检索结果-内蒙古大学图书馆

10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Vinu, M.S. Priya, P Kanaga Thilakaveni, P. Hermina, J. M. Ashforn Prashanthini, K. Misba, M. Nehru Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Psg Polytechnic College Department of Computer Engineering Coimbatore India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Erode India Sri Ramakrishna Engineering College Department of Robotics and Automation Coimbatore India Bethlahem Institute of Engineering Department of Computer Science and Engineering Nagercoil Karungal India

ISBN: (纸本)9798350384369

The development of intelligent street light systems has ushered in a new era of efficiency and sustainability in urban infrastructure. The proposed work studies the integration of modern sensors and Internet of Things (IoT) technologies to increase the functionality of street lights. The major components include Light Dependent Resistors (LDR) for automatic light management, an MQ135 sensor for air quality monitoring, and a fog detection system employing a laser module and LDR. These sensors are integrated with the ESP8266, providing cloud integration for real-time data visualization and monitoring. Additionally, solar panels are employed to enhance energy efficiency. The proposed methodology digs into the precise implementation, data analysis, and the potential of this system to alter urban lighting infrastructure © 2024 IEEE.

关键词： Air quality

来源：评论

学校读者我要写书评

暂无评论

Study of Dielectric Relaxation of Insulating Oil from Lagenaria siceraria Seeds

引用

World Journal of Engineering and Technology 2024年第4期12卷 821-835页

作者： Michael Koumbou Piembe Jean Ndoumbe Charles Hubert Kom Laboratory of Electronics Electrotechnics Automation and Telecommunications National Higher Polytechnic School of Douala University of Douala Douala Cameroon Laboratory of Computer Engineering Data Science and Artificial Intelligence National Higher Polytechnic School of Douala University of Douala Douala Cameroon

The present work concerns the study of the dielectric relaxation of dielectric oil based on Lagenaria siceraria (calabash) seeds. Dielectric spectroscopy was used to measure the loss angle, the dielectric constant and the electrical modulus. Three relaxation processes in calabash oil were identified. It was also found that the relative permittivity decreases with increasing temperature and frequency. A study of the imaginary part of the electrical modulus was done and revealed a relaxation process at low frequencies. At higher frequencies, the dielectric relaxation is thermally activated. The increase in temperature leads to a decrease in the relaxation rate. The result obtained indicates that relaxation type is not of the Debye type in the high-frequency region. The Cole-Cole model of the imaginary part of the permittivity as a function of its real part in calabash oil for different temperatures was drawn and analyzed. It shows the existence of a negative temperature coefficient of resistance in the fluid and helps identifying a relaxation process in the conductivity of the sample studied. It highlights the presence of Debye relaxation which characterizes the presence of an abnormal dispersion of the dielectric constant over a frequency range. Calabash seed oil exhibits better dielectric constant (relative permittivity) compared to other oils.

关键词： Dielectric Relaxation Electric Modulus Calabash Seed Oil Dielectric Spectroscopy Cole-Cole Model Debye Model

来源：评论

学校读者我要写书评

暂无评论

A Dynamic-Static Weighted Network with Diverse-Token Fusion Attention for Rhexis Margin Recognition in Microscopic Surgery

A Dynamic-Static Weighted Network with Diverse-Token Fusion ...

引用

2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Li, Zhen Yue, Wen-Qian Bian, Gui-Bin Zhang, Shuai Liu, Wei-Peng Li, Shuo Tongji University School of Electronic and Information Engineering Shanghai200092 China Chinese Academy of Sciences Institute of Automation Beijing100190 China Hebei University of Technology School of Health Sciences and Biomedical Engineering Tianjin300131 China Hebei University of Technology School of Artificial Intelligence and Data Science Tianjin300131 China Case Western Reserve University Departments Biomedical Engineering and Computer and Data Science United States

