检索结果-内蒙古大学图书馆

2024 Solar Energy and Light-Emitting Devices, SOLED 2024

作者： Fuentes-Hernandez, Canek Larrain, Felipe A. Kolesov, Vladimir Chang, Yi-Chien Nam, Minwoo Huang, Tzu-Yen Toney, Michael Kippelen, Bernard Department of Electrical and Computer Engineering Northeastern University BostonMA20155 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Faculty of Engineering and Sciences Universidad Adolfo Ibanez Santiago7941169 Chile Department of Electronic Engineering Keimyung University Daegu42601 Korea Republic of

We present an overview of solution-based electrical p-doping of organic semiconductors using polyoxometalates yielding stable exponentially decaying depth-profiles into the bulk and other highly desirable properties f... 详细信息

关键词： Photovoltaics

来源：评论

学校读者我要写书评

暂无评论

Identification of Haploid Maize Seeds Using Efficient Channel Attention with Selective Kernel Networks and Multi-layer Stacked Ensemble

Identification of Haploid Maize Seeds Using Efficient Channe...

引用

Cognitive Computing and Complex Data (ICCD), International Conference on the

作者： Lieto Wamunyima Haiyi Bian Bobwillie Kessellie Sulonteh Faculty of Electronic Information Engineering Huaiyin Institute of Technology Huai’an City China Faculty of Computer Application and Engineering RIMT University Mandi Gobindgarh Punjab India

ISBN: (数字)9798350352894

ISBN: (纸本)9798350352900

This study focuses on the recognition of maize haploid seeds using convolutional neural networks (CNNs). A dataset comprising 3,000 maize seed images, consisting of 1,230 haploid maize seed images and 1,770 diploid maize seed images, was utilized for experimentation. Classical CNN models, including VGG, AlexNet, ResNet, and SKNet, were employed to compare their effectiveness in haploid maize seed recognition. Additionally, this study proposes the ECA-SKEnsemble model, which enhances the SKNet architecture by replacing its fully connected layer with a one-dimensional convolution, thus reducing model complexity. The ECA-SKEnsemble integrates multiple instances of the ECA-SKNet model, each trained with different initializations and training techniques. By combining these models using ensemble techniques such as weighted voting or averaging, ECA-SKEnsemble achieves superior performance in maize seed recognition. The model attained an accuracy of 93.04%, outperforming standard CNN architectures, including VGG and ResNet. This work demonstrates the effectiveness of ensemble learning combined with efficient channel attention for improving maize seed recognition accuracy.

关键词： Training Accuracy Convolution Computational modeling computer architecture Convolutional neural networks Ensemble learning Kernel Tuning Standards

来源：评论

学校读者我要写书评

暂无评论

Compressed VGGNet for Automatic COVID-19 Disease Detection from CT Scan Images 8th

Compressed VGGNet for Automatic COVID-19 Disease Detection f...

引用

8th IFIP TC 12 International Conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Vinothini, R. Niranjana, G. Dhamanti, Inge Lailiyah, Syifa’ul Yakub, Fitri Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur 603203 India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur 603203 India Department of Health Policy and Administration Faculty of Public Health Universitas Airlangga Surabaya Indonesia Faculty of Health Medicine and Life Sciences Universitas Airlangga East Java Indonesia Electronic System Engineering Department Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia

ISBN: (纸本)9783031736162

Millions of people across the globe were affected by this rapidly spreading disease by the year 2020. Contamination of the respiratory system results from contracting COVID-19. Nonetheless, establishing a conclusive diagnosis of COVID-19 may prove difficult due to the subtle differences it shares with conventional pneumonia and the complexities involved in identifying areas of infection. A growing number of approaches based on deep learning (DL) are being proposed for the automated detection of COVID-19 from CT scan images. By employing the data pretreatment methodology, unprocessed image data becomes prepared for further analysis. The proposed framework utilised transfer learning to construct VGGNet, which is capable of discerning the Covid-19 disease. The model was subsequently assessed in comparison to the most sophisticated models, VGG16 and VGG19, using the SARS-COV2 CT scan dataset. This dataset contains 1230 CT scans of non-infected images and 1252 CT scans of Covid-19-infected images. The model has achieved 99% accuracy, 98% precision, 97% recall, and 98% F1-score, among other performance metrics. © IFIP International Federation for Information Processing 2025.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Multi-Virtual-Vector-Based Predictive Current Control for Fault-Tolerant Inverter-Fed Dual Three-Phase Permanent Magnet Synchronous Machines

Multi-Virtual-Vector-Based Predictive Current Control for Fa...

