检索结果-内蒙古大学图书馆

An improved KPLS-KELM method for breast cancer detection 9

An improved KPLS-KELM method for breast cancer detection

9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

作者： Bacha, Sawssen Taouali, Okba Liouane, Noureddine National Engineering School of Monastir Research Laboratory of Automation Signal Processing and Image Monastir5019 Tunisia University of Tabuk Faculty of Computers and Information Technology Department of Computer Engineering Tabuk Saudi Arabia

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

The conception of a computer-Aided Diagnosis system (CAD) using Artificial Intelligence (AI) is a hot topic in the domain of medical diagnosis. Recently, many approaches have been developed. In the proposed work, a novel classification technique from mammograms based on Kernel Extreme Learning Machine (KELM) and Kernel Partial Least Square (KPLS) method is introduced. The suggested algorithm first used the KPLS algorithm to extract features from the images. The extracted characteristics were then sent to the KELM classifier. In order to improve the generalization of the proposed approach, the cross-validation strategy was used. The simulation results were tested on the Mammographic Image Analysis Society (MIAS) dataset and measured using accuracy, F score, sensitivity, and specificity analysis. These results were compared to existing approaches tested on the same dataset and it was observed that the proposed work is the most efficient. © 2022 IEEE.

关键词： Mammography

来源：评论

学校读者我要写书评

暂无评论

Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

引用

IET Control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET Control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Closed loop systems

来源：评论

学校读者我要写书评

暂无评论

Transformer-Based Single-Cell Language Model:A Survey

引用

Big Data Mining and Analytics 2024年第4期7卷 1169-1186页

作者： Wei Lan Guohang He Mingyang Liu Qingfeng Chen Junyue Cao Wei Peng Guangxi Key Laboratory of Multimedia Communications and Network Technology School of ComputerElectronic and InformationGuangxi UniversityNanning 530004China School of Computer and Electronic Information Guangxi UniversityNanning 530004China College of Life Science and Technology Guangxi UniversityNanning 530004China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China

The transformers have achieved significant accomplishments in the natural language processing as its outstanding parallel processing capabilities and highly flexible attention *** addition,increasing studies based on transformers have been proposed to model single-cell *** this review,we attempt to systematically summarize the single-cell language models and applications based on ***,we provide a detailed introduction about the structures and principles of ***,we review the single-cell language models and large language models for single-cell data ***,we explore the datasets and applications of single-cell language models in downstream tasks,such as batch correction,cell clustering,cell type annotation,gene regulatory network inference,and perturbation ***,we discuss the challenges of single-cell language models and provide promising research *** hope this review will serve as an up-to-date reference for researchers who are interested in the direction of single-cell language models.

关键词： language model transformers deep learning single-cell data

来源：评论

学校读者我要写书评

暂无评论

Effects of the Flatness Network Parameter Threshold on the Performance of the Rectified Linear Unit Memristor-Like Activation Function in Deep Learning

引用

SN computer Science 2024年第8期5卷 1-10页

作者： Tchepgoua Mbakop, Marcelle Mboupda Pone, Justin Roger Chassem Kamdem, Priva Kengne, Romanic Research Unit of Condensed Matter Electronics and Signal Processing (RU-MACETS) Department of Physics Faculty of Science University of Dschang P. O. Box 67 Dschang Cameroon Research Unit of Automation and Applied Computer (RU-AIA) Electrical Engineering Department of IUT-FV University of Dschang P.O. Box 134 Bandjoun Cameroon Research Unit of Fundamental Computer Sciences and Artificial Intelligence (RU-FCSAI) Department of Computer Sciences Faculty of Science University of Dschang P. O. Box 67 Dschang Cameroon

In this contribution, we improve of the performance of the Rectified Linear Unit Memristor Like Activation Function with the implication to help training process of CNN without a lot of epochs by computing the best value of the flatness network parameter (p). In this regards the flatness network parameter threshold (p) has been investigated and a good performance of the activation function has been discovered at p = 4.5. We firstly used the MNIST and the CIFAR-10 datasets to trained and test the Alex-Net architecture model of convolutional neural network (CNN) and we showed better performances of Rectified Linear Unit Memristor-like Activation Function compared to those of the literature. We noticed that the performance of Alex-Net also improved and the better performance was recorded when p = 4.5 with 99.50%, 99.25%, 98.81% for training, validation and testing accuracy respectively when using the MNIST. These results open the outcome to reduce the training time of neural networks when this activation function is used. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Activation function Artificial intelligence Deep learning Flatness network parameter threshold Memristive windows function Neural network

