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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Sobhdel, Amirreza Razavi-Far, Roozbeh Palade, Vasile Urmia University Dept. of Electrical and Computer Engineering Iran University of New Brunswick Faculty of Computer Science Canada Centre for Computational Science Coventry University United Kingdom

ISBN: (纸本)9798350374889

In this paper, we study the performance of few-shot learning, specifically meta learning empowered few-shot relation networks, over supervised deep learning and conventional machine learning approaches in the problem of Sound Source Distance Estimation (SSDE). In previous research on deep supervised SSDE, low accuracies have often resulted from the mismatch between the training data (from known environments) and the test data (from unknown environments). By performing comparative experiments on a sufficient amount of data, we show that the few-shot relation network outperforms other competitors including eXtreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Convolutional Neural Network (CNN), and MultiLayer Perceptron (MLP). Hence it is possible to calibrate a microphone-equipped system, with a few labeled samples of audio recorded in a particular unknown environment to adjust and generalize our classifier to the possible input data and gain higher accuracies. © 2024 IEEE.

关键词： Self-supervised learning

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Effects of Mismatch on IC-Equipped Programmable Metasurfaces with Multibeam Functionality

Effects of Mismatch on IC-Equipped Programmable Metasurfaces...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Kossifos, Kypros M. Georgiou, Julius Antoniades, Marco A. University of Cyprus Dept. of Electrical & Computer Engineering Nicosia Cyprus Toronto Metropolitan University Dept. of Electrical Computer & Biomedical Engineering ON Canada

ISBN: (纸本)9781665442282

Integrated circuit (IC) technology can be incorporated in programmable metasurfaces (PMSFs) and reduce their cost and power consumption while increasing their electromagnetic manipulation capabilities. Such improvements can succour the incorporation of PMSFs as a common telecommunication technology. In order for this to be realised, the reproducibility and reliability of IC-equipped PMSFs need to be addressed. A study is presented on effects of IC mismatch on the performance of a PMSF with multibeam functionality. A mismatch of 10% to 40% of the nominal IC response is used and the effects on the far field are presented. © 2023 IEEE.

关键词： Timing circuits

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A Hybrid Method for the Detection and Plucking of Mature Coconut Using an Advanced Object Detection Technique 1

A Hybrid Method for the Detection and Plucking of Mature Coc...

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1st International Conference on Trends in engineering Systems and Technologies, ICTEST 2024

作者： Muhammed Ilyas, H. Elayidom, Sudheep School of Engineering Cusat Dept. of Computer Science Cochin India

ISBN: (纸本)9798350307795

Vision is a crucial aspect for both artificial intelligence and automated robots. In the case of an automated coconut harvesting machine, a computerized system linked to the machine plays a key role in real-time identification of ripe coconuts within the coconut tree crown. The project employs AI theory to craft an intelligent system. This system utilizes prior knowledge to predict the maturity of coconuts in the current image of the coconut tree crown. A computational board is then employed to compare the captured image with a dataset, enabling the identification of different coconut growth stages and pinpointing the mature coconuts in the current image capture. © 2024 IEEE.

关键词： Object detection

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COMPARING WSN PERFORMANCE: TRADITIONAL VS. SDN APPROACH

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: electrical engineering and computer science 2024年第4期86卷 81-94页

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Okumus, Ibrahim Taner Tapus, Nicolae Faculty of Automatic Control and Computer Science University of Science and Technology POLITEHNICA Bucharest Soran Technical college Erbil Polytechnic University Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey Dept. of Computer Science University of Science and Technology POLITEHNICA Bucharest Romania