引用

2023 IEEE International Conference on Predictive Control of Electrical Drives and Power electronics, PRECEDE 2023

作者： Li, Ze Rodriguez, Jose Xia, Jinhui Guo, Yuanbo Gao, Xiaonan Zhang, Xiaohua Hebei University College of Electronic and Information Engineering Baoding China Faculty of Engineering Universidad San Sebastian Santiag Chile Southeast University School of Automation Nanjing China Dalian University of Technology School of Electrical Engineering Dalian China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9798350396867

Dual three-phase permanent magnet synchronous machine (DTP-PMSM) has received extensive interests due to its inherent fault-tolerant capability. However, conventional single-virtual-vector-based predictive current control (SVV-PCC) for DTP-PMSM with open-phase fault (OPF) presents poor steady-state performance and high computational burden. To address these issues, a multi-virtual-vector-based PCC (MVV-PCC) for DTP-PMSM with OPF is proposed in this paper. Therein, two virtual vectors and one zero vector with optimal duty cycles are determined in each sampling period to improve the steady-state performance. A simplification strategy for selecting the optimal virtual vectors and calculating the optimal duty cycles is established to reduce the computational burden in digital implementation. Extensive comparisons are conducted to verify the effectiveness of the proposed MVV-PCC scheme. © 2023 IEEE.

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

Using Linear Regression Model to Predict the Wholesale of the Electric Car in Indonesia: What Can Be Learned from the Model? 2nd

Using Linear Regression Model to Predict the Wholesale of th...

引用

2nd International Conference on Renewable Power, ICRP 2023

作者： Al-Hakim, Rosyid R. Soelaiman, Nur F. Riani, Sri Arief, Yanuar Z. Department of Electrical Engineering Faculty of Information Sciences and Engineering Jakarta Global University Kota Depok Indonesia Graduate School IPB University Bogor Indonesia Department of Computer and Informatics Jakarta State Polytechnic Depok Indonesia Faculty of Information and Communication Technology Universiti Teknikal Melaka Malacca Malaysia Department of Biology International Women University Bandung Indonesia Faculty of Biology Universitas Jenderal Soedirman Purwokerto Indonesia Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Malaysia Sarawak Sarawak Kota Samarahan Malaysia

ISBN: (纸本)9789819967483

We analyze wholesale datasets from Indonesian Automobile Industry Data for electric cars in Indonesia using statistical analysis to predict the electric cars used in the future. We apply a linear regression approach that adjusts the regression model according to wholesale electric cars between 2020 and 2022, as well as a statistical correlation test and the Wilcoxon test to support the regression result. We find a strong positive relationship for electric cars bought in the future, with a not significantly different population median of the total number of wholesale electric cars. It might be 210 cars estimated per year. Among the regression model, it is more effective for policymakers, as well as car industries. We estimate that there are various reasons and conditions for Indonesian people regarding buying electric cars inside conventional ones. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry

来源：评论

学校读者我要写书评

暂无评论

Optimal Parameters in Spiking Neurons Make Better Image Classification

Optimal Parameters in Spiking Neurons Make Better Image Clas...

引用

computer technology and Information Science (ISCTIS), International Symposium on

作者： Wei Li Yang Liu Faculty of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

In deep learning, there are many researches on image classification. However, for the traditional Artificial Neural Network (ANN), it is not suitable for some low-power edge devices because of the high energy consumption mainly for a large number of floating-point operations. As the third-generation neural network, Spiking Neural Network (SNN) can avoid high-precision floating-point multiplications due to its pulse mechanism, thereby achieving low power consumption. At the same time, SNN can extract spatio-temporal features and perform well on processing some event-based image sequences. However, formulating efficient and high-performance learning algorithms for SNN remains challenging. Most learning methods only learn the network weights and ignore the optimization of some parameters in the spiking neurons. In this paper, we draw inspiration from the observation that membrane-related parameters differ across brain regions and propose a decoupled spike parameters (DSP) training algorithm that simultaneously learns network weights and membrane potential time constant of SNN by solving a bilevel optimization problem. Our method achieves state-of-the-art on various classification tasks, including the CIFAR, DVS128 Gesture, and CIFAR10DVS datasets. Overall, DSP shows promise in image classification tasks for SNNs, providing a new paradigm for future high-performance SNN training.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Estimating finger joint angles by surface EMG signal using feature extraction and transformer-based deep learning model

引用

Biomedical Signal Processing and Control 2024年第PartB期87卷

作者： Putro, Nur Achmad Sulistyo Avian, Cries Prakosa, Setya Widyawan Mahali, Muhammad Izzuddin Leu, Jenq-Shiou Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taiwan Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Indonesia Department of Electronics and Informatics Engineering Faculty of Engineering Universitas Negeri Yogyakarta Indonesia

Human-machine interfaces frequently use electromyography (EMG) signals. Based on previous work, feature extraction has a great deal of influence on the performance of EMG pattern recognition. Furthermore, the Deep Learning method is supposed to increase performance and not depend on feature engineering. However, directly processing raw signals will require a higher computation rate. This study proposed a new method that combines feature extraction and Deep Learning to address those issues while improving performance, reducing architecture size, and producing a more representative output. The proposed architecture employs the Transformer model as the backbone to get the correlation between elements and focus on the important information for estimating the flexion-extension of finger joint angles. This study uses experiment three of the NinaPro (Non-Invasive Adaptive Hand Prosthetics) DB5 dataset. Each experiment produces 16 Surface EMG data streams from two Myo Armbands devices representing 22 finger joint angles as output. This study compares the windowing process, feature extraction, execution time, and results with previous studies. The results show that the proposed model outperforms the previous study, from 0.957 in the previous study to become 0.970 in this study for the R-Square score. This result is obtained using 100 data points for the windowing process and Median Frequency for the best feature extraction method. © 2023

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Classification Method of Surface Defects of Aluminum Profile Based on Transfer Learning 2

Classification Method of Surface Defects of Aluminum Profile...

