检索结果-内蒙古大学图书馆

11th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2024

作者： Inokuchi, Yuto Gonzalez, Pedro Henrique Aritsugi, Masayoshi Mendonca, Israel Kumamoto University Graduate School of Science and Technology Kumamoto Japan Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan

ISBN: (纸本)9798350367300

In this paper, we aim to reduce the number of nodes from Graph Neural Networks (GNNs), thereby simplifying models and reducing computational costs. GNNs are highly effective for various tasks, such as prediction, classification, and clustering, due to their ability to learn node and edge attributes and relationships, and they have been utilized for intelligent transportation systems recently by converting sensor networks into graph structures. Deep spatio-temporal neural networks, including Spatio-Temporal Graph Convolutional Networks (STGCNs), capture spatial and temporal dependencies, making them suitable for traffic speed forecasting, traffic demand prediction, and travel time estimation. Despite their success, GNNs face challenges in industrial applications due to significant memory usage and time consumption. In this paper, we propose a new approach to node reduction that outperforms existing methods in computational efficiency. Our experiments on two real-world traffic datasets demonstrate that using the heuristic and edge information to reduce nodes can cut computation time of optimization up to 95% and, by eliminating noise, can even enhance prediction accuracy. © 2024 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Low-temperature spin Seebeck effect in nonmagnetic vanadium dioxide

引用

Physical Review B 2024年第2期110卷 024415-024415页

作者： Renjie Luo Tanner J. Legvold Liyang Chen Henry Navarro Ali C. Basaran Deshun Hong Changjiang Liu Anand Bhattacharya Ivan K. Schuller Douglas Natelson Department of Physics and Astronomy Applied Physics Graduate Program Rice Quantum Institute Department of Physics and Center for Advanced Nanoscience Materials Science Division Department of Electrical and Computer Engineering Department of Materials Science and NanoEngineering

The spin Seebeck effect (SSE) is sensitive to thermally driven magnetic excitations in magnetic insulators. Vanadium dioxide in its insulating low-temperature phase is expected to lack magnetic degrees of freedom, as vanadium atoms are thought to form singlets upon dimerization of the vanadium chains. Instead, we find a paramagnetic SSE response in VO2 films that grows as the temperature decreases below 50 K. The field and temperature-dependent SSE voltage is qualitatively consistent with a general model of paramagnetic SSE response and inconsistent with triplet spin transport. Quantitative estimates find a spin Seebeck coefficient comparable in magnitude to that observed in strongly magnetic materials. The microscopic nature of the magnetic excitations in VO2 requires further examination.

关键词： Spin Seebeck effect Paramagnets Strongly correlated systems

来源：评论

学校读者我要写书评

暂无评论

Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective 41

Feature Distribution on Graph Topology Mediates the Effect o...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Lee, Soo Yong Kim, Sunwoo Bu, Fanchen Yoo, Jaemin Tang, Jiliang Shin, Kijung Kim Jaechul Graduate School of Artificial Intelligence KAIST Daejeon Korea Republic of School of Electrical Engineering KAIST Daejeon Korea Republic of Department of Computer Science and Engineering Michigan State University Michigan United States

How would randomly shuffling feature vectors among nodes from the same class affect graph neural networks (GNNs)? The feature shuffle, intuitively, perturbs the dependence between graph topology and features (A-X dependence) for GNNs to learn from. Surprisingly, we observe a consistent and significant improvement in GNN performance following the feature shuffle. Having overlooked the impact of A-X dependence on GNNs, the prior literature does not provide a satisfactory understanding of the phenomenon. Thus, we raise two research questions. First, how should A-X dependence be measured, while controlling for potential confounds? Second, how does A-X dependence affect GNNs? In response, we (i) propose a principled measure for A-X dependence, (ii) design a random graph model that controls A-X dependence, (iii) establish a theory on how A-X dependence relates to graph convolution, and (iv) present empirical analysis on real-world graphs that align with the theory. We conclude that A-X dependence mediates the effect of graph convolution, such that smaller dependence improves GNN-based node classification. Copyright 2024 by the author(s)

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Enhancing Energy Efficiency in IoT Networks Through Fuzzy Clustering and Optimization

引用

Mobile Networks and Applications 2024年第5期29卷 1594-1617页

作者： Javadpour, Amir Sangaiah, Arun Kumar Zaviyeh, Hadi Ja’fari, Forough Department of Computer Science and Technology Harbin Institute of Technology Shenzhen China ADiT-Lab Electrotechnics and Telecommunications Department Instituto Politécnico de Viana do Castelo Porto4900-347 Portugal International Graduate School Artificial Intelligence National Yunlin University of Science and Technology Douliu Taiwan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon School of Economics and Statistics Guangzhou University Guangzhou510006 China Department of Computer Engineering Sharif University of Technology Tehran Iran

