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共 12917 条记录，以下是91-100 订阅

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Advances in Deep Learning for Tuberculosis Detection in Chest X-Rays: A Review of Diagnostic Accuracy 3

Advances in Deep Learning for Tuberculosis Detection in Ches...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Jayakumar, K. Muthupandi, G. Dhayanidhi, R. Pavithra, S. Dept. of Computer Science and Engineering Chennai Institute of Technology Tamilnadu Chennai600069 India

ISBN: (纸本)9798331527549

Tuberculosis (TB) is one of the leading causes of deaths globally, mainly in low- and middle-income countries. Early and accurate detection is crucial for effective treatment and disease control. In this paper, models like CNNs-VGG16, ResNet, and DenseNet, to name a few, are taken into an exhaustive study. optimization techniques, including transfer learning and ensemble methods, which can increase accuracy in the challenging diverse clinical settings, will be presented. Equitable healthcare outcome is achieved in terms of future research directions which include representative datasets and interpretability of the model. © 2025 IEEE.

关键词： Disease control

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Research and Practice of Algorithm Platform in Logistics Distribution Network optimization 3

Research and Practice of Algorithm Platform in Logistics Dis...

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3rd international conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2024

作者： Yu, He Changchun College of Electronic Technology Changchun130000 China

ISBN: (纸本)9798331519032

Logistics industry as the main distribution mode of online shopping, then the efficiency of logistics distribution will become a very important content for consumers, and will also become the optimization direction of logistics distribution network. Combined with many previous studies, this paper believes that the design of distribution route will become the main way to improve distribution efficiency, and studies the algorithm platform and its potential, and proposes to use an improved ant colony algorithm to design a more efficient distribution route, so as to realize the optimization of logistics distribution network. In addition, this paper also verified the method through a comparative experiment. The two sides of the comparison experiment were the distribution route based on the method in this paper as the experimental group and the conventional distribution route as the control group. In the comparison of delivery time, the average delivery time of the experimental group was 9.69h, and the average delivery time of the control group was 14.01h. The average delivery time of the experimental group based on the proposed method is nearly 5h less than that of the control group, which fully indicates that the proposed method can improve the efficiency of logistics distribution and achieve optimization. © 2024 IEEE.

关键词： optimization algorithms

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Predictive adaptive protection scheme for relay co-ordination of directional overcurrent relay using Student Psychology based optimization 3

Predictive adaptive protection scheme for relay co-ordinatio...

引用

3rd international conference on Power Electronics and IoT applications in Renewable Energy and its control, PARC 2024

作者： Kaur, Gurpreet Moulik, Bedatri Rao, K. Uma Amity University Deptt. of Electrical and Electronics Engineering UP Noida India Amity University Amity Institute of Technology UP Noida India R.V College of Engg Deptt. of Electrical and Electronics Engineering Banglore India

ISBN: (纸本)9798350309409

The novel Predictive Adaptive Protection Scheme (PAPS) presented in this paper addresses the coordination issues related to Directional Overcurrent Relays (DOCRs). Coordination becomes more difficult when renewable energy sources (RES) are integrated into the distribution grid because the on/off states of distribution generators (DG) alter the topology of the grid. These modifications affect short-circuit currents, which impairs dependability and causes protection relays miscoordination. In order to mitigate this, Directional Overcurrent Relay (DOCR) settings are optimised by Student Psychology Based optimisation (SPBO), which is essential for managing the propagation of bi-directional fault currents, the overall relay response time should be minimised. Considering various operational scenarios of distributed generators (DGs) in the grid, the successful performance of the suggested Protection Scheme (PAPS) in coordinating DOCRs is verified through the incorporation of the IEEE 14-bus distribution network. © 2024 IEEE.

关键词： Students

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Ensembled Machine Learning Models for Antenna optimization in Wireless Communication/ Biomedical applications 3

Ensembled Machine Learning Models for Antenna Optimization i...