ISBN: (纸本)9798350325706

In microscopic cataract surgery, capsulorhexis is the first, most critical step. However, recognizing the boundary of the rhexis during capsulorhexis is challenging and has rarely been studied due to its intraoperative invisibility, variable shape, and lack of a proprietary labeled dataset, especially in the robot-sssisted surgery. To solve the problems, this paper proposes a creative dynamic boundary recognition solution, which includes a novel segmentation network, DCTNet, and a compensation block. First, the dilated HRNet is designed to constrain the over-compression while maintaining high-resolution representation for better detail preservation. Second, the cascaded transformer block is proposed: The decoupling transformer (DET) is developed to assign dynamic-static weights thus learning the variation pattern for segmented targets decoupling. The coupling transformer(COT) with redistributed embeddings is then developed to fuse diverse-resolution tokens for multi-scale prediction coupling. Moreover, the compensation block compensates for inter-frame movement by key-point registration and recovers a more realistic boundary by a smoothing process. Creatively, we mathematically estimate the uncertainty of framework to eliminate the misidentifications due to aleatoric uncertainty in data. Finally, to evaluate the proposed framework, we establish the first known capsulorhexis dataset, CapSeg. Our proposed DCTNet achieves superior performance to state-of-the-art networks with a lower computational cost, and the feasibility experiment shows its great potential in medical surgical robot. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimizing Power Flow in Northern Cameroon’s Interconnected Grid: Challenges and Solutions

引用

Journal of Power and Energy Engineering 2024年第9期12卷 63-83页

作者： Jean Ndoumbe Ivan Basile Kabeina Michael Koumbou Piembe Martin Ndjock Laboratory of Computer Engineering Data Science and Artificial Intelligence National Higher Polytechnic School of Douala University of Douala Douala Cameroon Laboratory of Electronics Electrotechnics Automation and Telecommunications National Higher Polytechnic School of Douala University of Douala Douala Cameroon

This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve complex power flow equations. This study simulates a series of outage scenarios to evaluate the responsiveness of the grid. The results obtained underline the crucial importance of reactive power management and highlight the urgent need to consolidate the grid infrastructure of North Cameroon. To increase grid resilience and stability, the paper recommends the strategic integration of renewables and the development of interconnections with other power grids. These measures are presented as viable solutions to meet current and future energy distribution challenges, ensuring a reliable and sustainable power supply for Cameroon.

关键词： Power Flow Northern Interconnected Grid Newton-Raphson MATLAB Grid Stability

来源：评论

学校读者我要写书评

暂无评论

A Domain Generalization Model Based on Multilevel Domain Adversarial Invariant Representation Learning

A Domain Generalization Model Based on Multilevel Domain Adv...

引用

6th International Conference on Intelligent Computing and Signal Processing (ICSP)

作者： Kun Liu Ding Wang Ying Yang Jingkai Wang Jingkun Mao School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

Due to the influence of various factors such as cross-scene shooting height, shooting time, imaging angle of view, weather, etc., the performance of the defect detection model degrades in cross-scene situations. In this paper, we proposed a domain generalization model based on multilevel domain adversarial invariant representation learning, which included the designed defect space feature and channel feature enhancement modules. Among them, the defect space feature enhancement module uses the shallow feature invariance score to guide the model to extract cross-scene invariant representations, and at the same time, design and use the defect importance information in the shallow features to enhance the representation of defects in the shallow features. The channel feature enhancement module assigns learning weights to different channels of each sample according to the similarity between the sample and the whole, and the importance of different feature channels to defects, so as to better guide the model to extract cross-scene invariant representations. The experimental verification on the photovoltaic cell data set collected in outdoor natural scenes shows that, proposed model has stronger generalization ability than existed domain generalization methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improved Blending Attention Mechanism in Visual Question Answering

引用

Computer Systems science & Engineering 2023年第10期47卷 1149-1161页

作者： Siyu Lu Yueming Ding Zhengtong Yin Mingzhe Liu Xuan Liu Wenfeng Zheng Lirong Yin School of Automation University of Electronic Science and Technology of ChinaChengdu610054China College of Resource and Environment Engineering Guizhou UniversityGuiyang550025China School of Data Science and Artificial Intelligence Wenzhou University of TechnologyWenzhou325000China School of Public Affairs and Administration University of Electronic Science and Technology of ChinaChengdu611731China Department of Geography and Anthropology Louisiana State UniversityBaton Rouge70803LAUSA

Visual question answering(VQA)has attracted more and more attention in computer vision and natural language *** are committed to studying how to better integrate image features and text features to achieve better results in VQA *** of all features may cause information redundancy and heavy computational *** mechanism is a wise way to solve this ***,using single attention mechanism may cause incomplete concern of *** paper improves the attention mechanism method and proposes a hybrid attention mechanism that combines the spatial attention mechanism method and the channel attention mechanism *** the case that the attention mechanism will cause the loss of the original features,a small portion of image features were added as *** the attention mechanism of text features,a selfattention mechanism was introduced,and the internal structural features of sentences were strengthened to improve the overall *** results show that attention mechanism and feature compensation add 6.1%accuracy to multimodal low-rank bilinear pooling network.