引用

2nd International Conference on Machine Learning and Intelligent Systems engineering, MLISE 2022

作者： Li, Bin Ren, Fuji Ni, Hongjun Kang, Xin Lv, Shuaishuai Hao, Zhuangzhuang Tokushima University Faculty Of Engineering Tokushima Japan Nantong University School Of Mechanical Engineering Nantong China University Of Electronic Science And Technology School Of Computer Science And Engineering Chengdu China

ISBN: (数字)9781665492461

ISBN: (纸本)9781665492461

In the field of industrial defect detection based on machine learning, small and unbalanced number of sample data has been a challenge to the defect classification task. In this paper, the number of aluminum profile defect pictures is increased by digital image processing methods such as rotation and flipping. Then, a VGG16 network is pre-trained on ImageNet dataset, in which the weights of feature extraction modules are transferred to the classification task of surface defects of aluminum profile. Furthermore, the classification modules of VGG16 are structurally fine-tuned, the number of neurons in the second and third fully connected layers of which is adjusted to 256 and 10 respectively. The experimental results show that the classification accuracy of 10 types of aluminum profile surface defects reaches 98.47%, and the training process is stable without any obvious overfitting phenomenon. Our results suggest that the proposed method for aluminum profile surface defect classification is smooth in feature transferring and structural fine-tuning and renders reliable results in defect classification. © 2022 IEEE.

关键词： Surface defects

来源：评论

学校读者我要写书评

暂无评论

Population-Input Memristor Circuit Based on Matrix-Friendly Genetic Algorithm

IEEE Transactions on Circuits and Systems for Artificial Int...

引用

IEEE Transactions on Circuits and Systems for Artificial Intelligence 2025年第2期2卷 174-182页

作者： Hao Chen Quan Shi Ling Chen Tingwen Huang Chuandong Li College of Electronic and Information Engineering Southwest University Chongqing China Westa College Southwest University Chongqing China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China

This paper presents the design and implementation of a novel matrix-friendly genetic algorithm (MGA) based population input memristor circuit. Selection, crossover and mutation operations can be efficiently implemented in MGA by utilizing the unique properties of memristors. The proposed circuit performs well in solving binary nonconvex function optimization problems. Through extensive simulations and comparisons with classical optimization algorithms, our method improves about 4.24% on average in exploring the optimal fitness value, which reflects the advantages of the method in finding the optimal solution. In addition, the existence of its function to visualize the image of a one-dimensional function is also found during the experimental process. The proposed circuit has good scalability and flexibility, demonstrating its potential for a wide range of applications in complex optimization tasks.

关键词： Memristors Circuits Genetic algorithms Biological cells Optimization Genetics Parallel processing Logic gates Education Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Modelling and control of a multi-product pipeline transportation process

引用

International Journal of Information technology (Singapore) 2025年 1-11页

作者： Jiménez-Cabas, Javier Piñeres-Espitia, Gabriel Rodelo-Serrano, Esteban Pamucar, Dragan Ramirez-Leon, Hermes Butt, Shariq Aziz Naz, Sumera Simic, Vladimir Computer Science and Electronic Department Universidad de La Costa Barranquilla Colombia Departamento de Ingeniería Mecánica Universidad Simón Bolívar Barranquilla Venezuela Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia Department of Industrial Engineering & Management Yuan Ze University Taoyuan Taiwan Department of Mechanics and Mathematics Western Caspian University Baku Azerbaijan Faculty of Transport and Traffic Engineering University of Belgrade Vojvode Stepe 305 Belgrade 11010 Serbia Department of Computer Science and Engineering College of Informatics Korea University Seoul 02841 South Korea School of Systems and Technology Department of Computer Science University of Management and Technology Lahore Pakistan Department of Mathematics Division of Science and Technology University of Education Lahore Pakistan

One of the most critical processes in the petroleum industry is transporting crude oil and its derivatives. Usually, it is done, due to easiness and economic aspects, through pipelines;several products, such as gasoline, kerosene, naphtha, and liquefied petroleum gas, among others, are moved in batch processes to both distribution and storage centers or transport ships. Since these transport systems transport different products, many works have focused on developing optimization strategies for scheduling these pipelines. That is, strategies that seek to optimize the use of the pipeline by establishing at what time points certain products must be transported. These strategies would be located at the planning level in the automation pyramid. In this work, on the other hand, different control strategies are proposed for a pipeline, but at the operation level. These strategies would be located at the control level, below the planning strategies in the automation pyramid. A pipeline of three pipe sections is modeled to develop the proposed control strategies, and the mathematical model is validated with actual data. The results show that, first, the proposed model approximates the actual behavior of the pipeline quite well and, second, that the combination of PID and feedforward control is an excellent alternative to implement control strategies for the operation of liquid transportation systems through pipelines. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： control strategies liquid transportation modeling of system

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：