引用

3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Upadhyay, Nidhi Kaur, Amanpreet Singh, Ashima Pattanayak, Arnab Thapar Institute of Engineering and Technology Department of Electronics and Communication Engineering Punjab India Thapar Institute of Engineering and Technology Department of Computer Science Engineering Punjab India

ISBN: (纸本)9798331528201

In this work, the antenna optimisation process is done by using ML algorithms such as KNN, random forest, Gradient Boost, XG Boost and MLP. Then the predicted results are ensembled using Voting Regressor. A Cylindrical Dielectric Resonator Antenna (CDRA) was designed and simulated in CST MWS'23 for this purpose. Dataset is created by varying the radius of the DR using parametric sweep function of the EM simulator. A close prediction between actual values and the predicted ones is obtained using these ML models. It is observed that by ensembling these varied approaches, a model that can handle different types of relationships in the data, can be created. This algorithm can be further utilized for optimisation of other antenna parameters and thus helping in reducing time in optimising complex antenna designs. The accuracy achieved by the ensemble model is 98.6% while maintaining a small MSE of 0.001. The optimized design shows stable characteristics within the ISM band and hence can be used for biomedical as well as wireless communication applications. © 2024 IEEE.

关键词： Random forests

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Research on the loss optimization design of asynchronous motors 3

Research on the loss optimization design of asynchronous mot...

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3rd international conference on Energy, Power and Electrical Technology, ICEPET 2024

作者： Hou, Yulin Shuai, Shiyi Xu, Yifei Harbin University of Science and Technology Department of Electrical Engineering and Automation Harbin China

ISBN: (纸本)9798350352658

With energy conservation and emission reduction becoming an urgent task in society, electric motors, as the driving force of various equipment, improving their efficiency and reducing losses can achieve the goal of energy conservation and emission reduction. This article explores the sources of motor losses and proposes an accurate calculation method. By designing a suitable stator slot optimization process, find the appropriate stator slot, and verify whether the designed stator slot meets the optimization requirements through slot planning equations and power planning equations. By comparing the effects before and after optimization through finite element simulation, it is concluded that this optimization method improves the operational efficiency of the motor. © 2024 IEEE.

关键词： Emission control

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Load Frequency control Design for Interconnected Power System Using Kho-Kho optimization 3

Load Frequency Control Design for Interconnected Power Syste...

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3rd Odisha international conference on Electrical Power Engineering, Communication and Computing Technology, ODICON 2024

作者： Imchen, Samaniba Jamir, Imosong Das, Dushmanta Kumar Nit Nagaland Dimapur Department of EEE Nagaland797103 India

ISBN: (纸本)9798350354379

This study presents a proportional-integral-derivative (PID) controller devised to resolve the load frequency control challenge in an integrated power system incorporating a doubly-fed induction generator based on the wind power system. Its primary duty is to oversee the regulation of processes, ensuring consistent adherence to a predetermined set point. This precision in control is attained through the continuous adjustment of the controller's output, intricately connected to the ongoing disparity between the real-time measurement of the process variable and the desired set-point. In this study, the conceptual model of the KKO method is based on implementing the kho-kho algorithm. This method embodies a population-related, nature-inspired heuristic optimization technique, reflecting the strategic approach of the pursuing team to tag or capture the opposing team's sprinter. © 2024 IEEE.

关键词： Asynchronous generators

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Medical Equipment Maintenance Management and optimization in Healthcare Facilities: Literature Review 3

Medical Equipment Maintenance Management and Optimization in...

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3rd IEEE international conference on Electronic Engineering, ICEEM 2023

作者： Ramadan, E.A. Abu-Ghaleb, A.A. El-Brawany, M.A. Menoufia University Faculty of Electronic Engineering Department of Industrial Electronics and Control Engineering Menouf32952 Egypt

ISBN: (纸本)9798350323511

The goal of this paper is to summarize the current literature on maintenance management, optimization techniques of medical equipment in healthcare facilities and try to critique the deficits of each technique. Comprehensive reviews of the literature and select articles were conducted to identify the various optimization techniques, maintenance management models, and the most popular and applicable models in real-world applications. This review found that there is a scarcity of current studies in the field of maintenance optimization modeling of medical equipment. Further studies and research are needed. The paper provides a comprehensive overview of the literature on maintenance management and optimization techniques for medical equipment. It will be a valuable resource for researchers, maintenance professionals, and clinical engineers who are interested in understanding the importance of maintenance management and the various optimization techniques that can be used to make informed decisions about medical equipment assets. © 2023 IEEE.

