检索结果-内蒙古大学图书馆

Sustainable Expert Systems (ICSES), International Conference on

作者： M. Varusai Mohamed Ankita Nainwal Ayshwarya B H S Kumar Dhaval Rabadiya Syed Noeman Taqui Department of Computer Application B. S. Abdur Rahman Crescent Institute Of Science And Technology (BSACIST) Chennai Tamil Nadu India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Computer science Kristu Jayanti College Bengaluru Karnataka India Department of Mechanical Engineering Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT) Nitte Karnataka India Faculty of Management studies Parul University Vadodara Gujarat India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

The rapid expansion of IoT within Industry 4.0 has heightened the risk of cyber-attacks, underscoring the need for advanced detection mechanisms. Existing cyber-attack detection systems in this context often struggle with reduced accuracy, high computational time, complexity, and elevated error rates. This study addresses these challenges by proposing an Optimized Siamese Humboldt Squid Attention Network (OSH-SqAtNet) architecture for cyber-attack detection in IoT Industry 4.0 environments. The input data, sourced from datasets like CSE-CIC-IDS2018, undergoes preprocessing via a Mixture of Conventional Fast Bilateral Filter (MC2FB) to enhance data quality. A Gold Rush Optimizer (GRO) is then employed for feature selection, isolating the most significant features to optimize classification performance. The preprocessed and optimized data are classified using the OSH-SqAtN et architecture for accurate cyber-attack detection. For secure data transmission, Rabin Fuzzy Cryptosystem assisted Elliptic Curve Cryptography (RFC-ECC) is utilized. Experimental simulations conducted on the Python platform reveal that the proposed method outperforms existing techniques, achieving higher accuracy (98%) and recall (0.993%). These results demonstrate the approach's superior efficacy and potential for advancing cybersecurity in IoT Industry 4.0.

关键词： Gold Accuracy Data preprocessing Urban areas computer architecture Feature extraction Elliptic curve cryptography Fourth Industrial Revolution Time complexity Cyberattack

来源：评论

学校读者我要写书评

暂无评论

Performance Comparison of Various Photovoltaic Module Arrangements based on Game Puzzle Theory under PSCs: Experimental Validation

Performance Comparison of Various Photovoltaic Module Arrang...

引用

2022 International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2022

作者： Pachauri, Rupendra Kumar Gupta, Pankaj Kumar Sharma, Manish Gupta, Ankur Kumar Minai, Ahmad Faiz Shashikant School of Engineering University of Petroleum and Energy Studies Eeed Dehradun India Greater Noida Institute of Technology Department of Information and Technology Greater Noida India Iimt University School of Computer Science & Application Meerut250001 India Iimt University Department of Research and Development Meerut250001 India Integral University Electrical Engineering Department Lucknow India Babu Banarasi das University Electrical Engineering Department Lucknow India

ISBN: (纸本)9781665454995

In this paper, series-parallel (SP), total-cross-tied (TCT) and game puzzle dependent photovoltaic (PV) array configurations show the comprehensive results during partial shadowing conditions (PSCs). The productivity indices are investigated with respect to power and voltage at global maximum power point (GMPP), fill factor (FF), power enhancement (PE), etc. In this paper, a MATLAB/Simulink performs to develop PV system configurations and carries the extensive investigation under the shadowing conditions. Experimental study proves the obtained the simulation results and found that the Calcu-Do-Ku game puzzle based configuration has higher results in terms of GMPP as 49.29W and 60.14W compared to the conventional PV array configurations under considered both shadowing cases. The experimental study proves the results obtained through the MATLAB/results during the similar shading circumstances. © 2022 IEEE.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Characteristics, Classification and Challenges in Searching for CEMP Stars

引用

Research in Astronomy and Astrophysics 2025年第5期 184-193页

作者： Lefeng He Xiangru Li Xiaoming Kong A-Li Luo Haifeng Yang School of Computer Science South China Normal University School of Mechanical Electrical&Information EngineeringShandong University Shandong Key Laboratory of Intelligent Electronic Packaging Testing and Application Shandong University Key Lab of Optical Astronomy National Astronomical ObservatoriesChinese Academy of Sciences University of Chinese Academy of Sciences School of Computer Science and Technology Taiyuan University of Science and Technology

