation in terms of Bit error rate(BER)and packet error rate(PER)***-to-noise ratio(SNR).The simulation results demonstrate that the reliability of IEEE 802.11a standard has been significantly improved to be at PER=10−5 or even better with the implementation of polar *** results also show that the general-purpose wireless net

关键词： Machine-type communication mission-critical applications MTC URLLC M2M wireless networks polar codes

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Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning

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Intelligent Automation & Soft Computing 2023年第5期36卷 1915-1930页

作者： Rab Nawaz Bashir Imran Sarwar Bajwa Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel ABahaddad Khalid Ali Almarhabi Department of Computer Science COMSATS University IslamabadVehari CampusPakistan Department of Computer Science and IT Islamia University BahawalpurPakistan Department of Software Engineering Superior University Lahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation *** the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)*** relationship between environmental conditions and ET rate is hard to be deﬁned by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)***-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity *** proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)*** validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm *** applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.

关键词： Leaching fraction saline soil evapotranspiration machine learning calibrated evapotranspiration artiﬁcial intelligence blaney criddle method

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Optimizing Optical Attocells Positioning of Indoor Visible Light communication system

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computers, Materials & Continua 2023年第2期74卷 3607-3625页

作者： Mohammed S.M.Gismalla Asrul I.Azmi Mohd R.Salim Farabi Iqbal Mohammad F.L.Abdullah Mosab Hamdan Muzaffar Hamzah Abu Sahmah M.Supa’at School of Electrical Engineering Faculty of EngineeringUniversiti Teknologi MalaysiaSkudai81310Malaysia Lightwave Communications Research Group(LCRG) Faculty of Electrical EngineeringUniversiti Teknologi Malaysia(UTM)SkudaiJohorMalaysia Department of Electronics and Electrical Engineering Faculty of EngineeringInternational University of AfricaKhartoum12223Sudan Department of Communication Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Parit RajaBatu Pahat86400JohorMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Department of Computer Science University of São PauloSão PauloBrazil

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond *** random movement of mobile terminals in the indoor environment is a challenge in the VLC *** model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)*** optimized optical attocells were examined and compared with previous *** novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 *** bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,*** optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,*** the results of the proposed model are optimal,it is suitable for standard office and room model applications.

关键词： Visible light communication(VLC) optical attocell received power signal-to-noise ratio(SNR) bit error rate(BER) coefficient of variation(CV)

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Empowering Human-Machine communication in Code Generation with NLP 5

Empowering Human-Machine Communication in Code Generation wi...

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5th IEEE International Conference on Recent Trends in computer science and Technology, ICRTCST 2024

作者： Aswal, Upendra Singh Rao, Pappala Mohan Supreeth, B.R. Manikandan, G. Srinivasan, R. Tiwari, Mohit Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Andhra University College Of Engineering AU College Of Engineering Computer Science and System Engineering AP Visakhapatnam530003 India Oxford Degree and PG College Sir. M. Visveshwaraiah Layout Department of Computer Science Ullal Bangalore India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Thandalam India St. Martins Engineering College Department of Computer Science and Engineering Telangana Secunderabad India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering A-4 Rohtak Road Paschim Vihar Delhi India

ISBN: (纸本)9798350351378

The symbiotic interaction between people and computers in the realm of software development is experiencing a fundamental transition, spurred by improvements in Natural Language Processing (NLP). This study investigates how natural language processing (NLP) is changing the software development process by facilitating better human-machine collaboration throughout the coding phase. Data collection, NLP model creation, and assessment are all part of the rigorous process used in our work, which yields important results. The possibility for improving code quality and efficiency while also democratizing code production is discussed in the context of a fictional situation. Ethical concerns are also highlighted, along with the need to minimize bias in NLP-driven code production. To the benefit of developers, organizations, and society at large, this study not only adds empirical insights but also imagines a future in which software development is more inclusive, efficient, and morally responsible. From improved natural language processing models to real-time feedback loops and multimodal techniques, the future of this transforming discipline promises to further influence the landscape of software development. © 2024 IEEE.

关键词： Software design

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Mobile-based Cloud Computing with Autonomous Assets Supply 4

Mobile-based Cloud Computing with Autonomous Assets Supply

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4th International Conference on Electronics and Sustainable communication systems, ICESC 2023

作者： Shadaksharappa, B. Maruthu Kannan, B. Yuvaraj, S. Maniraj, S.P. Sri Sairam College of Engineering Department of Computer Science and Engineering Karnataka Bengaluru India Sphoorthy Engineering College Nadergul Department of Computer Science and Engineering Telangana Hyderabad India Srm Institute of Science and Technology Kattankulathur Faculty of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350300093

The overwhelming rise in computing and networking skills makes Mobile platforms as predominant means of Internet access. Specific portable apps are unusable due to the inadequate computing capacities of mobile platforms. The constrained conne ctivity and reaction times involved in offloading data into multiple servers, such as a cloud data center, make permitting applications needing real-time information collection and processing on mobile stages are very challenging. The hybrid statics/mobile computing network is the latest supply system which has the heterogeneous ability for sensing, computing, and networking with static/mobile devices nearby. This robust computing network can allow creative mobile information and calculation-intensive applications, including omnipresent context-aware health and wellbeing checks of older adults, remote precipitation and flood risk evaluation, shared object detection and monitoring, and shared multimedia content searching and sharing. A detailed experimental study is provided to validate and demonstrate the advantages of the autonomous capability of the proposed system. © 2023 IEEE.

关键词： Cloud computing

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Collaborative Service Provisioning for UAV-Assisted Mobile Edge Computing

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Chinese Journal of Electronics 2024年第6期33卷 1504-1514页

作者： Yuben QU Zhenhua WEI Zhen QIN Tao WU Jinghao MA Haipeng DAI Chao DONG The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Colllege of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Xi'an Research Institute of High Technology Department of Information and Communication Noncommissioned Officer Academy of PAP National University of Defense Technology Department of Computer Science and Technology Nanjing University

Unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC), as a way of coping with delaysensitive and computing-intensive tasks, is considered to be a key technology to solving the challenges of terrestrial MEC networks. In this work, we study the problem of collaborative service provisioning(CSP) for UAV-assisted MEC. Specifically, taking into account the task latency and other resource constraints, this paper investigates how to minimize the total energy consumption of all terrestrial user equipments, by jointly optimizing computing resource allocation, task offloading, UAV trajectory, and service placement. The CSP problem is a non-convex mixed integer nonlinear programming problem, owing to the complex coupling of mixed integral variables and non-convexity of CSP. To address the CSP problem, this paper proposes an alternating optimization-based solution with the convergence guarantee as follows. We iteratively deal with the joint service placement and task offloading subproblem, and UAV movement trajectory subproblem, by branch and bound and successive convex approximation, respectively,while the closed form of the optimal computation resource allocation can be efficiently obtained. Extensive simulations validate the effectiveness of the proposed algorithm compared to three baselines.

关键词： Energy consumption Multi-access edge computing Collaboration Programming Autonomous aerial vehicles Minimization Trajectory Resource management Optimization Convergence

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