来源：评论

学校读者我要写书评

暂无评论

Editorial: Modeling and application of computational intelligence in sustainable energy systems

引用

Frontiers in Energy Research 2025年 13卷

作者： Wang, Yirui Gao, Shangce Yu, Yang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Faculty of Engineering University of Toyama Toyama Japan College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Jiangsu Nanjing China

In recent years, the study of computational intelligence in sustainable energy systems has gained increasing attention due to its effectiveness and sophistication. Sustainable energy systems are designed, modeled and optimized by various computational intelligence methods, such as evolutionary computation and machine learning. These methods show the great value and significant contributions in energy research. As researchers continue to explore this area, new insights are being uncovered that have the potential to improve the role and significance of computational intelligence methods in modeling and optimizing sustainable energy systems. In this Research Topic, several studies have contributed significantly to the advancement of computational intelligence in sustainable energy systems. In [1], this study focused on optimizing the configuration and scheduling of integrated energy systems with flexible load resources to maximize energy efficiency and reduce environmental impact. By using Weibull and Beta distribution models to account for uncertainties in wind and solar power, and proposing an enhanced Kepler Optimization Algorithm (EKOA), the approach improved search scope and efficiency. A case study in southeastern China demonstrated that this method reduced energy curtailment and costs, while enhancing renewable energy use. Despite the success, the study only considered hydrogen for single-use and did not explore market benefits, leaving room for future research on hydrogen demand response and market integration. In [2], multi-energy microgrids (MEM) integrate various energy sectors to enhance renewable energy use while maintaining balance. This study analyzed the technical challenges of increasing renewable penetration, using an artificial neural network-based model for solar power forecasting, integrated with the EnergyPLAN tool. A case study on Norway revealed that combined heat and power plants hindered renewable integration, while heat pumps enhanced it. A

关键词： aritificial neural networks computational intelligence evolutionary compuation machine learning metaheuristics optimizaiton algorithms sustainable energy systems

来源：评论

学校读者我要写书评

暂无评论

Classification of sprott chaotic systems via projection of the attractors using deep learning methods

引用

The European Physical Journal Special Topics 2024年 1-17页

作者： Akgul, Akif Deniz, Emre Emin, Berkay Çizmeci, Hüseyin Alaca, Yusuf Akmeşe, Ömer Faruk Özdem, Selim Department of Computer Engineering Faculty of Engineering Hitit University Corum Turkey Department of Electronics and Automation Osmancık Omer Derindere Vocational School Hitit University Corum Turkey Department of Computer Technologies Vocational School of Technical Sciences Hitit University Corum Turkey Department of Electronics and Automation Alaca Avni Celik Vocational School Hitit University Corum Turkey

This study uses deep learning methods to classify the projection of the attractor’s images of five different chaotic systems. The chaotic systems addressed in the research are Sprott C, Sprott F, Sprott G, Sprott H, and Sprott M. A dataset was created for classification using the projection of attractors of these five different chaotic systems. This dataset contains time series images, and the graphs are generated based on initial conditions, Runge–Kutta 4 step size, and time length. Deep learning methods such as ResNet50, ResNet50V2, VGG19, InceptionV3, MobileNetV2, and VGG16 have been utilized for classification. This study's classification accuracy varies between 91.6% and 99.9%, depending on the problem. Therefore, this research accurately determines which chaotic system a projection of the attractors graphic image belongs to. This high accuracy demonstrates the usability of this model in analyzing chaotic systems in real-world applications. Such accuracies can be considered a powerful tool in analyzing industrial systems or other systems with complex structures. This work successfully uses deep learning methods for classifying chaotic systems. Such research could be an important step toward understanding and managing complex systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

引用

IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

来源：评论

学校读者我要写书评

暂无评论

Towards a real-time control of robotic ultrasound using haptic force feedback

Towards a real-time control of robotic ultrasound using hapt...

