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共 2526 条记录，以下是181-190 订阅

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Preliminary Hyperspectral Characterization of Tissue-Mimicking Breast Phantoms

Preliminary Hyperspectral Characterization of Tissue-Mimicki...

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IEEE MTT-S International Microwave Bio Conference ((IMBIOC)

作者： Simona Di Meo Emanuele Torti Elisa Marenzi Roberto Gandolfi Marco Pasian Francesco Leporati Dept. of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9798350351057

ISBN: (纸本)9798350351064

In this paper, a preliminary hyperspectral characterization study of tissue-mimicking oil-in-gelatin phantoms is presented. The phantoms tested are composed by different percentages of water and oil, and were previously proposed by some of the authors of this paper to mimic the dielectric properties of human breast tissues. Using a setup comprising a Specim IQ hyperspectral camera with a spatial resolution of 1280 x 960 pixels and a spectral resolution of 204 bands in the range 400–1000 nm, the hyperspectral characteristics of the main constituents of the phantoms, namely water&gelatin and oil, were first evaluated; then, the hyperspectral characteristics of the phantoms were measured. The results show that a difference in the hyperspectral characteristics among these compounds is appreciable over the whole range investigated.

关键词： Water Oils Phantoms Breast Dielectrics Compounds Spatial resolution

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Systematic Comparison of Machine Learning for Activity Recognition in Cross-Subject vs. NonCross-Subject Scenarios: A Preliminary Analysis

Systematic Comparison of Machine Learning for Activity Recog...

引用

IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI)

作者： Samuele Pe Giovanna Nicora Bruna Maria Vittoria Guerra Stefania Sozzi Enea Parimbelli dept. of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9798350362138

ISBN: (纸本)9798350362145

Human Activity Recognition (HAR) is pivotal for automating the detection and classification of human movements. Technological advances in data collection from sensors and cameras is making automatic HAR increasingly available to support robotics-assisted rehabilitation, where the detection of abnormal patterns in movement and gait can aid clinical evaluation of patients with diverse disorders. HAR typically employs Machine Learning (ML) or Deep Learning (DL) techniques to analyze sensor data patterns for various activities. However, the generalizability of ML/DL models remains underexplored, particularly concerning the impact of different training and evaluation settings. Overfitting is a common challenge, especially in medical applications where user-dependent training data hinder generalization. Investigating the performance of ML and DL algorithms after a cross-subject (CS) and a noncross-subject (NCS) division of the dataset into training and test sets is crucial. This study aims to systematically compare various ML and DL algorithms for HAR, evaluating their performance across the CS and NCS settings to discern the impact of inter-subject variability on model generalizability.

关键词： Training Technological innovation Systematics Machine learning algorithms Robot vision systems Training data Medical services Sensors Human activity recognition Overfitting

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Speckle Pattern Imaging for Recognition of Milk Dilutions

Speckle Pattern Imaging for Recognition of Milk Dilutions

引用

IEEE Instrumentation and Measurement Technology Conference

作者： Valentina Bello Matteo Fiocchi Irene Bassi Elena Figus Sabina Merlo Dept. of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Milk adulteration is one of the more frequently reported food fraud and represents a global social and economic concern. One of most common type of counterfeiting is dilution with water. In this work., we report a simple but effective method to recognize different types of commercial cow milk and to detect if a whole milk sample has been diluted with water. The technique is based on the acquisition., by means of a CMOS camera., of speckle pattern images., generated by a red semiconductor laser. Data are then processed: the average intensity and the dimension of the speckle grains can be extracted. We then prove that., by considering both statistical parameters., it is possible to identify different milk type as well as diluted samples with a water fraction higher than 10%.

关键词： Semiconductor device measurement Dairy products Statistical analysis Semiconductor lasers Toxic chemicals Speckle Cows

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Detecting Manure Applications in Sandy Soil Peanut Farmlands Using Multitemporal Sentinel-2 Multispectral Data: A Case Study

Detecting Manure Applications in Sandy Soil Peanut Farmlands...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Mert Cihangiroglu David Marzi Fabio Dell’Acqua Dept. of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

This study investigates the efficacy of NDVI (Normalized Difference Vegetation Index), EOMI (Exogenous Organic Matter Index), and MNDWI (Modified Normalized Difference Water Index) in identifying application of manure in sandy soil farmlands. By leveraging Sentinel-2 multispectral imagery acquired over Turkish farmland in the Adana region, this study aims to assess the joint utilization of these indices to enhance detection methodologies within the specified geographic context.

关键词： Technological innovation Normalized difference vegetation index Normalized difference water index Land surface Soil Satellite images Reliability

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Multicluster Kernel Intuitionistic Fuzzy C-Means and State Transition Algorithm : Framework for Low Light Segmentation Imaging of Tuberculosis Bacilli Base of Semisupervised Approach

Multicluster Kernel Intuitionistic Fuzzy C-Means and State T...