Wireless Sensor and Internet of Things (WSIoT) networks are characterized by nodes scattered throughout the environment, posing a significant challenge when it comes to battery replacement. The task of developing an algorithm that effectively reduces energy consumption in IoT networks through the utilization of artificial intelligence and fuzzy logic is a formidable one. Heuristic algorithms emerge as valuable tools in this context, capable of swiftly addressing non-deterministic polynomial problems or approximating optimal solutions with remarkable accuracy. Conversely, mathematical optimization approaches often falter due to their sluggishness or inefficiency, rendering them less suited for the dynamic demands of IoT networks. This study embarks on a novel approach, leveraging the synergy of fuzzy clustering to intricately connect sensors to the network and particle optimization to approximate the initial values of head clusters within the realm of WSIoT. A comprehensive evaluation of our proposed strategy is meticulously conducted through extensive simulations utilizing the NS2 simulator. In this evaluation, we distinguish our algorithm from existing methods, including IoTbWSN and REcsIoT. The results of this comparative analysis are illuminating. In contrast to other methodologies, our proposed approach demonstrates a notable 9.57% improvement in network throughput and a substantial 8.47% reduction in energy consumption. This signifies a remarkable leap forward in the quest to address the challenges posed by energy consumption and battery replacement within the complex landscape of IoT networks. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2023.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer 24

Predicting Microsatellite Instability from Histology Images ...

引用

24th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2024

作者： Chen, Yun-Chi Chao, Tung Phandita, Wimaya Nitya Sun, Tzu-Yu Wang, Huai-Zhi Hsieh, Yi-Hsien Hsu, Le-Yin Lin, Che Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan NTU Data Science Degree Program Taipei Taiwan NTU Department of Electrical Engineering Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan NTU Smart Medicine and Health Informatics Program Taipei Taiwan

ISBN: (纸本)9798331518622

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

MOCBOA:Multi-Objective Chef-Based Optimization Algorithm Using Hybrid Dominance Relations for Solving engineering Design Problems

引用

computer Modeling in engineering & sciences 2025年第4期143卷 967-1008页

作者： Nour Elhouda Chalabi Abdelouahab Attia Abdulaziz S.Almazyad Ali Wagdy Mohamed Frank Werner Pradeep Jangir Mohammad Shokouhifar Computer Science Department University of M’silaIchebiliaM’sila28000Algeria Computer ScienceDepartment Mohamed El Bachir El IbrahimiUniversity of Bordj BouArreridjBordj BouArreridj34000Algeria Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan Faculty of Mathematics Otto-von-Guericke UniversityMagdeburg39016Germany University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Electrical and Computer Engineering Shahid Beheshti UniversityTehran14399Iran DTU AI and Data Science Hub(DAIDASH) Duy Tan UniversityDa Nang550000Vietnam

Multi-objective optimization is critical for problem-solving in engineering,economics,and *** study introduces the Multi-Objective Chef-Based Optimization Algorithm(MOCBOA),an upgraded version of the Chef-Based Optimization Algorithm(CBOA)that addresses distinct *** approach is unique in systematically examining four dominance relations—Pareto,Epsilon,Cone-epsilon,and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto *** comparison investigation,which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering,mechanical design,and power systems,reveals that the dominance approach used has a considerable impact on the key optimization measures such as the hypervolume *** paper provides a solid foundation for determining themost effective dominance approach and significant insights for both theoretical research and practical applications in multi-objective optimization.

关键词： Multi-objective optimization chef-based optimization algorithm(CBOA) pareto dominance epsilon dominance cone-epsilon dominance strengthened dominance

来源：评论

学校读者我要写书评

暂无评论

A Novel Miniaturized Reconfigurable Microstrip Antenna Based Printed Metamaterial Circuitries for 5G Applications

引用

Progress In Electromagnetics Research C 2022年 120卷 1-10页

作者： Al-Khaylani, Hayder H. Elwi, Taha A. Ibrahim, Abdullahi A. Electrical and Computer Engineering Department Graduate School of Science Altinbas University Istanbul Turkey Department of Communication Engineering Al-Ma’moon University College Baghdad Iraq Baghdad Quarter Iraq

A novel reconfigurable sub-6 GHz microstrip patch antenna operating at three resonant frequencies 3.6, 3.9, and 4.9 GHz is designed for 5G applications. The proposed antenna is constructed from metamaterial (MTM) array with a matching circuit printed around a printed strip line. The antenna is excited with a coplanar waveguide to achieve an excellent matching over a wide frequency band. The proposed antenna shows excellent performance in terms of S11, gain, and radiation pattern that are controlled well with two photo resistance. The proposed antenna shows different operating frequencies and radiation patterns after changing the of photo resistance status. The main antenna novelty is achieved by splitting the main lobe that tracks more than one user at the same resonant frequency. Nevertheless, the main radiation lobe can be steered to the desired location by controlling the surface current motion using two varactor diodes on a matching circuit. © 2022, Electromagnetics Academy. All rights reserved.