引用

作者： Schreiter, J. Semshchikov, V. Hanses, M. Elkmann, N. Hansen, C. University of Magdeburg Faculty of Computer Science & Research Campus Stimulate Magdeburg Germany University of Magdeburg Faculty of Electrical Engineering and Information Technology Magdeburg Germany Fraunhofer Institute for Factory Operation and Automation Iff Magdeburg Germany

Ultrasound is a widely used imaging technique and is appreciated for its non-invasiveness, absence of radiation, widespread availability, and compact equipment. Ergonomic difficulties in manual handling of the probe could be enhanced by a robotic controlled ultrasound. The paper addresses the development of such a system which enables remote operation of a ultrasound probe and includes haptic force feedback as well as video conferencing components for visual feedback. The development process followed a user-centered approach by investigating needs of potential end-users. Preliminary results demonstrated the functionality of the developed system for generating medical image data under laboratory conditions. © 2022 by Walter de Gruyter Berlin/Boston.

关键词： Probes

来源：评论

学校读者我要写书评

暂无评论

Exploring the Possibility of Improving the Design of a Fuel Level Measuring Device Using a Compensating Sensor 22

Exploring the Possibility of Improving the Design of a Fuel ...

引用

22nd International Symposium on Electrical Apparatus and Technologies, SIELA 2022

作者： Simeonov, Stanislav Gospodinova, Ekaterina Assen Zlatarov University Department of Computer Systems and Technologies Burgas8010 Bulgaria Technical University of Sofia Faculty of Engineering and Pedagogy-Sliven Department of Electrical Engineering Automation and Information Technology Sliven8800 Bulgaria

ISBN: (数字)9781665411394

ISBN: (纸本)9781665411394

The choice of systems for level measurements determined by the properties of the fluid, the design features of the tank, the type of level reading and other factors. This article discusses the results of the experimental study of two automated measuring systems and analyzes the errors in measuring the level of light fuels in the laboratory and real conditions. After research in this work, we have proposed an improvement in the construction of the level measuring system, width a compensating sensor is used. © 2022 IEEE.

关键词： Fuels

来源：评论

学校读者我要写书评

暂无评论

A Novel Attention-based Explainable Deep Learning Framework Towards Medical Image Classification 7

A Novel Attention-based Explainable Deep Learning Framework ...

引用

7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Muoka, Gladys W. Yi, Ding Ukwuoma, Chiagoziem Chima Martin, Moindi Duke Aydin, Ahmet Arif Al-Antari, Mugahed A. University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China Chengdu University of Technology Sichuan College of Nuclear Technology and Automation Engineering Chengdu China Unicaf University Lilongwe Department of Computer Science Lilongwe Malawi Inönü University Faculty of Engineering Department of Computer Engineering Turkey Sejong University College of Software & Convergence Technology Daeyang AI Center Department of Artificial Intelligence Seoul Korea Republic of

ISBN: (纸本)9798350383065

Deep learning applications for medical image classification have shown remarkable promise, particularly incorporating attention-based neural networks. This is particularly relevant in medical imaging, where the integration of Artificial Intelligence assists with various imaging tasks, including classification, segmentation, and detection. Deep learning is revolutionizing medical research and playing a significant role in advancing personalized clinical treatment. However, the lack of interpretability in these models presents a significant obstacle to their adoption in clinical practice. Therefore, there is a growing need for a comprehensive understanding of artificial intelligence systems and their internal mechanisms, capabilities, and limitations, which is the focus of the field of explainable AI. This study proposes a novel attention-based explainable deep learning framework for medical image classification tasks, including Covid-19, breast cancer (BreakHis), lung cancer (LC2500), and Retinal optical coherence tomography (OCT). The proposed framework recorded overall accuracies of 98% (Covid-19 Radiography), 95% (BreakHis), 99.8% (LC2500), and 95%(OCT). For visual analysis of the outcomes, we employ and use the LIME, SHAP, and ELI-5 to analyze the achieved results. The study's primary goal is to bridge the gap between the high performance achieved by attention-based models and the necessity for transparency and interpretability in medical image diagnostics. © 2023 IEEE.

关键词： Optical tomography

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：