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Exploiting Impact of Eavesdropping Attacks on Secrecy Performance in WPT-based Secure Multi-hop Transmission 14

Exploiting Impact of Eavesdropping Attacks on Secrecy Perfor...

引用

14th International Conference on Ubiquitous and Future Networks, ICUFN 2023

作者： Shim, Kyusung An, Beongku Hankyong National University School of Computer Engineering & Applied Mathematics Korea Republic of Hongik University Dept. of Software and Communications Engineering Korea Republic of

ISBN: (纸本)9798350335385

In this paper, we study the impact of various eaves-dropping attacks on the secrecy performance in wireless power transfer (WPT)-based secure multi-hop transmission. Since each node has a limited power supply, each node harvests energy from the power beacon before data transmission. After then, each node fully consumes the harvested energy for data transmission. Meanwhile, according to the nature of the wireless medium, eavesdroppers can overhear the confidential message at each hop. In order to exploit the relationship between network parameters and secrecy performance, we derive the closed-form expression for secrecy outage probability (SOP) with different eavesdropping attacks, respectively. From the numerical results, we show that the Monte-Carlo simulation and analysis results are tightly matched. Additionally, we evaluate and discuss the impact of the power beacon's transmit power, the number of eavesdroppers, and time switching ratio on the secrecy performance. © 2023 IEEE.

关键词： Monte Carlo methods

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SWIN and Vision Transformer-Driven Crack Detection in the Al Qattara Oasis, UAE: Towards Sustainable Infrastructure Management 11

SWIN and Vision Transformer-Driven Crack Detection in the Al...

引用

11th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2024

作者： Ali, Luqman Ambali Parambil, Medha Mohan Swavaf, Muhammed Alnajjar, Fady Aljassmi, Hamad De Man, Adriaan De Emirates Centre for Mobility Research United Arab Emirates University Dept. Computer Science and Software Engineering Al Ain United Arab Emirates United Arab Emirates University Dept. Computer Science and Software Engineering Al Ain United Arab Emirates Emirates Centre for Mobility Research Dept. Civil and Enviromental Engieering Engieering Al Ain United Arab Emirates United Arab Emirates University Dept. Tourism and Heritage Al Ain United Arab Emirates

ISBN: (纸本)9798350367300

Heritage sites are central to the cultural identity and historical narrative of a community. The Al Qattara Oasis, located in the United Arab Emirates (UAE), illustrates this function well. This study addresses the pressing need to preserve and maintain built heritage by employing modern technological solutions for infrastructure upkeep. Specifically, it focuses on crack detection, a critical aspect of ensuring the structural integrity of heritage buildings. Utilizing data collected from various structures across the UAE, obtained through handheld cameras, the effectiveness of Vision Transformers (ViTs) and Swin Transformers in identifying cracks within Al Qattara is assessed. The research thoroughly evaluates models, with particular attention to different input patch sizes. Through systematic experimentation and analysis over 100 epochs, ViT models with a patch size 16 exhibit significant promise in crack detection. Notably, the ViT-16 model achieves good performance metrics, including training and validation accuracies of 85% and (82%) respectively, and correctly classifies 791 out of 957 cracks and 772 out of 903 non-cracks. In contrast, Swin Transformers show lower validation accuracies (70-74%) and higher misclassification rates. The outcomes underscore the potential of ViT models in enhancing infrastructure maintenance efforts within heritage sites like Qattara Oasis. By combining advanced technology with a profound respect for historical preservation, this study aims to contribute to the sustainable conservation and protection of cultural heritage, ensuring that future generations can continue to appreciate the enduring legacy of sites such as Qattara Oasis. © 2024 IEEE.

关键词： Historic preservation

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A New Compensation Topology For Inductive Power Transfer (IPT) Systems 49

A New Compensation Topology For Inductive Power Transfer (IP...

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Huang, You-Chun Madawala, Udaya Baguley, Craig A. Hsieh, Yao-Ching National Sun Yat-sen University Dept. of Electrical Engineering Kaohsiung Taiwan University of Auckland Dept. of Electrical Computer and Software Engineering Auckland New Zealand Auckland University of Technology Dept. of Electrical and Electronic Engineering Auckland New Zealand

ISBN: (纸本)9798350331820

This paper presents a new IPT compensation topology that can be operated at two different frequencies to form either primary series and secondary parallel (S-P) or primary parallel and secondary parallel (P-P) compensation. Model are presented to demonstrate how this transformation between S-P and P-P compensations with dual frequency control. The simulated results of a 1 kW IPT system have verified that the proposed system can remain output power with phase-shift modulation (PSM) and allows for efficient power transfer despite large pad misalignments by operating at different compensation. © 2023 IEEE.

