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End-To-End Encryption Enabled Lightweight Mutual Authentication Scheme for Resource Constrained IoT Network

computers, Materials & Continua 2025年第2期82卷 3223-3249页

作者： Shafi Ullah Haidawati Muhammad Nasir Kushsairy Kadir Akbar Khan Ahsanullah Memon Shanila Azhar Ilyas Khan Muhammad Ashraf Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Computer Engineering Section Malaysian Institute of Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Electrical Engineering Section Universiti Kuala LumpurBritish Malaysian InstituteSalengor53100Malaysia Electrical Engineering Department Mehran UniversityKhairpur-Mirs76062Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.

关键词： Mutual authentication lightweight end-to-end encryption elliptic curve cryptography industrial internet of things curve25519 machine-to-machine communication

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Development of Mechatronic Solution on Hot-Stamping Heads 33rd

Development of Mechatronic Solution on Hot-Stamping Heads

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33rd International Conference on Organization and Technology of Maintenance, OTO 2024

作者： Ostojić, Ivan Velimirović, Mirjana Kovačević, Nada Ratković Dihovicni, Djordje Computer-Mechanical Engineering Section Department of Electrical and Computer Engineering Academy of Technical Applied Studies Belgrade Belgrade Serbia Urban Technics Valjevo Serbia

ISBN: (纸本)9783031805967

The general goal of the research is to reduce loss of productivity, failure and downtime and the percentage of waste in production in the company, which is already committed to and successful in applying standards, raising the quality of service, as well as occupational safety and environmental protection. In this scientific paper a mechatronic subsystem is designed and implemented, as an addition to the hot-stamping production line, which would monitor whether there are present (and whether there are in quantities enough of) each of the three thermoplastic, metallized strips, which line the product - profiled lath. When it is detected and recognized that the tape will soon be used up, the sub-system automatically signals this with turning off heating of the slat and activating a sound alarm, attracting attention of the human operator. The heater switches off automatically if the strip loss has occurred (event driven system), in order to prevent deformation of the slat profile. The subsystem includes automatic monitoring of the remaining amount of tape, alarm notification in case of imminent disappearance of the tape, with the heater turned off and alarming the operator. The human operator then has enough time to replace the tape (approximately five to ten minutes, depending on the product). The subsystem described above is designed, built, implemented, tested and put in operation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Quality of service

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ENERGY AND COST BENEFITS OF ADVANCED LIGHTING TECHNOLOGY APPLICATIONS IN TRAFFIC LIGHT SYSTEMS 14

ENERGY AND COST BENEFITS OF ADVANCED LIGHTING TECHNOLOGY APP...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Polycarpou, Alexis Georgiou, Marios S. Department of Electrical Computer Engineering and Informatics Frederick University Nicosia Cyprus Electromechanical Section Nicosia Municipality Nicosia Cyprus

ISBN: (纸本)9781837242689

Following a pilot project, which concluded in 2016, the replacement of old energy consuming Traffic Light Systems (TLS) of Nicosia Municipality were the subject of an investigation with regards to the energy saving potential and most importantly the payback period of the investment, through presumptions. This paper presents the results obtained of the new efficient technology implementation, with regards to the energy saving that materialised in the Nicosia Municipality. Investigation is presented in an attempt to determine whether the proposed solution and calculated capital employed had the expected energy usage reduction, return on investment, and payback period. The estimated cost benefit of the installed systems compared to the actual benefits varies significantly, after factors such as maintenance and electricity costs are considered. © The Institution of engineering & Technology 2024.

关键词： Street lighting

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RP-SWSGD: Design of sliding window stochastic gradient descent method with user’s ratings pattern for recommender systems

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Multimedia Tools and Applications 2024年第14期83卷 41083-41120页

作者： Khan, Zeshan Aslam Raja, Hafiz Anis Chaudhary, Naveed Ishtiaq Iqbal, Sumbal Mehmood, Khizer Raja, Muhammad Asif Zahoor Department of Electrical and Computer Engineering International Islamic University Islamabad Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan

To offer relevant and useful recommendations, the crucial role of recommender systems in e-commerce industry is to predict the users’ concern for various items by estimating items’ attributes and users’ preferences. The reliability of a recommender system is usually assessed through accuracy and speed of relevant recommendations for a variety of items. The matrix factorization-based stochastic gradient descent (SGD) methods proposed by researchers lack memory needed to capture the ratings history hidden in the previous iterations. Recently, sliding window-based SGD strategies designed for Recommender systems and Hammerstein nonlinear systems gained attention due to the improved performance in terms of convergence speed and estimated accuracy. The memory impact with regard to the historical information enhances the performance of sliding window-based SGD techniques. However, sliding window-based methods are deficient in capturing the ratings history based on the users’ rating patterns. Hence utilizing the same window length for the set of observed ratings rated by users. Therefore, we propose an improved sliding window-based SGD strategy to acquire historical information of the ratings with respect to a user’s rating patterns for efficient matrix factorization of recommender systems. The proposed strategy performs significantly by accomplishing fast convergence speed and accuracy for window sizes greater than 1. The accuracy of the suggested technique is verified for two benchmark datasets such as ML-100 K and Film-Trust. However, the authenticity of the proposed method as compared to the standard counterpart (window size = 1) is confirmed through Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The average improvements achieved by the proposed strategy in terms of RMSE and MAE over the baseline for ML-100 K dataset are 0.726% and 2.245% respectively. Whereas the proposed method accomplishes considerable average improvement of 7.89% and 9.41% for RMSE an

关键词： Recommender systems

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Distributed Big Data Clustering using MapReduce-based Fuzzy C-Medoids

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Journal of The Institution of Engineers (India): Series B 2022年第1期103卷 73-82页

作者： Sardar, Tanvir H. Ansari, Zahid School of Computer Science & Engineering Jain University Bangalore India Electrical Engineering Section University Polytechnic Aligarh Muslim University Aligarh India

Efficient big data clustering is a requirement for massive data generating in this digitalized connected world. The traditional clustering algorithms do not scale over massively sized and highly unstructured big data. Thus, to obtain efficiency in clustering big data new architecture and programming paradigm is required. In this work, a novel MapReduce-based Fuzzy C-Medoids clustering algorithm is designed and experimented with to cluster big data repository of documents datasets. The performance of the proposed algorithm is experimentally evaluated for different-sized Hadoop cluster sizes and different-sized document datasets. The algorithm is found to be scalable and efficient in performing clustering jobs. © 2021, The Institution of Engineers (India).

关键词： MapReduce

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MapReduce-based Fuzzy C-means Algorithm for Distributed Document Clustering

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Journal of The Institution of Engineers (India): Series B 2022年第1期103卷 131-142页

The clustering of big data is a challenging task. The traditional clustering algorithms are inefficient for clustering big data. The recent researches in this field suggest that the traditional clustering algorithms needed to be redesigned for the modern architecture of computing. This wok has proposed a novel MapReduce-based fuzzy C-means algorithm for big document data clustering. The algorithm is extensively experimented with using different sizes of document datasets and executed over the Hadoop cluster of different sizes. The proposed algorithm’s efficiency is compared against serial traditional fuzzy C-means and MapReduce-based K-means algorithms. The proposed design of the fuzzy C-means algorithm is scaled well with the Hadoop platform and documents big datasets and resulted in a performance gain. © 2021, The Institution of Engineers (India).

关键词： MapReduce

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A Deep Learning Approach for Crowd Counting in Highly Congested Scene

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computers, Materials & Continua 2022年第12期73卷 5825-5844页

作者： Akbar Khan Kushsairy Abdul Kadir Jawad Ali Shah Waleed Albattah Muhammad Saeed Haidawati Nasir Megat Norulazmi Megat Mohamed Noor Muhammad Haris Kaka Khel Electrical Section Universiti Kuala Lumpur British Malaysian InstituteSelangor53100Malaysia Department of Electrical Engineering International Islamic UniversityIslamabad44000Pakistan Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Electrical Engineering National University of Computer and Emerging SciencesIslamabad44000Pakistan Computer Engineering Technology Section Universiti Kuala Lumpur Malaysian Institute of Information TechnologyKuala Lumpur50250Malaysia

With the rapid progress of deep convolutional neural networks,several applications of crowd counting have been proposed and explored in the *** congested scene monitoring,a variety of crowd density estimating approaches has been *** understanding of highly congested scenes for crowd counting during Muslim gatherings of Hajj and Umrah is a challenging task,as a large number of individuals stand nearby and,it is hard for detection techniques to recognize them,as the crowd can vary from low density to high *** deal with such highly congested scenes,we have proposed the Congested Scene Crowd Counting Network(CSCC-Net)using VGG-16 as a core network with its first ten layers due to its strong and robust transfer learning rate.A hole dilated convolutional neural network is used at the back end to widen the relevant field to extract a large range of information from the image without losing its original *** dilated convolution neural network is mainly chosen to expand the kernel size without changing other ***,several loss functions have been applied to strengthen the evaluation accuracy of the ***,the entire experiments have been evaluated using prominent data sets namely,ShanghaiTech parts A,B,UCF_CC_50,and UCF_*** model has achieved remarkable results i.e.,68.0 and 9.0 MAE on ShanghaiTech parts A,B,199.1 MAE on UCF_CC_50,and 99.8 on UCF_QNRF data sets respectively.