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Sari Ayu Wulandari I Ketut Eddy Purnama Eko Mulyanto Yuniarno Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Biomedical Engineering Faculty of Electrical Engineering Universitas Dian Nuswantoro Semarang Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350319545

ISBN: (纸本)9798350319552

Annotated images are required as ground truth for deep learning. Bacterial segmentation is requires a lot of time and effort when done manually. The autosegmentation task gets more challenging since bacterial images contain low light properties, which have an important effect on auto annotating tasks. In order to solve this issue, we present a system that includes a fuzzy-based clustering method that enhances bacterial object segmentation performance by utilizing the multicluster idea. The State Transform Algorithm (STA) is used to obtain starting centroids in order to increase stability, because the Kernel of Intuitionistic Fuzzy C- Means (KIFCM) is sensitive to starting centroids and hence sensitive to being stuck in local optima. The accuracy of KIFCM-STA with bicluster is poor in low-light images. To boost performance, the multicluster technique (MKIFCM-STA) is presented as a continuation hybrid of KIFCM-STA. This framework allows for the ideal amount of clusters (Silhouette) and cluster ranking to provide clusters containing bacterial objects (Topsis). In order to compare our method against four prior approaches (IFCM, KFCM, KIFCM, and KIFCM-STA), we compare its qualitative aspects (visualization of images) and quantitative aspects (average IOU, Dice, HD, ASD, and Accuracy). In low light image clustering tasks, our model significantly improves and achieves great results in terms of accuracy, with a score of 89.438%. This accomplishment highlights how crucial it is that our framework tackles the problem of low-light image clustering in images of bacteria, eventually improving the image auto-annotation procedure.

关键词： Deep learning Image segmentation Visualization Microorganisms Accuracy Clustering methods Clustering algorithms

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Scalable Resource Management for Latency-Sensitive Applications in Edge Computing 12

Scalable Resource Management for Latency-Sensitive Applicati...

引用

12th electrical Power, Electronics, Communications, Controls and informatics Seminar, EECCIS 2024

作者： Prijono, Wahyu Adi Kuswiradyo, Primatar Sahoo, Dipak Kumar Kusmaryanto, Sigit Purnomowati, Endah Budi Mustofa, Ali Universitas Brawijaya Department of Electrical Engineering Malang Indonesia Odisha University of Technology and Research Dept. of Computer Science Bhubaneswar India

ISBN: (纸本)9798350379914

Edge computing is crucial for latency-sensitive Internet of Things (IoT) applications, providing reduced latency and enhanced computational efficiency. However, ensuring low latency while maintaining scalability presents significant challenges. This paper proposes a scalable resource management algorithm using heuristic methods to optimize resource allocation and workload distribution in edge computing environments. The algorithm dynamically adjusts to real-time demands, ensuring minimal latency and efficient utilization of computational resources. Extensive simulations were conducted to evaluate the performance of the proposed algorithm compared to the Greedy Algorithm and the First-Come, First-Served (FCFS) Algorithm. The results demonstrate that the proposed heuristic algorithm significantly outperforms the baseline algorithms in terms of number of packet losses, decreased average latency by up to 38%, and better resource utilization efficiency by up to 27%. The inclusion of buffers at edge nodes to handle non-real-time traffic allows the system to prioritize real-time traffic effectively, resulting in reduced packet drops and improved overall performance. These results highlight the algorithm's potential for improving the performance and scalability of edge computing for real-time IoT applications. Future research directions include exploring advanced optimization techniques, integrating energy-efficient resource management strategies, addressing security and privacy challenges, and conducting real-world deployment and validation of the proposed algorithm. © 2024 IEEE.

关键词： Heuristic algorithms

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An Investigation of Running Load Comparisons of ARCore on Native Android and Unity for Outdoor Navigation System Using Smartphone 6

An Investigation of Running Load Comparisons of ARCore on Na...

引用

6th International Conference on Vocational Education and electrical engineering, ICVEE 2023

作者： Brata, Komang Candra Funabiki, Nobuo Sukaridhoto, Sritrusta Fajrianti, Evianita Dewi Mentari, Mustika Okayama University Dept. of Information and Communication Systems Okayama Japan Universitas Brawijaya Dept. of Informatics Engineering Malang Indonesia Politeknik Elektronika Negeri Surabaya Dept. of Informatic and Computer Surabaya Indonesia State Polytechnic of Malang Dept. of Information Technology Malang Indonesia

ISBN: (纸本)9798350326642

In recent years, the utilization of location-based augmented reality (LAR) has gained popularity across various domains, including tourism, education, gaming, and advertising. The advancements in AR technology have made it easier to develop immersive LAR applications. ARCore, a widely adopted AR development library, enables the creation of location-based AR apps on Android devices. However, the implementation of ARCore in real-Time scenarios that demand significant computational resources, like outdoor pedestrian navigation, can vary depending on the chosen development environment. This research aims to explore and compare the running load performance of ARCore implementation in location-based AR applications developed with Unity and Android Native, which are two prevalent AR development platforms. The study involves building a prototype LAR application using both Unity and native Android, followed by comprehensive running load performance evaluations. The findings reveal that while both Unity and native Android apps can deliver compelling location-based AR experiences, native Android apps demonstrate superior performance and resource efficiency in outdoor scenarios, whereas Unity offers the advantage of multi-platform support and ease of development for complex 3D assets. These insights provide valuable guidance to developers in selecting the most suitable approach for developing location-based AR applications for navigation, aligning with their specific needs and requirements. © 2023 IEEE.