The proliferation of Wireless Sensor Networks (WSN) in various applications has necessitated the exploration of network architectures that can ensure efficient, scalable, and reliable communication. This study presents a comparative performance evaluation of traditional networking paradigms and Software-Defined Networking (SDN)-based architectures within WSN. Utilizing the Floodlight SDN controller and Mininet-WiFi emulator, we conducted a series of experiments across three different network topologies, varying the number of hosts and access points. The performance metrics focused on are average latency, packet loss percentage, and throughput. The results demonstrate a considerable improvement in all measured parameters under the SDN-based environment compared to the traditional setup. Specifically, SDN environments consistently showcased lower latency, minimal packet loss, and higher throughput, with the most notable difference observed in smaller network configurations. The findings suggest that SDN, with its centralized control plane, can significantly enhance the performance of WSNs, particularly in scenarios demanding rapid scalability and dynamic traffic management. This study underscores the potential of SDN architectures in optimizing WSN operations and lays the groundwork for future research in this domain. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Floodlighting

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Lung Cancer Disease Prediction using Hybrid Subtractive Clustering Method 2

Lung Cancer Disease Prediction using Hybrid Subtractive Clus...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Paul, Banibrata Mir, Mahmood Hussain Murugan, Stalin Kurian, Asha Alliance University Dept. of Computer Science & Engineering Bangalore India

ISBN: (纸本)9798350360523

As of right now, lung cancer is the primary cause of cancer-related deaths worldwide for both men and women. One possible explanation for lung cancer's main cause is smoking. 86% to 96% of instances of lung cancer are thought to originate in the epithelial cells that line the larger and smaller airways (bronchi and bronchioles), despite the fact that lung cancer can grow in any section of the lung. The primary objective of this work is to identify lung cancer using the ANFIS approach based on subtractive clustering method. Using Kaggle, we have made use of the Lung Cancer dataset. The network is trained using data from 1000 lung cancer patients, ranging in age from 14 to 73. The proposed system uses 11 input attributes to assess the presence and absence of lung cancer during testing, and consistently achieves 100% accuracy for each clustering radii. © 2024 IEEE.

关键词： Diseases

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Advancing Pediatric Appendicitis Diagnosis: Harnessing CNN and Hybrid Models with Ultrasound Imaging

Advancing Pediatric Appendicitis Diagnosis: Harnessing CNN a...

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Kulkarni, Supritha Sharma, Sanchit Manavi, J. Vachana, U. Bhargavi, M.S. Bangalore Institute of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508685

Pediatric appendicitis, an acute inflammatory disease, arises from the obstruction of the appendix, often due to inflammation or a fecalith. This common abdominal emergency in children presents diagnostic challenges due to its varied clinical manifestations, which can lead to misdiagnosis or higher perforation rates stemming from atypical symptoms. This research investigates the use of deep learning, more especially Convolutional Neural Networks (CNNs), by utilizing ultrasonic imaging data, which is less expensive, non-invasive, and quicker than the other approaches now in use. Several variants are evaluated including a basic CNN and more advanced hybrid models such as CNN-Support Vector Regression, CNN-Transformer, and Hierarchical Deep CNN, to identify the most optimal model to significantly enhance diagnostic accuracy, for young patients facing this condition. The study's main goal is to develop a highly accurate and dependable diagnostic tool for evaluating the severity of pediatric appendicitis by differentiating between simple and complex cases and identifying whether surgery is required to inform treatment plans. Various challenges that need to be tackled are managing significant dataset imbalances, enhancing interpretability and transparency for real-world clinical settings, and ensuring the robustness and adaptability of all these models across various healthcare environments. © 2025 IEEE.

关键词： Pediatrics

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Handcrafted Feature Assisted Light-Weight Encoder Decoder Based Classifier for Yoga Posture Recognition 2

Handcrafted Feature Assisted Light-Weight Encoder Decoder Ba...

