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共 1528 条记录，以下是181-190 订阅

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Application of the YOLOv5 Neural Network for Pattern Recognition on Radiographic Images of the Human Wrist Joint

Application of the YOLOv5 Neural Network for Pattern Recogni...

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International conference of Signal processing and Intelligent Systems (ICSPIS)

作者： Alena S. Krasnoperova Andrey V. Kamenskiy Dept. of Television and Control Laboratory of television automation Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

ISBN: (数字)9798331532543

ISBN: (纸本)9798331532550

The possibility of using artificial intelligence in the task of recognizing objects of interest in medical radiographic images has been studied. To implement computer vision, the YOLOv5 neural network and the use of its functionality for pattern recognition on radiographic images of the human wrist joint were considered. YOLOv5 is one of the most popular neural network models due to a number of advantages and features: high learning speed, object detection accuracy, efficient use of hardware and support for various architectures. The use of an artificial neural network in medicine is a promising direction that allows one to obtain data on pathologies and anomalies on radiographs, improving the diagnostic process and providing quick results with a high percentage of reliability. To adapt the model for the task of recognizing objects of the wrist joint in radiographic images, a data set was labeled, including images for retraining the neural network model and test images. Learning key numerical properties is key to building and tuning effective neural network models. The correctness of their selection and debugging have a direct impact on achieving the desired results when retraining and using neural networks. According to the results of the neural network, all classes of objects were correctly identified in more than 70% of the images; this indicator is a worthy result of the work, which confirms the relevance of using a computer vision tool in medical diagnostics and practical application in clinical practice.

关键词： Wrist YOLO Adaptation models Image recognition Neural networks Bones Pattern recognition Numerical models Object recognition Joints

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Rolling Bearing Fault diagnostics Using SSA-ELM and TVF-EMD Multi-Scale Entropy

Rolling Bearing Fault Diagnostics Using SSA-ELM and TVF-EMD ...

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Advanced Algorithms and control Engineering (ICAACE), International conference on

作者： Shuo Song Guangcuan Wu Wenbo Wang Hubei Province Key Laboratory of System Science in Metallurgical Process Wuhan University of Science and Technology Wuhan China Guangdong Hongtu Wuhan Die Casting Co. Wuhan China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

In order to address the issues with the traditional intelligent algorithm for optimizing ELM parameters-such as slow optimization speed, many adjustment parameters, and easy fall into the local optimal value-and its potential use in bearing fault classification using extreme learning machines (ELM), we propose a fault diagnosis method that combines time-varying filtering empirical modal decomposition (TVF-EMD) multiscale entropy with support vector machine (SSA-ELM). This research takes a look at rolling bearing defect feature extraction and ELM parameter optimization, and then introduces a novel swarm intelligence optimization approach. To improve the optimization speed and accuracy of bearing fault classification, the Sparrow Search algorithm (SSA) is used to optimize ELM parameters. A number of intrinsic mode functions (IMF) are derived from the signal after its decomposition using the TVF-EMD method. The next step is to recombine the beneficial IMF components by using the appropriate coefficient approach to identify them. Finally, the reconstructed signal's multi-scale entropy is determined using the feature vector, and the fault classification is carried out with the input of SSA-optimized ELM. The results show that the fault information can be obtained accurately and the identification accuracy is high. The feature vector is used to calculate the multi-scale entropy of the reconstructed signal, this method has better fault diagnosis classification performance.

关键词： Fault diagnosis Support vector machines Rolling bearings Feature extraction Entropy Data models Vectors

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An Approach to Gathering a Set of Vibrational Signals From Rolling Element Bearings at Various Stages of Local Defect Development

An Approach to Gathering a Set of Vibrational Signals From R...