关键词： Decision making

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Advancing Deep Learning on Edge Devices: Fine-Tuning and Deployment of YOLOv7 Model for Efficient Object Detection in AI based Computer Vision applications 3

Advancing Deep Learning on Edge Devices: Fine-Tuning and Dep...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Shekhar, Sudhanshu Sathwik, T.S. Pritwani, Mayank Mohana Ramakanth Kumar, P. Sreelakshmi, K. RV College of Engineering® Bengaluru India

ISBN: (纸本)9798331527549

This paper investigates the optimization and deployment of YOLOv7 deep learning model on NVIDIA Jetson Nano, an AI-focused edge computing platform for object detection in various computer vision applications. The work leverages TensorRT and quantization techniques for model acceleration for good detection accuracy. Further it examines performance metrics such as speed, accuracy, and resource utilization for image dataset. The model is trained using 80 different classes of objects and demonstrates the use of 6 classes. The average detection accuracy obtained 92.35% and the average processing time is 117.8ms. This work supports AI by demonstrating the feasibility of running deep learning models on edge devices and provides insight into the challenges and opportunities of optimizing AI models for energy-efficient, real-time operations on edge devices for various computer vision applications. © 2025 IEEE.

关键词： Adversarial machine learning

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Cloud-Enabled Bio-Inspired optimization: A Scalable Solution for Complex Real-World Problems 3

Cloud-Enabled Bio-Inspired Optimization: A Scalable Solution...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Shreya Sakthi, U.R. Sruthi, S. Shruti, S.G. Rajganesh, N. Department of Computer Science and Engineering Sri Venkateswara College of Engineering Sriperumbudur India

ISBN: (纸本)9798331527549

Bio-inspired optimization algorithms, encompassing swarm intelligence, neural networks, fuzzy logic, and evolutionary algorithms, are powerful tools for addressing complex real-world optimization problems. However, their effectiveness is often constrained by the computational demands of training and execution, which surpass the capabilities of traditional computing platforms—particularly when dealing with massive datasets or intricate optimization challenges. These limitations restrict the practical applicability of such algorithms. This work introduces a framework that leverages cloud computing as a scalable and efficient platform to overcome these computational barriers. By integrating bio-inspired optimization techniques with the elastic and high-performance resources of cloud environments, this research demonstrates significant improvements in both the scope and efficiency of these algorithms. Experimental results validate the proposed approach, showcasing enhanced performance, reduced execution time, and the ability to solve larger and more complex real-world problems, thereby unlocking the full potential of bio-inspired optimization in practical applications. © 2025 IEEE.

关键词： Cloud platforms

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Oppositional Chemical Reaction optimization Applied to Renewable-Hydro-Thermal Energy Systems 3

Oppositional Chemical Reaction Optimization Applied to Renew...

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3rd IEEE international conference on control, Instrumentation, Energy and Communication, CIEC 2024

作者： Hazra, Sunanda Shukla, Rishabh Dev Roy, Provas Kumar Metia, Supradip Budge Budge Institute of Technology Electrical Engg. Department Kolkata India Kalyani Govt. Engg. College Electrical Engg. Department Nadia India

ISBN: (纸本)9798350313703

Renewable wind energy has always been extremely helpful to minimizing generation costs as well as reducing emissions to develop green/clean environments, in response to the environmental challenges. The high-proportional integration of renewable power presents challenges to the safe and stable operation of power networks because of its randomness, intermittency, and volatility. However, renewable wind power integrated hydro-thermal power plant is a complex optimization problem due to the water discharge rate, variable wind speed, water transport delay, valve point effect, scheduling time linkage and constraints related with hydraulic continuity and generational limits. The stochastic wind speed is evaluated using Weibull probability density function (W-pdf). For resolving complex economic problems, an effective chemical reaction optimization (CRO) is introduced, for the Hydro-Thermal-Wind (HTW) scheduling problem. Additionally, opposition-based learning (OBL) is integrated with the primary CRO algorithm to increase the solution superiority and convergence speed. The proposed optimization (OCRO) is applied to four hydro, three thermal, and two wind power plants systems. Moreover, proposed technique is compared to other current approaches and the suggested method is determined to be more effective than other methods described in the literature. Lastly, the output of cascade hydropower plants is stable, highly adjustable, and responds quickly. © 2024 IEEE.

关键词： Thermoelectric power plants

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