关键词： Augmented reality

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Artificial Intelligence of Things;Remote Robot System Interacts with Humans and Vice Versa During Pandemic 5

Artificial Intelligence of Things;Remote Robot System Intera...

引用

5th World Symposium on Communication engineering, WSCE 2022

作者： Metallidou, Chrysi Psannis, Kostas E. Sarigiannidis, Panagiotis Michalas, Angelos Vergados, Dimitrios D. Goudos, Sotirios University of Macedonia Dept. of Applied Informatics Thessaloniki Greece Dept of Economics/Computer Science University of Western Macedonia Kastoria Greece University of Western Dept. of Electrical & Computer Engineering Kozani Greece University of Piraeus Dept. of Informatics Piraeus Greece Aristotle University Dept. of Physics Thessaloniki Greece

ISBN: (数字)9781665450577

ISBN: (纸本)9781665450577

Nowadays., the advancement of artificial intelligence has led to the application of robotic systems in the industry, especially in the hotel industry, with a view to providing intelligent, automated and luxury services. At the same time, the knowledge gained from the Covid19 pandemic outbreak that convulses the world community, highlights the issue of sustainability in the hotel industry, solved by utilizing artificial intelligence achievements, remote robot systems, so as to guarantee reliability and security of a hotel's functionality, by providing not only convenient accommodation to guests, but safety, as well. In this paper, we focus on the development of a remote robot system, utilizing the Internet of Things, that has various kinds of sensors and cameras. Both the owners of the hotel and the guests can collaborate with the robot efficiently and accurately, since the robot is able to react with them. Specifically, the developed robot is able to serve clients, by providing them with hotel supplies and by giving them any requested information. In return, the guests are requested to give feedback to the robot upon check out. In addition, the robot browses throughout the hotel to inspect the normal and efficient functionality of all technical systems. The developed robot is also a Covid19 inspector, since it inspects whether one's pandemic measures are applied among guests in public areas and in case of a patient, the robot detects people connected to the patient, isolates the patient and gives medical care, food and supplies, so as to prevent humans from closely contacting the patient. © 2022 IEEE.

关键词： Sustainable development

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Optimal Module Count for ISOP LLC Resonant Converters based on an HF Transformer Genetic Algorithm Optimization in Motorsport Applications

Optimal Module Count for ISOP LLC Resonant Converters based ...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Volpini, Andrea Tresca, Giulia Campailla, Salvatore Dappiano, Andrea Zanchetta, Pericle University of Pavia Dept. of Electrical Computer and Biomedical Engineering Pavia Italy Marelli Motorsport Research & Development Department Venaria Reale Italy Marelli Motorsport Research & Development Department Corbetta Italy

ISBN: (纸本)9798350376067

This paper investigates the selection of the optimal number of modules in an Input-Series-Output-Parallel (ISOP) LLC resonant DC-DC converter for motorsport applications. The study employs a Genetic Algorithm (GA) multi-objective optimization of the High Frequency Transformer (HFT) power losses and total volume. The analysis is repeated for converters with different numbers of modules, considering both commercially available and custom transformer cores, as well as air and water cooling systems. The Pareto front of solutions is determined and presented in each scenario. Optimization results indicate that for commercial cores, the range of optimal solutions is significantly constrained by thermal limitations. Conversely, a wider range of solutions can be obtained with custom cores. Furthermore, a lower number of modules is preferable for achieving high efficiency. On the other hand, increasing the number of modules can increase the converter power density, although this results in lower efficiency. © 2024 IEEE.

关键词： Genetic algorithms

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Detection of Macrolepiota Procera Mushrooms Using Machine Learning 5

Detection of Macrolepiota Procera Mushrooms Using Machine Le...

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5th World Symposium on Communication engineering, WSCE 2022

作者： Chaschatzis, Christos Karaiskou, Chrysoula Goudos, Sotirios K. Psannis, Konstantinos E. Sarigiannidis, Panagiotis University of Western Macedonia Dept. Electrical and Computer Engineering Kozani Greece Aristotle University of Thessaloniki Dept. Physics Thessaloniki Greece University of Macedonia Dept. Applied Informatics Thessaloniki Greece

ISBN: (数字)9781665450577

ISBN: (纸本)9781665450577

The overpopulation of the latest centuries and recent technological advancements in the primary sector increased demand for improved productivity and product quality in agricultural activities. Modern customers value eco-friendly activities and sustainable consumption. Thus they choose foods with high concentrations of nutritious ingredients. Machine learning algorithms enable the implementation of numerous potential solutions in precision agriculture in conjunction with new potent mechanisms. One algorithm that offers high-precision real-time object identifications is the YOLOv5 (You Only Look Once). Furthermore, to improve the resilience of precision agriculture, this work presents experimental findings from the machine learning algorithm (Yolov5) on a unique dataset based on mushroom crops, such as Macrolepiota Procera species. © 2022 IEEE.

关键词： Precision agriculture

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