关键词： Energy transfer

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Automated Optical Inspection for Quality Control in PCBA assembly lines: a case study for Point of Sale Devices Production Lines 6

Automated Optical Inspection for Quality Control in PCBA ass...

引用

6th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Aras, Kerem Saif, Syed Saad Giuseppi, Alessandro Coskun, Vedat R&D Center Token Financial Technologies Istanbul Turkey Dept. of Computer Control and Management of Rome La Sapienza Rome Italy Dept. of Software Engineering Istanbul Atlas University Istanbul Turkey

ISBN: (纸本)9798350394634

This paper reports on the design and development of a customized Automated Optical Inspection (AOI) solution aimed at detecting defects in a production line related to the correct mounting of integrated circuits. Contrary to most solutions avail- able on the market, the developed system relies on deep learning to be able to perform detailed real-time visual inspections of components without the need to compare the captured photos with any reference images/golden sample. The proposed solution was designed to also provide good generalization capabilities, accommodating visual changes in the environment and in the structure of the component being produced. A custom testing machine was built in order to perform real-time inferences and validate the simulation results in a real-world setting. © 2024 IEEE.

关键词： Assembly

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Transformer-Based Human Action Recognition with Dynamic Feature Selection

Transformer-Based Human Action Recognition with Dynamic Feat...

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Canadian Conference on computer and Robot Vision, CRV

作者： Soufiane Lamghari Guillaume-Alexandre Bilodeau Nicolas Saunier Dept. of Computer and Software Engineering LITIV Polytechnique Montreal Montreal Canada Dept. of Civil Geological and Mining Eng. Polytechnique Montreal Montreal Canada

Human action recognition in videos is an important task of computer vision that aims to automatically recognize and classify human actions in video sequences. However, accurately recognizing human actions can be challenging due to the complexity and variability of human motion and appearance. In this paper, we propose ActiViT, a novel approach for human action recognition in videos based on a Transformer architecture. Unlike existing methods that rely on convolutional or recurrent layers, our model is entirely based on the Transformer encoder, enabling us to leverage valuable information in action image patches features. We demonstrate that by dynamically selecting key patches guided by specific human poses, our model learns informative features useful for distinguishing between different actions. Our experimental results on real-world datasets convincingly demonstrate the effectiveness of our model and the importance of selecting discriminative key poses for action recognition.

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Intrusion Detection System Based on Machine Learning Techniques: A Survey 2

Intrusion Detection System Based on Machine Learning Techniq...

引用

2nd International Conference on Advances in engineering Science and Technology, AEST 2022

作者： Sheet, Omar I. Ibrahim, Laheeb M. University of Mosul College of Computer Sciences & Math Software Engineering Dept. Iraq

ISBN: (纸本)9798350334906

The volume of network traffic data has become so big and complicated as a result of the development in Internet-based services that it is extremely difficult to process using typical data processing techniques. Due to the enormous and complicated nature of network traffic data, fast and effective cybersecurity intrusion detection is a highly difficult task. In order to detect hostile traffic as soon as feasible, a realistic cyber security intrusion detection system should be able to handle a huge volume of network traffic data as quickly as *** paper studies a classification-based intrusion detection algorithms based on Machine Learning for speedy and effective intrusion detection in huge network traffic, including Support Vector Machines (SVM), Random Forests(RF), Decision Trees(DT), Naïve Bayes (NB), Deep Neural Network (DNN), Extreme Gradient Boosting (XG Boost), Nondominated Sorting Genetic Algorithm (NSGA2), as well as Deep Belief Network (DBN) and artificial neural network(AI). It has been applied to ACTUAL TIME The KDD dataset, KDD Cup 99 dataset, NSL-KDD dataset, CICIDS-2017 dataset, CICIDS-2018 dataset, ISCX Dataset, CICAndMal2017 dataset and UNSW-NB15 to compare performance based on rating Intrusion detection systems which are assessed in terms of training time, prediction time, accuracy. © 2022 IEEE.

关键词： Intrusion detection

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An In-dept. Study on Handwritten Signature Authentication Using Unique Writer Traits 1

An In-Depth Study on Handwritten Signature Authentication Us...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Vamsikrishna, M. Murari, Haritha Manikandan, M. Mishra, Nilamadhab Raghavendra Gupta, T. Patel, Rohit Aditya University Dept. of Computer Applications Kakinada India Spark Infotech Inc Sr Software Engineer PhoenixAZ United States VeL Tech. R Dr.S Dept. of Computer Science and Engineering Tamilnadu India VIT Bhopal University Dept. of Computer Science and Engineering Sehore India HITM Telenagana Hyderabad India Calorx Teachers' University Dept of CSE Gujrat India