关键词： Visual question answering spatial attention mechanism channel attention mechanism image feature processing text feature extraction

来源：评论

学校读者我要写书评

暂无评论

Microfluidic Lab-on-a-Chip Design and Analysis for GFAP Biomarker Detection Using Machine Learning Algorithms 3

Microfluidic Lab-on-a-Chip Design and Analysis for GFAP Biom...

引用

3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Balaji, P. Devasena, D. Rithick, P. Karthi, T. Rishmitha, K. Roopa, R. Sri Ramakrishna Engineering College Dept. Of. Electronics and Instrumentation Engineering Tamilnadu Coimbatore India Sri Ramakrishna Engineering College Dept. of Robotics and Automation Engineering Tamilnadu Coimbatore India Kongu Engineering College Dept. of Automobile Engineering Erode India Science Arjun College of Technology Dept. of Artificial Intelligence and Data Tamilnadu Coimbatore India

ISBN: (纸本)9798331528201

The detection of Glial Fibrillary Acidic Protein (GFAP) is a crucial biomarker for diagnosing neurological conditions such as traumatic brain injuries (TBI) and astrocytoma. This paper presents the design and analysis of a novel microfluidic Lab-on-a-Chip (LoC) platform for GFAP biomarker detection. The system integrates microfluidic channels with embedded gold nanoparticle-functionalized electrochemical sensors for high-sensitivity biomarker capture. The microfluidic chip is designed using soft lithography and PDMS (Polydimethylsiloxane), allowing for precise fluid handling and minimal sample consumption. The electrochemical sensors generate voltage signals corresponding to GFAP concentration levels, which are processed using digital filtering techniques to mitigate noise and improve signal quality. For accurate biomarker quantification, machine learning algorithms, including Random Forest ,KNN and Support Vector Machine (SVM), are employed to classify sensor output data into clinically significant concentration ranges. The model is trained on both simulated and experimentally collected sensor data, achieving an accuracy of over 93 percent in distinguishing low (below 50 ng/mL) and high (above 50 ng/mL) GFAP concentrations. The combination of microfluidic precision, sensitive electrochemical detection, and data analysis enables rapid and reliable detection of GFAP , providing a scalable and portable solution for early diagnosis of brain injuries and neurodegenerative diseases. This system highlights the potential of integrating microfluidics and machine learning in next-generation point-of-care diagnostic devices. © 2024 IEEE.

关键词： Polydimethylsiloxane

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis on Drug Reviews Using Diverse Classification Techniques 3

Sentiment Analysis on Drug Reviews Using Diverse Classificat...

引用

3rd International Conference on Communication, Computing and Industry 4.0, C2I4 2022

作者： Duraisamy, Premkumar Natarajan, Yuvaraj Preethaa, K.R.Sri Mouthami, K. KPR Institute of Engineering and Technology Department of Artificial Intelligence and Data Science Coimbatore India KPR Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Research Professor Intelligent Construction Automation Center Kyungpook National University Deagu Korea Republic of

