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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Veeranan, Arunprasad Amalraj, J.Leo Kandavalli, Sumanth Ratna. Bandili, Sunil Kumar Rajendiran, M. Meenakshi, S. Theni Kammavar Sangam College of Technology Department of Mechanical Engineering Tamilnadu India RMK College of Engineering and Technology Science and Humanities Tamilnadu India New York University Tandon School of Engineering Department of Mechanical Engineering New York United States Saint Louis University School for Professional Studies Department of Computer and Information Sciences St. LouisMO63103 United States Panimalar Engineering College Department Computer Science and Engineering Tamilnadu Chennai India Tamilnadu Kavarapettai India

ISBN: (纸本)9798350370249

This paper presents a novel methodology that integrates YOLOv3, a cutting-edge object identification model, with thermal analysis approaches to examine and evaluate the structural integrity of welded areas. The technology being presented utilizes the sophisticated object detection capabilities of YOLOv3 to reliably find and track specific regions of interest inside a welded structure. By incorporating this object detection model into thermal analysis tools, it becomes possible to see and study the temporal temperature distribution and thermal characteristics of the discovered locations. The study entails the collection of thermal data through the utilization of sophisticated sensors and thermal imaging technologies. This approach aims to acquire a thorough comprehension of the distribution and dissipation of heat inside the welded area under different operational circumstances. This methodology enables the continuous monitoring of operations in real-Time, enabling the identification of possible concerns such as excessive heat, concentrated stress, or material distortions. These factors have the potential to undermine the integrity and security of welded structures. The findings of this study make a valuable contribution towards improving the quality control and maintenance practices of welded components. © 2024 IEEE.

关键词： Thermal modeling

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Metaheuristic with Deep Learning Enabled Biomedical Bone Age Assessment and Classification Model

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computers, Materials & Continua 2022年第12期73卷 5473-5489页

作者： Mesfer Al Duhayyim Areej A.Malibari Marwa Obayya Mohamed K.Nour Ahmed S.Salama Mohamed I.Eldesouki Abu Sarwar Zamani Mohammed Rizwanullah Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The skeletal bone age assessment(BAA)was extremely implemented in development prediction and auxiliary analysis of medicinal issues.X-ray images of hands were detected from the estimation of bone age,whereas the ossification centers of epiphysis and carpal bones are important *** typical skeletal BAA approaches remove these regions for predicting the bone age,however,few of them attain suitable efficacy or *** BAA techniques with deep learning(DL)methods are reached the leading efficiency on manual and typical ***,this study introduces an intellectual skeletal bone age assessment and classification with the use of metaheuristic with deep learning(ISBAAC-MDL)*** presented ISBAAC-MDL technique majorly focuses on the identification of bone age prediction and classification *** attain this,the presented ISBAAC-MDL model derives a mask Region-related Convolutional Neural Network(Mask-RCNN)with MobileNet as baseline model to extract *** by,the whale optimization algorithm(WOA)is implemented for hyperparameter tuning of the MobileNet *** last,Deep Feed-Forward Module(DFFM)based age prediction and Radial Basis Function Neural Network(RBFNN)based stage classification approach is *** experimental evaluation of the ISBAAC-MDL model is tested using benchmark dataset and the outcomes are assessed over distinct *** experimental outcomes reported the better performances of the ISBAACMDL model over recent approaches with maximum accuracy of 0.9920.

关键词： Biomedical images bone age assessment age prediction computer vision deep learning image classification

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Unlocking the Potential of Mobile Computing for Infusing Computational Thinking Using Social Cognitive Approach in Higher Education Institutes 1

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International Conference on Data Analytics and Management, ICDAM 2023

作者： Al Yakin, Ahmad Obaid, Ahmed J. Muthmainnah Shnawa, Ammar H. Haroon, Noor Hanoon Teacher Training and Education Faculty Universitas Al Asyariah Mandar Sulawesi Barat Indonesia Polewali Mandar Indonesia Faculty of Computer Science and Mathematics University of Kufa Kufa Iraq National University of Science and Technology Thi-Qar Iraq Department of Computer Technical Engineering Technical Engineering College Al-Ayen University Thi-Qar Iraq