The study of carbon-enhanced metal-poor (CEMP) stars is of great significance for understanding the chemical evolution of the early universe and stellar *** stars are characterized by carbon overabundance and are classified into several subclasses based on the abundance patterns of neutron-capture elements,including CEMP-s,CEMP-no,CEMP-r,and CEMP-r/*** subclasses provide important insights into the formation of thefirst stars,early stellar nucleosynthesis,and supernova ***,one of the major challenges in CEMP star research is the relatively small sample size of identified stars,which limits statistical analyses and hinders a comprehensive understanding of their ***,a series of large-scale spectroscopic survey projects have been launched and developed in recent years,providing unprecedented opportunities and technical challenges for the search and study of CEMP *** this end,this paper draws on the progress and future prospects of existing methods in constructing large CEMP data sets and offers an in-depth discussion from a technical standpoint,focusing on the strengths and *** addition,we review recent advancements in the identification of CEMP stars,emphasizing the growing role of machine learning in processing and analyzing the increasingly large data sets generated by modern astronomical *** to traditional spectral analysis methods,machine learning offers greater efficiency in handling complex data,automatic extraction of stellar parameters,and improved prediction *** these advancements,the research faces persistent challenges,including the scarcity of labeled samples,limitations imposed by low-resolution spectra,and the lack of interpretability in machine learning *** address these issues,the paper proposes potential solutions and future research directions aimed at advancing the study of CEMP stars and enhancing our understanding of their role in the chemical evolutio

关键词：

来源：评论

学校读者我要写书评

暂无评论

Two-timescale Distributed Approach to Nash Equilibrium Seeking of Euler-Lagrange Systems in Multi-cluster Nonconvex Games

引用

IEEE Transactions on Automatic Control 2025年

作者： Huang, Banghua Liu, Yang Lu, Jianquan Jiang, Yunliang Gui, Weihua Zhejiang Normal University School of Mathematical Sciences Jinhua321004 China Zhejiang Normal University Zhejiang Key Laboratory of Intelligent Education Technology and Application School of Mathematical Sciences Jinhua321004 China Zhejiang Normal University Hangzhou School of Automation Hangzhou311231 China Southeast University School of Mathematics Nanjing210096 China Zhejiang Normal University Zhejiang Key Laboratory of Intelligent Education Technology and Application School of Computer Science and Technology Jinhua321004 China Huzhou University School of Information Engineering Huzhou313000 China Central South University School of Automation Changsha410083 China

In this paper, we investigate a distributed generalized Nash equilibrium (GNE) seeking problem for multi-cluster games, where each cluster consists of multiple players. Different from most of the existing multi-cluster game studies, the multi-cluster games considered nonconvex cost functions, nonconvex (coupled) inequality constraints, and nonaffine (coupled) equality constraints. Each player in a cluster communicates and cooperates with other players based on a directed connected network to make optimal actions that minimize the cost function of their cluster. We propose a two-timescale multi-agent system (MAS) for multi-cluster nonconvex games. We further propose a two-timescale MAS in which players are formulated by Euler-Lagrange (EL) dynamics. We prove the convergence of the MAS with derived conditions to one of the local GNEs. We elaborate on a numerical example, a price-bidding problem in an electricity market, and a Nash-Cournot game to illustrate the characteristics of the proposed approach. © 1963-2012 IEEE.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Boundary-Aware Network for Abdominal Multi-Organ Segmentation

arXiv

引用

arXiv 2022年

作者： Hu, Shishuai Liao, Zehui Xia, Yong National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China

Automated abdominal multi-organ segmentation is a crucial yet challenging task in the computer-aided diagnosis of abdominal organ-related diseases. Although numerous deep learning models have achieved remarkable success in many medical image segmentation tasks, accurate segmentation of abdominal organs remains challenging, due to the varying sizes of abdominal organs and the ambiguous boundaries among them. In this paper, we propose a boundary-aware network (BA-Net) to segment abdominal organs on CT scans and MRI scans. This model contains a shared encoder, a boundary decoder, and a segmentation decoder. The multi-scale deep supervision strategy is adopted on both decoders, which can alleviate the issues caused by variable organ sizes. The boundary probability maps produced by the boundary decoder at each scale are used as attention to enhance the segmentation feature maps. We evaluated the BA-Net on the Abdominal Multi-Organ Segmentation (AMOS) Challenge dataset and achieved an average Dice score of 89.29% for multi-organ segmentation on CT scans and an average Dice score of 71.92% on MRI scans. The results demonstrate that BA-Net is superior to nnUNet on both segmentation tasks. © 2022, CC BY-NC-ND.