关键词： Deep learning congested scene crowd counting fully convolutional neural network dilated convolution

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COVICT: an IoT based architecture for COVID-19 detection and contact tracing

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Journal of Ambient Intelligence and Humanized Computing 2023年第6期14卷 7381-7398页

作者： Wahid, Mirza Anas Bukhari, Syed Hashim Raza Daud, Ahmad Awan, Saeed Ehsan Raja, Muhammad Asif Zahoor Department of Electrical and Computer Engineering COMSATS University Islamabad Attock Campus Islamabad Pakistan Department of Electrical and Computer Engineering Air University Islamabad Islamabad Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 Uni-versity Road Section 3 Douliou ROC Yunlin64002 Taiwan

The world we live in has been taken quite surprisingly by the outbreak of a novel virus namely SARS-CoV-2. COVID-19 i.e. the disease associated with the virus, has not only shaken the world economy due to enforced lockdown but has also saturated the public health care systems of even most advanced countries due to its exponential spread. The fight against COVID-19 pandemic will continue until majority of world’s population get vaccinated or herd immunity is achieved. Many researchers have exploited the Artificial intelligence (AI) knacks based IoT architecture for early detection and monitoring of potential COVID-19 cases to control the transmission of the virus. However, the main cause of the spread is that people infected with COVID-19 do not show any symptoms and are asymptomatic but can still transmit virus to the masses. Researcher have introduced contact tracing applications to automatically detect contacts that can be infected by the index case. However, these fully automated contact tracing apps have not been accepted due to issues like privacy and cross-app compatibility. In the current study, an IoT based COVID-19 detection and monitoring system with semi-automated and improved contact tracing capability namely COVICT has been presented with application of real-time data of symptoms collected from individuals and contact tracing. The deployment of COVICT, the prediction of infected persons can be made more effective and contaminated areas can be identified to mitigate the further propagation of the virus by imposing Smart Lockdown. The proposed IoT based architecture can be quite helpful for regulatory authorities for policy making to fight COVID-19. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： COVID-19

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Angle of Arrival Estimation Using SRS in 5G NR Uplink Scenarios

Angle of Arrival Estimation Using SRS in 5G NR Uplink Scenar...

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2024 Work-in-Progress in Hardware and Software for Location Computation, WIPHAL 2024

作者： Spanos, Thodoris Fabra, Fran López-Salcedo, José A. Seco-Granados, Gonzalo Kanistras, Nikos Lapin, Ivan Paliouras, Vassilis Dept. of Electrical and Computer Engineering University of Patras Greece Loctio Greece Spain Radio Navigation Systems and Techniques Section European Space Agency Netherlands

This paper presents a comprehensive exploration of Angle of Arrival (AoA) estimation techniques in 5G environments, using the Sounding Reference Signal (SRS) in Uplink scenarios both in simulations and with actual measurements. Leveraging 5G capabilities, we investigate AoA algorithms for single-base station positioning. The study includes simulations and practical tests on a developed dedicated testbed featuring a base station equipped with a three-element Uniform Linear Array (ULA), considering Line of Sight conditions in an open environment. The testbed, employing Ettus E312 as the transmitter and Ettus N310 as the receiver, details waveform structures and reception processes. Additionally, our study examines the performance of Angle of Arrival (AoA) estimation algorithms, such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariant Techniques (ESPRIT), and Joint Angle and Delay Estimation (JADE) ESPRIT. A MATLAB ray tracing propagation model of the environment where the measurements are conducted, has been constructed. Simulation results using this model are presented, along with the actual measurements. The obtained results affirm the effectiveness of our implementation. © 2024 Copyright for this paper by its authors.

关键词： Multiple signal classification

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Achieving Room-Temperature ppb-Level H2S Detection in a Au-SnO2 Sensor with Low Voltage Enhancement Effect

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ACS Sensors 2024年第9期9卷 4568-4577页

作者： Deb, Moumita Lu, Chia-Jung Zan, Hsiao-Wen Department of Photonics College of Electrical and Computer Engineering National Yang Ming Chiao Tung University 1001 Ta Hsueh Rd Hsinchu300 Taiwan Department of Photonics College of Electrical and Computer Engineering National Chiao Tung University 1001 Ta Hsueh Rd Hsinchu300 Taiwan Department of Chemistry National Taiwan Normal University 162 Heping East Rd. Section 1 Taipei11677 Taiwan

Although semiconductor metal oxide-based sensors are promising for gas sensing, low-power and room temperature operation (24 ± 1 °C) remains desirable for practical applications particularly considering the request of energy saving or net zero emission. In this study, we demonstrate a Au/SnO2-based ultrasensitive H2S gas sensor with a limit of detection (LOD) of 2 ppb, operating at very low voltages (0.05 to 0.5 V) at room temperature. The Au/SnO2-based sensor showed approximately 7 times higher response (the ratio of change in the current to initial current) of ∼270% and 4 times faster recovery (126 s) compared to the pure SnO2-based sensor when exposed to 500 ppb H2S gas concentration at 0.5 V operating voltage at relative humidity (RH) 17.5 ± 2.5%. The enhancement can be attributed to the catalytic characteristics of AuNPs, increasing the number of adsorbed oxygen species on sensing material surfaces. Additionally, AuNPs aid in forming flower-petal-like Au/SnO2 nanostructures, offering a larger surface area and more active sites for H2S sensing. Moreover, at low voltage (2 interface may further enhance the absorption of polar oxygen molecules and hence promote the reaction between H2S and oxygen species. This low-power, ultrasensitive H2S sensor outperforms high-powered alternatives, making it ideal for environmental, food safety, and healthcare applications. © 2024 The Authors. Published by American Chemical Society.

关键词： Room temperature

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