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International conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Zoya A. Kolosova Dmitry A. Shnayder Olga P. Kolosova Department of Automation and Control South Ural State University Chelyabinsk Russian Federation Department of Technical Mechanics South Ural State University Chelyabinsk Russian Federation

ISBN: (数字)9798331512194

ISBN: (纸本)9798331512200

The paper presents an approach to obtaining a set of vibrational signals from rolling element bearings (REBs) at various stages of local defect development. The study is highly relevant due to the need to enhance the accuracy and reliability of bearing diagnostics under real operating conditions. In realworld obtaining such a set of signals can be challenging, as it requires either waiting for a defect to naturally occur over an extended period or intentionally damaging the bearing. However, the paper proposes an alternative method that combines experimental extraction of real signal and modeling impulses generated by a local defect. This method involves the following steps: recording a signal from a healthy bearing on a laboratory test rig, creating a model of this bearing using the finite element method (FEM), generating a sequence of impulses that simulate a defect (e.g., a pit on the outer race of the bearing) and superimposing this sequence onto the healthy signal to obtain a vibrational signal from a REB with a defect. By changing the model, it is possible to obtain signals from bearings with various defects and stages of their development, making a set with gradually developing defects. This set of signals can be used for testing vibration diagnostic methods. It can significantly simplify the research process and enhance its efficiency.

关键词： Vibrations Accuracy Rolling bearings Industrial engineering Finite element analysis Recording Manufacturing Reliability Testing

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Reliability Assessment of LCC-HVDC links Using Protection Devices

Reliability Assessment of LCC-HVDC links Using Protection De...

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Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition (ICRSEtoSET), International conference on

作者： Abdelhadi Hameurlaine Larbi Boukezzi Salah Karef Haouari Sayah Laboratory of Applied Automation & Industrial Diagnostics University of Djelfa Djelfa Algeria Materials Science and Informatics Laboratory MSIL University of Djelfa Djelfa Algeria Com Laboratory of Modeling Optimization and Simulation of Real Complex Systems University of Djelfa Djelfa Algeria Intelligent Control and Electrical Power System Laboratory University of SidiBel-Abbes SidiBel-Abbes Algeria

ISBN: (数字)9798350346336

ISBN: (纸本)9798350346343

the DC/AC interaction and the presence of the high nonlinearity in the HVDC links, these problems needs to examine the behavior of the system in steady-state and transient conditions in order to define the great role of protection functions and control parameters. Furthermore, control and protection systems are a vital part of an HVDC system to guarantee the safety, reliability, and stability of its operation. This research aim is to provide the solutions for control and protection problems that can occur in HVDC link. In this paper, we study how we mitigate this serious malfunction of commutation failure process in the operation of HVDC converters. Indeed some protection functions like the commutation failure prevention. Furthermore, HVDC transmission systems are vulnerable to DC faults and its protection becomes ever more important with the fast growth in the number of installations. Finally, the dynamics of the studied power system including the HVDC link is thoroughly investigated through various simulation scenarios.

关键词： Performance evaluation HVDC transmission Power system dynamics Power system stability Stability analysis Power system reliability Steady-state

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A New Era of Malaria’s Disease control using AI-Driven Predictive Models

A New Era of Malaria’s Disease Control using AI-Driven Pred...

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Advancement in Computation & Computer Technologies (InCACCT), International conference on

作者： Paras Jain Jaishree Meena Priyank Pandey Vidisha Amity Prathamesh Shelke Vishan Kumar Gupta School of Computing Science Engineering and Artificial Intelligence VIT Bhopal University Kothrikalan Sehore MP India Department of Bioinformatics Amity School of Biological Sciences Amity University Punjab Mohali India Department of CSE Graphic Era Deemed to be University Dehradun India Amity School of Engineering and Technology Amity University Punjab Mohali India

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Malaria remains a public health menace affecting around more than 240 million cases, and hundreds of thousands of deaths per annum with most cases reported from Sub-Saharan region. Advancement in Artificial Intelligence and Machine Learning offers transformative solutions in malarial control using predictive analytics, programmed diagnostics, effective treatment and malarial drug discovery. This paper aims to explore the use of AI in managing malaria, outlining methodologies like Recurrent Neural Networks that can predict malarial outbreaks with high efficiency, Convolutional Neural Networks for blood smears detection and Deep Learning models for identifying new drug combinations for malarial management. AI can be useful in vector control by reviewing the behavior and environment of mosquitoes to improve the efficiency of the treatments and its implementation in malaria diagnosis and tailored treatment decreasing human error and smoothening the use of resources while speeding up the treatment process. The long-term advancement includes both AI technology in geo-spatial and predictive analytics in real-time approach to epidemic surveillance and management of resources. Genetic markers for patients and individual treatment history shall also continue to expand the possibilities of the management of malaria. However, issues like ethical hurdles, collection and protection of patient data and medical implementation need to be attended. It is therefore important to engage collective efforts of governments, non-government organizations as well as technology delivering firms to unlock the full potential of AI in eliminating malaria and in improving global health outcomes worldwide.