关键词： computerized tomography

来源：评论

学校读者我要写书评

暂无评论

Gradient Alignment Improves Test-Time Adaptation for Medical Image Segmentation

arXiv

引用

arXiv 2024年

作者： Chen, Ziyang Ye, Yiwen Pan, Yongsheng Xia, Yong National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China Research & Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen China Ningbo Institute of Northwestern Polytechnical University Ningbo China

Although recent years have witnessed significant advancements in medical image segmentation, the pervasive issue of domain shift among medical images from diverse centres hinders the effective deployment of pre-trained models. Many Test-time Adaptation (TTA) methods have been proposed to address this issue by fine-tuning pre-trained models with test data during inference. These methods, however, often suffer from less-satisfactory optimization due to suboptimal optimization direction (dictated by the gradient) and fixed step-size (predicated on the learning rate). In this paper, we propose the Gradient alignment-based Test-time adaptation (GraTa) method to improve both the gradient direction and learning rate in the optimization procedure. Unlike conventional TTA methods, which primarily optimize the pseudo gradient derived from a self-supervised objective, our method incorporates an auxiliary gradient with the pseudo one to facilitate gradient alignment. Such gradient alignment enables the model to excavate the similarities between different gradients and correct the gradient direction to approximate the empirical gradient related to the current segmentation task. Additionally, we design a dynamic learning rate based on the cosine similarity between the pseudo and auxiliary gradients, thereby empowering the adaptive fine-tuning of pre-trained models on diverse test data. Extensive experiments establish the effectiveness of the proposed gradient alignment and dynamic learning rate and substantiate the superiority of our GraTa method over other state-of-the-art TTA methods on a benchmark medical image segmentation task. Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Design of Adaptive Priority Based IoT Communication in Wireless Network

Design of Adaptive Priority Based IoT Communication in Wirel...

引用

2022 International Conference on Advanced Computing Technologies and applications, ICACTA 2022

作者： Prabha, R. Senthil, A.G. Saranya, N. Naga Arun, M. Somasundaram, K. Karthikeyan, C. Sri SaiRam Institute of Technology Dept of Electronics and Communication Engineering Chennai India Dept of Electronics and Communication Engineering Chennai India Meenakshi College of Engineering Dept of Master of Computer Application Chennai India Panimalar Institute of Technology Dept of Electronics and Communication Engineering Chennai India SIMATS Saveetha School of Engineering Dept of Institute of Information Technology Chennai India Koneru Lakshmaiah Education Foundation Department of Comuter Science and Engineering Andhra Pradesh India

ISBN: (纸本)9781665495158

Heterogeneous wireless networks of the future must be able to satisfy ever increasing demands while also making the best use of available resources. Relaying IoT contact has emerged as a novel promising approach for improving coverage, lowering power consumption, and reducing the possibility of outages. Enabling cooperation among nodes significantly increases throughput in a multi-hop heterogeneous wireless system to provide optimal IoT communication. In recent IoT communication developments, relay selection has a significant impact on network performance. IoT communication, particularly in surveillance-based wireless networks, has a number of advantages over traditional direct communication, and relay selection is widely regarded as a smart way to increase capacity efficiency. The observation of numerous relying approaches prompted the creation of a better way to solve the imprecise nature of wireless networks by using adaptive priority-based relay selection decisions. In this work, a multi-hop terminal scenario, IoT communication to develop an efficient method for selecting a better relay in each IoT device, as well as to investigate the various user options for relay selection parameters. The results is experiments using NS2 (Network simulator) and implementation of Throughput, Packet Delivery Ratio (PDR) and End-to-End Delay performance are tested. © 2022 IEEE.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

A Dual-View Fusion Network for Automatic Spinal Keypoint Detection in Biplane X-ray Images

A Dual-View Fusion Network for Automatic Spinal Keypoint Det...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Dandan Zhou Lijun Guo Rong Zhang Xiuchao He Qiang Wang Jianhua Wang The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China The Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China The Department of Radiology The Affiliated Hospital of Medicine School of Ningbo University Ningbo China

Accurate keypoint detection in medical images of the spine is critical for the assessment, diagnosis, treatment planning, and clinical investigation of spinal deformities. However, due to severe occlusions of spinal structures in lateral X-ray images, accurate keypoint detection can be hardly achieved in lateral X-ray images based on single-view information. