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检索条件"任意字段=2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022"

共 15377 条记录，以下是251-260 订阅

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The development of an Alzheimer's Diagnostic Sensor and Algorithm using Microsaccades Biomarkers 46

The Development of an Alzheimer's Diagnostic Sensor and Algo...

引用

46th Annual international conference of the ieee engineering in Medicine and Biology Society, EMBC 2024

作者： Oh, Seokjun Lee, Jong-Ha Keimyung University Department of Biomedical Engineering Daegu42601 Korea Republic of

ISBN: (纸本)9798350371499

Alzheimer's disease is an irreversible neuro degenerative disease, and associated declines in cognitive function have a significant effect on daily life. Methods such as mini-mental state examination and Montreal cognitive assessment, the existing diagnostic methods for Alzheimer's disease, take a long time and have poor objective assessment score accuracy. This paper presents a novel method that assesses the brain's cognitive state by utilizing eye-tracking technology. The experiment results confirmed that the number of microsaccade occurrences on the x and y axes gradually increased as aging progressed. In addition, it was confirmed that the number of microsaccade occurrences increased as cognitive function scores declined, even among seniors in the same age groups. Based on these results, we prove the correlation between aging and the brain's cognitive functions and verifies that declines in the brain's cognitive functions affect microsaccades. © 2024 ieee.

关键词： Diagnosis

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Entrainment effects upon synaptically connected microcircuit in transcranial alternating current stimulation 11

Entrainment effects upon synaptically connected microcircuit...

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11th international ieee EMBS conference on Neural engineering (ieee/EMBS NER)

作者： Park, Kyeongseop Chung, Hyeyeon Im, Cheolki Jun, Sung Chan Gwangju Inst Sci & Technol Sch Elect Engn & Comp Sci Gwangju 61005 South Korea Duke Univ Dept Biomed Engn Durham NC 27708 USA

ISBN: (纸本)9781665462921

Transcranial alternating current stimulation (tACS) has garnered attention as a popular neuromodulation method for clinical applications. However, neurons' responses to tACS are uncertain and controversy remains whether tACS can entrain neural activity or not. To resolve this controversy, we constructed a realistic cortical microcircuit from validated experimental data to investigate tACS's effects on neural entrainment. We analyzed the firing rate and neural synchronization in response to 10 Hz tACS for models with/without synaptic connections. Consequently, we observed that our results were consistent with in vivo experimental data and that synaptic connections influence neural entrainment's effects. Clinical Relevance-This finding may help us to have a better understanding of the tACS mechanism with respect to neural entrainment. Moreover, the realistic microcircuit model may help predict the neural responses to tACS in clinical applications.

关键词： Electric impedance measurement

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Jointing High-State and Low-State Feature Reconstruction Networks and Discriminator Training for Track Anomaly Detection 4

Jointing High-State and Low-State Feature Reconstruction Net...

引用

4th international conference on Electronic Information engineering and Computer technology, EIECT 2024

作者： Wang, Ziyi Ye, Yun Xie, Hongxing Zheng, Xingke Zhang, Liyan Chen, Enguo Xu, Sheng Guo, Tailiang College of Physics and Information Engineering Fuzhou University Fuzhou350108 China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350108 China

ISBN: (纸本)9798331528850

Railway safety inspections are critical to prevent catastrophic incidents, yet existing anomaly detection methods often suffer from insufficient sample data and overgeneralization. This paper proposes an improved anomaly detection method called HLFRN-D, which integrates dual-state feature reconstruction networks trained alongside a discriminator. HLFRN-D mitigates decoder overgeneralization by shifting the discriminator's focus from pixel-level abnormalities to evaluating the reconstruction performance of the networks. An anomaly generation module and a novel loss function further enhance robustness. Experimental results show that HLFRN-D achieves superior performance, with an AUROC score of 97.6% and PRO score of 94.4% on MVTec AD, and 99.3% AUROC and 97.7% PRO on track datasets, highlighting its effectiveness in detecting diverse anomaly types and locations. © 2024 ieee.

关键词： Semantic Segmentation

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Research on PV power prediction based on VMD-BWO-KELM combination model 3

Research on PV power prediction based on VMD-BWO-KELM combin...