关键词： Epidemics Ethics Malaria Government Predictive models Real-time systems Public healthcare Predictive analytics Medical diagnostic imaging Non-governmental organizations

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Functionalization of Polydopamine on Fiber Optic-based Localized Surface Plasmon Resonance for Biosensor

Functionalization of Polydopamine on Fiber Optic-based Local...

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International conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)

作者： Nuha Nazilah Sahabudin Shela Ilmiyah Sjaikhurrizal El Muttaqien Brian Yuliarto Ferry Anggoro Ardy Nugroho Iwan Darmadi Lia Aprilia Research Center for Nanoscience and Nanotechnology Bandung Institute of Technology Bandung Indonesia Research Center for Photonics National Research and Innovation Agency South Tangerang Indonesia Research Center for Vaccine and Drug National Research and Innovation Agency South Tangerang Indonesia Department of Physics Universitas Indonesia Depok Indonesia

ISBN: (数字)9798350389920

ISBN: (纸本)9798350389937

This study features functionalization of polydopamine (PDA) on Au nanoparticles-coated fiber optics for biosensor applications, demonstrating both real-time (insitu) and at final stage (ex-situ) monitoring of the PDA polymerization with and without stirring. The measurement was set up in reflectance mode. Light from the halogen light source travels through the fiber optic, exciting a localized surface plasmon resonance (LSPR) of the Au nanoparticles along the sensing area in coupling to the evanescence field of the fiber optic. The reflected light spectrum is recorded and monitored by the spectrometer, and the evolution of the LSPR peak is tracked in real-time. As a result, the polymerization and deposition process of the PDA layer on the Au nanoparticle is observed to induce a redshift to the LSPR peak shift due to an increase in PDA thickness and refractive index. Moreover, the implementation of stirring during the PDA deposition process significantly accelerates the polymerization rate. Finally, the PDA functionalization was verified using bovine serum albumin (BSA) adsorption. The real-time binding process of BSA on the PDA layer is indicated by further LSPR peak redshift. The binding of BSA is irreversible upon solvent flush. These results showed that implementation of in-situ monitoring opens the possibility of monitoring nanoscale growth and activity in controlled environment that will benefit the development of sensitive, specific, and real-time biosensors for medical diagnostics, environmental monitoring, and food safety applications.

关键词： Optical fibers Reflectivity Gold Refractive index Radar antennas Optical variables control Real-time systems Surface plasmon resonance Polymers Biosensors

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Development of Optoelectronic control Measurement System Based on Attenuated Total Reflectance Effect

Development of Optoelectronic Control Measurement System Bas...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Bakhtiyorjon N. Rakhimov Salauat K. Kengesbayev Alisher A. Berdiyev Teleradiobroadcasting technologies dept Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

This paper delves into the refractometric methodology for monitoring liquid media within the infrared spectrum, presenting a pioneering design of an optoelectronic system anchored on an attenuated total reflectance element. The proposed system exhibits heightened sensitivity, tailored for precise analysis of optical parameters of liquid media products. Utilizing key components such as light-emitting diodes, a cuvette, the attenuated total reflectance element, and an optical detector, this system epitomizes versatility and efficacy across diverse *** the integration of attenuated total reflectance elements, researchers and engineers can develop highly sensitive instruments, facilitating non-destructive testing, chemical analysis, and environmental monitoring. The inherent flexibility in such systems enables customization to meet specific measurement requirements, ranging from industrial process monitoring to medical diagnostics, by adjusting parameters like angle of incidence, light wavelength, and optical material selection. This paper contributes to advancing optoelectronic control measurement systems, offering enhanced capabilities for accurate and reliable assessment of liquid media properties in various fields.

关键词： Reflectivity Liquids Accuracy Wavelength measurement Media Attenuation measurement Optical detectors

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Case Study: Predicting Electrical Submersible Pump Failures Using Artificial Intelligence

Case Study: Predicting Electrical Submersible Pump Failures ...