ISBN: (纸本)9798350356816

Handwriting verification, a subset of signature verification, involves using handwritten text to verify or authorize someone's identification. Although simple handwriting can serve as a signature, it is often modified to suit the signer's preferences. The uniqueness of each person's handwritten signature makes it essential for accurate distinction from others. This study presents a handwritten signature verification system using a writer-dependent approach. While signature verification is widely used for identity verification and security, it is susceptible to forgeries. The writer-dependent approach considers the unique characteristics of an individual's signature, training the system to recognize them and making forgery replication more challenging. An extensive review of the literature on signature verification systems, focusing on the writer-dependent approach, was conducted. A system was then developed and implemented based on this approach, utilizing a dataset of signatures from 12 writers. Results indicate that the writer-dependent approach outperforms other methods in terms of accuracy and robustness. The system demonstrated high precision and recall rates, underscoring its effectiveness in detecting both genuine and forged signatures. This study highlights the writer-dependent approach's efficacy in enhancing the accuracy and security of signature verification systems, with implications for developing more reliable and efficient identity verification systems in today's digital age. © 2024 IEEE.

关键词： Authentication

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Intelligent Model for Optimizing Gantt Chart in the Planning Stage 11

Intelligent Model for Optimizing Gantt Chart in the Planning...

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11th International Conference on Information Technology, ICIT 2023

作者： Bdair, Noor Alzyadat, Wael Alzubi, Shadi Alzaytoonh University of Jordan Faculty of Science and IT Dept of Software Engineering Jordan Alzaytoonh University of Jordan Faculty of Science and IT Dept. of of Computer Science Jordan

ISBN: (纸本)9798350320060

Scheduling tasks under resource constraints is essential for project success, and this research focuses on scheduling tasks efficiently to minimize completion time. To tackle this problem, two optimization techniques are employed: Linear programming (LP) and particle swarm optimization (PSO). PSO significantly reduces the duration, leading to a reduction in project duration. But the LP algorithm does not improve the project duration. Using suitable algorithms to maximize project efficiency and success is essential for successful project management. This research provides valuable information for project managers and decision makers, highlighting the importance of utilizing suitable algorithms to maximize project efficiency and success. © 2023 IEEE.

关键词： Linear programming

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A COMPARATIVE STUDY OF PRICE-DRIVEN PRODUCTION CONTROL METHODS USING A SAWMILL SIMULATOR

A COMPARATIVE STUDY OF PRICE-DRIVEN PRODUCTION CONTROL METHO...

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2024 Winter Simulation Conference, WSC 2024

作者： Duhem, Louis Benali, Maha Morin, Michael Gaudreault, Jonathan Dept. of Industrial Eng. Polytechnique Montréal MontréalQC Canada Dept. of Operations and Decision Systems Université Laval QuébecQC Canada Dept. of Computer Science and Software Eng. Université Laval QuébecQC Canada FORAC Research Consortium Université Laval QuébecQC Canada

ISBN: (纸本)9798331534202

In today’s dynamic markets, decision-making relies heavily on simulation models to evaluate different production control methods. Although price-driven production control methods have proven their effectiveness in exploiting price volatility, certain industries are still reluctant to adopt these methods in their operational decision-making. This research demonstrates the relevance of price-driven methods for the wood products industry. A sawmill simulator is used to illustrate this. Since the simulation of the sawmill production process is time-consuming, we propose a probabilistic sampling-based method to rationalize the dataset size. A comparative study shows that exploiting historical and recent price data increases sawmill revenues. © 2024 IEEE.

关键词： Saws

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Handcrafted and Deep features based Classification of Scoliosis 2

Handcrafted and Deep features based Classification of Scolio...

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2nd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2022

作者： Fatima, Joddat Mohsan, Mashood M. Qaisar, Muhammad Umair Hamza, Muhammad Tahir, Muhammad Zeshan Zaman, Ghazzal Bahria University Dept. of Computer Science Islamabad Pakistan National University of Sciences & Technology Dept. of Computer & Software Engineering Rawalpindi Pakistan

ISBN: (纸本)9781665498197

The Spinal cord acts as the central transmission line connecting the Brain with all other body organs. Vertebrae are 33 uneven bones stacked over one another that holds the whole skeleton structure. Scoliosis is the three-dimensional spinal deformity which commonly occurs during the growing age and erupts before puberty. It is further classified in two Shapes C and S. Our research work has two stages, in first stage we segment out the vertebral column using Mask-RCNN. The segmented column is used for features extraction and in stage two feature based classification is done for normal, C and S shape of scoliosis using AASCE2019 dataset. A comparative study on multiple image classification networks is also conducted and based on results EfficientNet-B4 is selected for formulation of hybrid feature set. The accuracy achieved using Random forest classifier, for handcrafted and deep features was up to 94.32% and 89.66%. Hybrid feature set formulated with combination of deep and handcrafted features attained accuracy up to 94.45%. © 2022 IEEE.

关键词： Decision trees

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