ISBN: (数字)9789819965472

ISBN: (纸本)9789819965465

In the current era of digital technology, computational thinking has become a crucial skill for understanding and analysing the informatics concepts behind every digital occurrence. While research has looked at the effectiveness of technology in education, limited studies have examined the potential of social cognitive learning with a mobile computing approach in developing computational thinking skills among students. This study aimed to analyse students’ perceptions of social cognitive learning using mobile computing to improve their computational skills. Using quantitative methods and purposive sampling, 135 students from Indonesia and the Philippines who were enrolled in social science subjects, using mobile computing with social science concepts, and interested in participating were surveyed. The study found that most students believed that social cognitive learning using mobile computing could significantly enhance their computational thinking skills. Implications were drawn from the study, such as the need for lecturers to have a thorough understanding of technology, various learning activities, and mobile computing apps to improve students’ computational skills and foster a future-oriented mindset. The appropriate social cognitive teaching stages and class design were also suggested as effective ways of developing computational thinking skills. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Students

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Advanced Road Sign Detection Techniques: Leveraging Harris Corner Detector for Robust Recognition 4

Advanced Road Sign Detection Techniques: Leveraging Harris C...

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4th International Conference on Soft Computing for Security Applications, ICSCSA 2024

作者： Mary Jenifer, A. Balamanigandan, R. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai602105 India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331515720

An automatic system for detection of road signs plays a crucial role in determining edges, obstacles, and signs of the road. Understandably, drivers might not always pay enough attention to signs. The preprocessing and feature extraction of road signs are done to carry out this process. The feature extraction applies the option of Harris detector, which is commonly used for corners detection. The detected signs are then matched against a database by using the special similarity measure used for the identification of these signs and enable an improvement in the levels of safety on roads. © 2024 IEEE.

关键词： MATLAB

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A Comprehensive Evaluaion of Solar Powered Electric Vehicle Charging Station Design Using Internet of Things 1

A Comprehensive Evaluaion of Solar Powered Electric Vehicle ...

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1st International Conference on Electronics, Communication and Signal Processing, ICECSP 2024

作者： Chitra, K. Gnanasekar, A. Ravi, C.N. Jaisudha, J. Ramya, R. Jithendar, P. CMR Institute of Technology Department of Electrical and Electronics Engineering Karnataka Bengaluru India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India CMR Engineering College Department of Computer Science and Engineering Hyderabad Medchal India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Nano Electronics Materials and Sensors Tamil Nadu Chennai India MLR Institute of Technology Department of Electrical and Electronics Engineering Hyderabad India

ISBN: (纸本)9798350364590

More than 1.3 million electric vehicles have been installed throughout the globe, and public charging networks for these vehicles are becoming increasingly common. It has been an area of interest to establish a plan for prioritizing the charging of electric vehicles (EVs) from a single network. This is particularly important in situations when the power source is restricted, such as with renewable energy, and for economic reasons (a higher price per KWh for quicker charging). When used in conjunction with electric vehicle (EV) charging, solar energy significantly decreases our reliance on fossil fuels. An electric car solar charger is created and constructed inside this system. In order to maximize the output from the solar panels, a dc-dc boost converter is used to transfer the voltage from the panels to the station's batteries. Maximum Power Point Tracking (MPPT) is also included. Power the charging station with energy from the solar panels so that the vehicle's rechargeable battery may be charged. The charging station's status can be monitored at any time via the Internet of Things. We have created a solar-powered charging station to provide simple accessibility. Solar power is both a sustainable and accessible renewable energy source. Arduino controller for light-dependent resistor (LDR) light intensity monitoring, solar cell energy observation, battery charging, and cloud storage. The core idea behind the article is the IoT Solar Charging Station (IoTSCS), and it is tested by comparing it to the Classical Solar Charging Station (CSCS), a more traditional scheme, in order to see how well the new scheme works. © 2024 IEEE.

关键词： Charging stations

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Compact Distance Oracles with Large Sensitivity and Low Stretch 1

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18th International Symposium on Algorithms and Data Structures, WADS 2023

作者： Bilò, Davide Choudhary, Keerti Cohen, Sarel Friedrich, Tobias Krogmann, Simon Schirneck, Martin Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Department of Computer Science and Engineering Indian Institute of Technology Delhi Delhi India School of Computer Science The Academic College of Tel Aviv-Yaffo Tel Aviv-Yafo Israel Hasso Plattner Institute University of Potsdam Potsdam Germany Faculty of Computer Science University of Vienna Vienna Austria

ISBN: (数字)9783031389061

ISBN: (纸本)9783031389054

An f-edge fault-tolerant distance sensitive oracle (f-DSO) with stretch σ⩾ 1 is a data structure that preprocesses an input graph G. When queried with the triple (s, t, F), where s, t∈ V and F⊆ E contains at most f edges of G, the oracle returns an estimate d^ G-F(s, t) of the distance dG-F(s, t) between s and t in the graph G- F such that dG-F(s, t) ⩽ d^ G-F(s, t) ⩽ σ· dG-F(s, t). For any positive integer k⩾ 2 and any 0 1+1/k) under the Erdős girth conjecture. Bilò et al. [STOC 2023] gave a solution with stretch 3 + Ε, query time O(nα) but space O(n2-αf+1), approaching the quadratic barrier for large sensitivity. In the realm of subquadratic space, our f-DSOs are the first ones that guarantee, at the same time, large sensitivity, low stretch, and non-trivial query time. To obtain our results, we use the approximate distance oracles of Thorup and Zwick [JACM 2005], and the derandomization of the f-DSO of Weimann and Yuster [TALG 2013] that was recently given by Karthik and Parter [SODA 2021]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Data structures

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Visual Identification of Oysters Using Machine Learning

Visual Identification of Oysters Using Machine Learning

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Essandoh, Joshua Straus, Michael Vukov, Nikolai Jin, Yuanwei Lu, Enyue Virginia Tech Department of Computer Science BlacksburgVA United States Columbia University School of Engineering and Applied Sciences New YorkNY United States Salisbury University Department of Mathematical Sciences SalisburyMD United States University of Maryland Eastern Shore Department of Engineering and Aviation Sciences Princess AnneMD United States Salisbury University Department of Computer Science SalisburyMD United States

ISBN: (纸本)9798350362480

Agricultural technology has evolved significantly since the 1800s. However, with respect to monitoring and farming of aquaculture such as oysters, industry is still stuck in the past. This project aims to modernize oyster monitoring and identification with machine learning. We developed a program capable of accurately identifying and classifying oysters in three states. They include closed, meaning they are healthy, or open for long periods of time, indicating mortality, and indeterminate. We also increased the scope of existing software with a website for real-time identification that is accessible to the public. In the process, we added support for video annotation, which was previously difficult to perform for those with no prior coding experience.1 © 2024 IEEE.

关键词： Adversarial machine learning

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Influence of Geometry Effects on Thermo-Mechanical Reliability of Aluminum Bond Wires in Discrete SiC MOSFETs 25

Influence of Geometry Effects on Thermo-Mechanical Reliabili...

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25th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems, EuroSimE 2024

作者： Kilian, Borja Maniar, Youssef Gleichauf, Jonas Wittler, Olaf Schneider-Ramelow, Martin Robert Bosch GmbH Corporate Sector Research and Advance Engineering Renningen Germany Fraunhofer IZM Department Environmental and Reliability Engineering Berlin Germany Technical University Berlin Faculty IV-Electrical Engineering and Computer Science Berlin Germany