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2nd IEEE International Conference on Device Intelligence, Computing and Communication Technologies, DICCT 2024

作者： Sarma, Prasiddha Ibotombi Singh, S. Tezpur University Dept. of Computer Science and Engineering Tezpur India

ISBN: (纸本)9798350372847

The trend for the need for at-home workout regimens and the potential for technology to support the trend is rising as remote employment becomes more and more common. One such activity that has benefits like increased flexibility and stress alleviation is yoga. Presently, numerous self-guided yoga courses in the form of pictures and videos are available online. Consequently, there is an urgent requirement for a system that can recognize and evaluate the precision of yoga posture execution in these instructional materials. In the current scenario lightweight prediction models are very much essential because devices like smartphones, edge devices, and embedded systems that have limited processing power or battery life, lightweight models are the best option as they require less resources to train and operate. One particular approach of making the recognition system lightweight is the use of keypoint-based pose/action classifiers. In this paper, a lightweight classifier for yoga postures based on neural network architecture using MoveNet pose estimation technique is proposed. Our model is able to classify the yoga postures by learning the human joints information in a efficient manner. © 2024 IEEE.

关键词： Classification (of information)

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Optimizing Cloud Security in Dynamic Environments Through Adaptive Workload Management Algorithm

Optimizing Cloud Security in Dynamic Environments Through Ad...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Yadav, Monika Sharma, Garima The Northcap University Dept. of Computer Science and Engineering Haryana India

ISBN: (纸本)9798350375237

With the growing interest of researchers in the area of cloud computing, security emerges as a major area of concern. As the complexity of cloud environments grows and the dependency on cloud services deepens across various sectors, ensuring robust security measures is crucial. This study proposes an innovative approach to enhance cloud security through efficient workload scheduling strategies. Leveraging insights from existing studies on green cloud computing, clonal selection algorithms, and energy-efficient resource allocation, the research introduces a novel security-aware workload organizing algorithm. The proposed algorithm aims to optimize both energy consumption and security in cloud data centers. Through comprehensive simulations on the Cloud Sim platform, the results demonstrate the algorithm's efficiency in reducing energy consumption while fortifying security measures. Moreover, the present study contributes to the evolving field of cloud security, offering a promising avenue for shielding data in dynamic cloud environments. © 2024 IEEE.

关键词： Energy utilization

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Proposal for a Virtual Reality System to Practice Knife Handling in Cooking 13

Proposal for a Virtual Reality System to Practice Knife Hand...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Nakazato, Yukitoshi Kano, Toru Ibaraki Univercity Dept. Computer Science and Engineering Ibaraki Japan

ISBN: (纸本)9798350355079

Knife handling is one of the most important skills in cooking. However, it is difficult to practice the handling of a kitchen knife repeatedly owing to limitations in resources. To address this, we propose a highly realistic system using a haptic device and CT (Computed Tomography) data. This system allows users to practice knife handling in a virtual environment, providing force feedback that reproduces real-life situations. Our goal is to enhance the efficiency and effectiveness of cooking training by enabling unlimited practice without the constraints of ingredients. © 2024 IEEE.

关键词： Virtual environments

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Intelligent Trolley System: Revolutionizing Retail Shopping 18

Intelligent Trolley System: Revolutionizing Retail Shopping

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Patel, Urmi Aglodiya, Mohmmadali Paliwal, Manish Shastri, Aditya Sabale, Ketan Sot Pdeu Dept. of Computer Science and Engineering Gandhinagar India

ISBN: (纸本)9789380544519

A smart shopping trolley incorporates technology to improve the shopping experience by providing features such as automatic checkout, item scanning, tailored suggestions, and budget tracking, boosting efficiency and convenience while optimizing purchases. This paper presents a prototype for an intelligent trolley system that follows a human being and does automatic billing. Human followers leverage HC05 Bluetooth, HMC5883L Compass, and GPS Neo 6M. Automatic billing leverages RFID tags for the unique identification of the product. The absence of GPS sensors led to the adoption of a sonar sensor for human followers. The article unfolds innovative solutions and insights gained from navigating IoT complexities, costs, and environmental factors. The paper envisions a future where machine learning and AI optimize the shopping journey, contributing to the continuous evolution of the retail narrative. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Human Following Robot Obstacle Avoidance RFID Sensor Smart IoT System

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