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Offshore Technology conference, OTC 2022

作者： Silvia, Shejuti Prior, Malcolm Gilad, Yocheved Baker Hughes United States

ISBN: (纸本)9781613998526

Unplanned Electrical Submersible Pump (ESP) failures can have a profound impact on well production and overall field economics;therefore, it is important to reliably predict the onset of damaging operating conditions and take proactive action to prevent early failure of an ESP. Most operators rely on production engineers to monitor and optimize equipment performance with remote monitoring and surveillance technologies that provide threshold-based diagnostics to detect electrical or mechanical problems. Due to inherent limitations in exception-based monitoring, it is extremely difficult to reliably predict the root cause of equipment failure and remaining useful life (RUL) of an ESP. A major operator in the Americas was experiencing similar operational challenges in three of its producing assets. Unplanned failures happen frequently since they are hard to predict ahead of time with the data available to production engineers. This case study demonstrates how Advanced ESP Predictive Failure Analytics (PFA) technology has helped this operator to detect such events and extend ESP run life. Methods, Procedures, process: PFA is an innovative technique that leverages artificial intelligence (AI), life data analysis, physics, and knowledge-based methods to predict electrical and mechanical events and provides an estimate of RUL of an ESP. The data-driven models are trained using sensor time-series of historical failures and entail advanced data processing, interpolation, quality evaluation and feature engineering. The trained models are deployed to predict short term damage events that may lead to immediate failure, such as broken shaft, short-circuit, grounded downhole sensor failure, as well as long term events which build up over time, such as sand, and scale deposition. Results, Observations, Conclusions: For one ESP, PFA detected scale deposition and predicted a sharp decline in RUL. After confirming the decrease in production fluid, and other surface and downhole senso

关键词： Quality control

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Event stream classification with limited labeled data for e-commerce monitoring 21

Event stream classification with limited labeled data for e-...

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21st IEEE International conference on Software Quality, Reliability and Security (QRS)

作者： Zimin, Alexander Mishchenko, Igor Steinert, Rebecca Amazon Com Inc Intelligent Cloud Control Seattle WA 98109 USA

ISBN: (纸本)9781665458139

Monitoring and diagnostics of large software systems is crucial to ensure uninterrupted functioning of modern businesses. Reliability engineers have to rely on automatic event processing to identify and mitigate any potential disruptions of the system health from underlying computer networks. As obtaining impact labels for individual events is expensive, systems operators usually maintain only a small representative dataset, making it hard for machine learning practitioners to train models on large-scale data streams. By formulating the problem within the multiple instance learning framework, we propose an approach to event classification that can be effectively trained using this limited information. Our evaluation results show potential 65% reduction in minutes spent by the network reliability engineers on disruption investigations when the proposed model is used. By automatically quantifying the network impact, the proposed approach streamlines the investigation process and reduces the risk of unnecessary wake-up calls among on-call reliability engineers and resolver personnel.

关键词： Machine learning Multiple instance learning Event stream classification Fault Management Service Monitoring

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diagnostics OF THE STATE AND RECOVERY OF REAL TIME SYSTEMS PERFORMANCE 22

DIAGNOSTICS OF THE STATE AND RECOVERY OF REAL TIME SYSTEMS P...

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Proceedings of the 6th International conference on Future Networks & Distributed Systems

作者： Abdujabbar Abidov Department of Digital Economy and Information Technologies Tashkent State University of Economics Uzbekistan

ISBN: (纸本)9781450399050

The issues of improving the operational reliability of the software of the adaptive switching node operating in a real-time system (r.t.s.) are considered in this paper. Methods for detecting errors, diagnosing the state of health, and methods for restoring the readiness of systems are analyzed. Redundancy is used to ensure the reliable functioning of the software of real-time systems. Of the three types of redundancy: temporal, informational, software; the paper pays great attention to temporal redundancy. Which consists in the presence of a reserve time exceeding the minimum necessary for the execution of the program with the control and restoration of the computational process in case of a possible error. Issues of diagnosing (testing) software products are touched upon and recommendations are made on the use of the considered methods of software reliability for real-time systems.

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