ISBN: (纸本)9798350393637

Bond wire reliability remains as one of the major challenges in power electronics as device miniaturization progresses and demands on performance increase. Physics-of-failure models are commonly formulated to determine the lifetime of wire bonding interconnects. Such approach relies on damage metrics derived from finite element models, often based on simplified geometries and modeling *** paper addresses the influence of various bond wire geometry features on the thermo-mechanical reliability of PCB-mounted discrete SiC power devices. For this purpose, the bond wire geometry is characterized and the component is subjected to active power cycling until failure occurs due to bond wire lift-off. Finite element models are solved using a two-stage simulation approach: First, an upstream wire bonding simulation is performed to obtain a realistic bond foot geometry, and then the active power cycling tests are simulated. A physics-of-failure lifetime model is calibrated using damage quantities derived from the simulation results. Finally, geometry variations of the bond foot and different bond wire positions and rotations are evaluated to determine their significance for the thermo-mechanical reliability of thick Al bond wires. © 2024 IEEE.

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Deep learning-based few-shot person re-identification from top-view RGB and depth images

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Neural Computing and Applications 2024年第31期36卷 19365-19382页

作者： Abed, Almustafa Akrout, Belhassen Amous, Ikram Miracl Laboratory Enet’com University of Sfax National School of Electronics and Telecommunications of Sfax Road Tunis City El Ons Sfax3018 Tunisia Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia Sfax University Sfax3021 Tunisia

Person re-identification (re-id) attempts to match a person from the images of different time steps. Existing deep learning approaches either use appearance or geometry features for re-id which does not provide the required robustness because of higher intra-class similarity. Existing supervised re-id approaches utilize Convolutional Neural Networks (CNNs) and identity-labeled images to train, where the person images are taken by the sensors from a horizontal view. The horizontal view exposes the privacy of the people because of their facial appearance in the image. Moreover, person re-id includes new unseen people;however, CNN does not have the ability to identify the new unseen people because of a lack of continual learning. Privacy-preserved computer vision-assisted person re-id systems can benefit from visual appearance and geometry features extracted from top-view RGB and depth input. This paper presents the privacy-preserved person top-view re-id few-shot network which uses the appearance and geometry features. The EfficientNet is used for appearance-based features from RGB input, while PointNet is used to extract the geometry features from the point cloud which is made from the RGB-D image registration. Concatenated features from EfficientNet and PointNet are fed to the two-layer Bi-LSTM network for person identification. Finally, the whole network is converted into a few-shot network to achieve continual learning by removing the output layer and joining the similarity measurement unit. This approach is based on CNN and fine-tunes a TVPR/2 dataset acquired by using a top-view arrangement that is publicly available. The experimental results on TVPR/2 and GODPR datasets show that the proposed re-id network outperforms other state-of-the-art networks. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Retail stores

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An Assessment of the Security Benefits of Secure Shell (SSH) in Wireless Networks 3

An Assessment of the Security Benefits of Secure Shell (SSH)...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Preetha, M. Dhabliya, Dharmesh Lone, Zeeshan Ahmad Pandey, Sakshi Acharjya, Kalyan Gowrishankar, J. Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science Engineering Faculty of Engineering and Technology Karnataka Ramnagar India

ISBN: (纸本)9798350319125

Comfortable Shell (SSH) is a community protocol that provides relaxed communique over an unsecured community, such as the internet. This protocol is generally used for far flung login, file switch, and remote command execution, making it a vital device for managing and securing networks. Wi-Fi networks, which rely upon radio frequency indicators for verbal exchange, are prone to various safety threats such as eavesdropping, spoofing, and man-in-themiddle assaults. This makes using relaxed protocols like SSH critical for protective sensitive statistics and keeping the integrity of Wi-Fi networks. This technical assessment evaluates the safety advantages of utilizing SSH in wireless networks. First of all, SSH makes use of strong encryption algorithms consisting of AES and RSA to encrypt the whole communique session, ensuring that records is transmitted securely between devices. This prevents attackers from intercepting and reading touchy records exchanged among gadgets. Secondly, SSH makes use of a public-key infrastructure for authentication, that's more at ease than conventional password-based totally authentication. This is because the private key, which is used for authentication, is not transmitted all through the login system, making it greater tough for attackers to advantage get entry to the network. © 2023 IEEE.

关键词： Authentication

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