引用

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

作者： Jing, Jiaheng Mutailipu, Meiheriayi Zhang, Jiuming Huang, Mingyao Xinjiang University School of Electrical Engineering Urumqi China Xinjiang University School of Electrical Engineering Engineering Research Center of Northwest Energy Carbon Neutrality Ministry of Education Urumqi China Co Ltd Jiaxing China

ISBN: (纸本)9798350352658

The accuracy of photovoltaic output (PV) power prediction is important for the effective operation of Photovoltaic systems and the well coordination of power system resources. The PV output power is characterized as its randomness, indirectness and fluctuation nature. In this paper, the PV output prediction correlation was established by the Pearson's correlation coefficient to determine the input factors, then the three weather types were categorized according to the size of the scattering ratio to make predictions separately with high integrity. Further more, to enhance the prediction ability of parameter selection, as well as the volatility and non-smoothness of load data, a PV output prediction model based on the combination of Variational mode decomposition (VMD) and Beluga whale optimization (BWO) based on the Kernel extreme learning machine (KELM) was proposed. The prediction results based on the combination model proposed in this paper is reaches a good greement with the selected data set when compared with the single model in terms of prediction effect, with RMSE of 12.64kW, and the MAPE of 0.81%, Thus, a combination model with high PV prediction accuracy is established in this work to provide theoretical support for efficient use of renewable energy in terms of photovoltaic power generation technology. © 2024 ieee.

关键词： Prediction models

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Hardware Design and development of Modular Multilevel Converter 17

Hardware Design and Development of Modular Multilevel Conver...

引用

17th ieee international conference on Compatibility, Power Electronics and Power engineering, CPE-POWERENG 2023

作者： Mayank, Kumar Verma, Atul Meikap, Somnath Hrishikesan, V.M. Kumar, Chandan IIT Guwahati Dept of EEE Guwahati India Chair of Power Electronics CAU of Kiel Keil Germany

ISBN: (纸本)9798350300048

Modular multi-level converter (MMC) is a popular multi-level converter configuration due to its various features such as ease of scalability, modularity, and low voltage and current rating demand for the power switches. This paper presents the development and implementation of hardware prototype of MMC as a grid forming inverter. An MMC prototype is developed having three sub-modules in an arm, which can be configured as either half bridge-based sub-module or full bridge-based sub-module. Design of various circuits and sizing of various components are carried out for the MMC setup. All the hardware related design and control technique are discussed. Lastly, hardware results for operation of MMC as grid forming inverter are presented. © 2023 ieee.

关键词： Electric inverters

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Machine Learning Security Algorithms and Framework for IOT System

Machine Learning Security Algorithms and Framework for IOT S...

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2022 OPJU international technology conference on Emerging Technologies for Sustainable development, OTCON 2022

作者： Mishra, Megha Mishra, Vishnu Kumar Tekale, Sunil Nagapraveena, T. Parijatha, Kimidi Dewangan, Bhupesh Hadimani, Saddamhusian Csvtu University Computer Science Engineering Shri Shankaracharya Technical Campus Chhattisgarh Bhilai India Jntuh University Computer Science & Engineering Malla Reddy College of Engineering Telangana Secunderabad India Op Jindal University Computer Science & Engineering Chhattisgarh Raigarh India

ISBN: (纸本)9781665492942

This paper cover different security issues needs along with attack and vectors attacks and also highlighted current issues and solutions for IoT security for networks are all thoroughly reviewed in this study. Here we cover ML and DL methods for holes in these security solutions that demand strategies are then highlighted. We also go into great detail about the ML and DL technologies that are now being used to solve a range of security harms to different IoT networks. In this study we highlighted the future research prospects for ML (Machine Leraning) and DL (Deep Learning) based IoT security based on the thorough analysis of the already published solutions. This work focused on a brand-new (ML) machine learning based security framework that adapts automatically to the evolving security needs of the IoT domain. For the purpose of reducing various vulnerabilities, this framework formulate utilize of both (NFV) Network Function Virtualization enabler's and (SDN) Software Defined Networking. To accomplish this result we are using supervised learning and their framework that system more secures and distributed data mining system, and neural networks. © 2023 ieee.

关键词： Internet of things

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Research on Weather Process Similarity Based on 3D CNN Autoencoder 3

Research on Weather Process Similarity Based on 3D CNN Autoe...