ISBN: (纸本)9781665474979

Free text reviews are abundantly distributed over the internet among the standard population of the world. Although online doctors were consulted during the pandemic, many drugs are taken without prescription by ordinary people. Reviews are distributed about the medicines through online feeds, posts and blogs, which are merely helpful in identifying the side effects and their adverse reactions in combination with another drug or standalone adverse reactions. Spelling mistakes, jargon and short names are normalized throughout the medical terminologies using Natural language processing (NLP) and RxNorm from the reviews extracted from these sources. The concept of Bidirectional Encoder Representations from Transformers (BERT) is used to mine the association rules for the drug interactions when used in conjugation with another drug, and the idea of Adaptive Fuzzy logic neural networks is used to validate the results of association rules derived from the BERT. Inconsistencies identified by the regulations generated were rejected efficiently by the Support vector machines (SVM), Radial Basis Function (RBF)and the system shows 60.11 percentage of accuracy with 10 cross-fold validation, whereas the results are equivalent to the accuracy obtained using SVM with RBF kernel. The data set is reduced from its dimension using Linear discriminant analysis (LDA) by applying the mining process and BERT on two drugs, namely 'Azithromycin' in conjugation with Buprenorphine has Type 'A' side effects, and Prozac in conjugation with Metronidazole shows different side effects. Deplin and Zoloft give very positive symptoms and are independent of dosage interactions. © 2022 IEEE.

关键词： Bidirectional Encoder Representations from Transformers (BERT) Linear discriminant analysis (LDA) Radial Basis Function (RBF) Support vector machines (SVM)

来源：评论

学校读者我要写书评

暂无评论

Towards in X-Ray Induced Acoustic Imaging for Nasopharyngeal Carcinoma Radiotherapy with a Multidimensional Information Fusion Network

Towards in X-Ray Induced Acoustic Imaging for Nasopharyngeal...

引用

International Conference on Computer Applications Technology (ICCAT)

作者： Xin Jiang Zhi-Chao Chen Zheng Sun Ming-Zhe Liu School of Artificial Intelligence Chongqing University of Technology Chongqing China Department of Radiology Chongqing University Cancer Hospital Chongqing China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China School of Data Science and Artificial Intelligence Wenzhou University of Technology Wenzhou China

ISBN: (数字)9798331539795

ISBN: (纸本)9798331539801

X-ray-induced acoustic computed tomography (XACT) imaging is an emerging noninvasive imaging technique with wide applications in various clinical medicine fields. However, traditional XACT imaging methods often suffer from low imaging quality and increased noise artifacts, particularly notable under sparse sampling conditions. To overcome these challenges, we propose a hybrid supervised reconstruction method based on deep learning. Specifically, we extract and integrate information from XACT thermoacoustic signals and XACT images reconstructed by traditional methods to leverage complementary feature information from both modalities. To adapt to imaging under sparse sampling, we define multiple sparse conditions based on real-world imaging environments and validate them using a real radiotherapy dataset of head and neck cancer patients. The results demonstrate the adaptability of our method to sparse conditions and its capability to enhance XACT imaging quality under such circumstances. Additionally, we validate the feasibility of X-ray thermoacoustic imaging for 3D dose monitoring.

关键词： Deep learning Three-dimensional displays Imaging Feature extraction Acoustics Robustness Radiation therapy data mining X-ray imaging Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Optimal Energy Storage Operation under Demand Uncertainty: A Prospect Theory Analysis 14

Optimal Energy Storage Operation under Demand Uncertainty: A...

引用

14th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Huang, Qisheng Xu, Jin Sun, Peng Liu, Bo Courcoubetis, Costas Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology School of Management Wuhan China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China The Chinese University of Hong Kong Shenzhen School of Data Science Shenzhen518712 China

ISBN: (纸本)9781665455541

In this paper, we study the consumer's optimal energy storage operation problem under demand uncertainty. Each consumer can purchase energy storage service from an independent energy storage aggregator to shift demand from peak periods to off-peak periods under time-of-use (ToU) pricing. Previous studies on energy storage operation and investment mainly focused on the expected cost-minimization problem of a risk-neutral consumer based on the expected utility theory (EUT). We propose a prospect theory (PT) model from behavioral economics to understand the consumer's realistic energy storage operation behaviors considering their risk preferences. Although it is challenging to solve the PT-based non-convex optimization problem, we are able to characterize the optimal solution by exploiting the unimodal structure of the objective function. Theoretical and numerical results show that the consumer's risk preferences have a significant impact on his decisions: 1) a PT-consumer with a low reference point is more willing to use energy storage to reduce risk compared with the EUT benchmark;and 2) a PT consumer is more willing to use the energy storage when the probability of high demand is small, due to the probability distortion. © 2023 IEEE.

关键词： Energy storage

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：