关键词： Metamaterials

来源：评论

学校读者我要写书评

暂无评论

Polymethyl Methacrylate-based Light Collector for Enhanced Indoor Visible Light Communication

Polymethyl Methacrylate-based Light Collector for Enhanced I...

引用

Optics and Photonics Conference (SBFoton IOPC), SBFoton International

作者： David Esteban Farfán-Guillén João Pedro Duarte Jankosz Neri Volpato Alexandre de Almeida Prado Pohl Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University Technology-Parana Curitiba Brazil Graduate Program in Mechanical Engineering and Material Science Federal University Technology-Parana. Curitiba Brazil

A new polymethyl methacrylate-based light collector has been designed and fabricated with additive manufacturing to optimize the efficiency of VLC systems. It enhances the area of detection, leading to a ~ 1.9x increa... 详细信息

ISBN: (数字)9798350388176

ISBN: (纸本)9798350388183

关键词： Optical device fabrication Optical variables measurement Three-dimensional printing Optics Optical receivers Optical sensors Reliability Visible light communication Testing Photonics

来源：评论

学校读者我要写书评

暂无评论

Real-Time Hand Gesture Recognition for Humanoid Robot Control Using Python CVZone 7th

Real-Time Hand Gesture Recognition for Humanoid Robot Contro...

引用

7th International Conference on Smart City Applications, SCA 2022

作者： Baihaqi, Muhammad Yeza Vincent Simatupang, Joni Welman Graduate Institute of Automation and Control College of Engineering National Taiwan University of Science and Technology Taipei Taiwan School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Study Program of Electrical Engineering President University Bekasi Indonesia

ISBN: (纸本)9783031268519

Humanoid robot is able to mimic repetitive activities done by human. By having them, humans can focus on tasks that require extra focus, while leaving the simple one to be done by humanoid robot. To extend the functionality of the 3D-printed upper-body humanoid robot, a camera along with a machine learning algorithm is implemented. In this case, their responses can be categorized based on the gesture it sees. In this paper, the authors evaluate the performance of an upper-body humanoid robot that implements CVZone. The method of evaluation is conducted under three different distances, and each distance has three different brightness levels. It is found that the success rate is highest at the shortest distance which is 50 cm, and under medium-lighted environment. As the distance increases, the hand gesture gets harder to differentiate. At the same time, low or high brightness environment makes the image that contain hand gesture hard to interpret, thus lowering the success rate. Finally, hand gesture that involves third and little finger has the lowest success rate of 75%, while the movement that involves three fingers simultaneously has the second lowest success rate of 80.9%. Meanwhile, simple hand gesture such as clenched-fist or lifting a thumb has 100% success rate under all condition. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Anthropomorphic robots

来源：评论

学校读者我要写书评

暂无评论

A motion-level-aware denoising framework for x-ray fluoroscopic images

A motion-level-aware denoising framework for x-ray fluorosco...

引用

Medical Imaging 2023: Physics of Medical Imaging

作者： Jo, Geonhui Jang, Minhee Jeon, Sun-Young Kim, Wonjin Choi, Jang-Hwan Department of Computer Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of

ISBN: (纸本)9781510660311

Fluoroscopy in a low-dose tube output is used to reduce the damage associated with radiation exposure. However, lowering the radiation dose inevitably increases random noise in x-ray images, resulting in poor diagnostic image quality, which requires noise reduction for accurate diagnosis. Also, in the case of non-static objects, the image is blurred due to motion. The most-used denoiser with a recursive filter (RF) preserves details well when applied to temporal data, but it is vulnerable to motion blur. Existing convolutional neural network (CNN)-based algorithms with single-frame input cannot use the temporary context, and others with multi-frame input are good for motion detection but poor for detail preservation. Therefore, we propose a motion-level-aware denoising framework to combine the results of RF- and CNN-based algorithms depending on the pixel-wise magnitude of motion to complement each other. The data we use are fluoroscopy images taken in continuous time, and we aim at many-to-one so that one frame is denoised by considering sequential frames. Also, since both RF- and CNN-based algorithms used in our architecture are many-to-one methods, they can consider spatiotemporal information. In the multi-frame input, the difference in intensity of each pixel between frames is calculated to obtain a moving map. Depending on the factor value from the moving map, the final image is obtained by reflecting the outputs of the RF- and CNN-based algorithms. If the factor value is high, the pixel intensity of the final image is like the CNN-based output, which is good for motion detection, and vice versa, it more reflects the intensity of RF output, which is excellent in perceptual quality. Therefore, it prevents motion blur and does not over-smooth microdetails, such as bones and muscles. The results show that combining the two outputs together records higher peak signal-to-noise ratio (PSNR) and has better perceptual quality for diagnosis than using only one method. F

关键词： Deep learning

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：