引用

3rd ieee international conference on Electrical engineering, Big Data and Algorithms, EEBDA 2024

作者： Cheng, Xingguo Zhou, Yajing Li, Zeping School of Software Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798350380989

This article proposes a weather process similarity and retrieval algorithm based on a 3D CNN Autoencoder. It uses 3D CNN to extract features of weather elements in multi-dimensional space. The encoder outputs a one-dimensional vector of size 512. The cosine similarity between two weather processes is then calculated based on the two one-dimensional vectors, representing their similarity. Experimental data demonstrates the effectiveness of this algorithm. By searching historical weather processes based on the forecast date and referring to the evolution of historical weather processes, it provides positive guidance for current weather forecasts. © 2024 ieee.

关键词： Autoencoder cosine similarity decoder encoder weather process similarity

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Management of IT Operations and IT Infrastructure with Virtual Reality

Management of IT Operations and IT Infrastructure with Virtu...

引用

2022 OPJU international technology conference on Emerging Technologies for Sustainable development, OTCON 2022

作者： Saurav, Swapnil Sudeep, K.S. Gitam University Computer Science & Engineering Hyderabad India

ISBN: (纸本)9781665492942

Virtual reality (VR) technology has been successfully implemented in multiple industries and VR has brought us a vast number of new displays and input devices. The purpose of this paper is to conduct an in-depth study of the various applications of virtual reality (VR) in industrial operations in order to collect evidence of VR's benefits, limitations, and potential future directions. Recent advances in VR software and hardware have made it possible to apply the technology in a wide range of manufacturing settings, including design, engineering, production, O&M, and more. The human-computer interface of the digital VR platform is both user-friendly and immersive, which can be beneficial for IT and computing instruction as well as maintenance services. This will allow VR to be directed to better serve IT industry operations. This is a fact that cannot be denied, both humans and VR technology can be trained to work together effectively through training programs designed for both. © 2023 ieee.

关键词： Virtual reality

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Triple-Attention Residual Networks for Hyperspectral Image Classification 5

Triple-Attention Residual Networks for Hyperspectral Image C...

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5th international conference on Computer Vision, Image and Deep Learning, CVIDL 2024

作者： Zhang, Lu Ruan, Chao Zhao, Jinling Huang, Linsheng Anhui University Anhui Province Hefei China Anhui University National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui Province Hefei China

ISBN: (纸本)9798350373820

The attention mechanism has been widely applied in hyperspectral image classification, yet most current methods rely on a relatively simple form of attention, which fails to extract features deeply. To address this issue, this paper proposes a triple-attention residual networks (TARN) for hyperspectral image (HSI) classification. This method can not only emphasize the importance of different bands in hyperspectral image classification, but also capture pairwise relationships between spatial feature pixels at the pixel level. By integrating these attention mechanisms, we achieve efficient extraction of spectral-spatial features. Extensive experiments demonstrate that the proposed artificial neural network significantly outperforms state-of-the-art methods, exhibiting its superior performance in hyperspectral image classification. © 2024 ieee.

关键词： Pixels

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Multi-objective Optimization Dispatch Strategy for the Building PEDF System Based on Model Predictive Control 2

Multi-objective Optimization Dispatch Strategy for the Build...

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ieee 2nd international conference on Power Science and technology (ICPST)

作者： Zhang Lin Ke Ji Duan Chendong Miao Yu Hao Yue Yin Yaohua Xing Xueshu Changan Univ Sch Energy & Elect Engn Xian Peoples R China State Grid Beijing Yizhuang Elect Power Supply Co Beijing Peoples R China Power China Guiyang Engn Co Ltd Guiyang Peoples R China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047;9798350349030

The power supply and distribution of the 'Photovoltaic, Energy Storage, Direct current and Flexibility (PEDF)' system in buildings is often challenged due to the temporal mismatch between electricity generation and consumption. The electricity supply of the PEDF system needs to be flexibly adjusted to accurately respond to load demand and decarbonize the building's operation, which poses challenges for power dispatching within the system. This study proposes a data-driven model predictive control optimization strategy, considering three representative electricity consumption scenarios for residential, commercial, and industrial sectors under two weather conditions (clear/cloudy). The proposed strategy aims to optimize carbon emissions and power purchase costs as primary objectives while incorporating Time-Of-Use pricing. The results demonstrate that across various scenarios, the optimized dispatch strategy significantly mitigates carbon emissions and reduces power purchase costs incurred by the system during daily operations compared to the conventional rule-based dispatch approach. These findings offer insights into promoting low-carbon buildings and fostering sustainable development in building energy.

关键词： Photovoltaic Energy Storage Direct current and Flexibility (PEDF) Model predictive control Multi-scenario analysis Multi-objective dispatch strategy

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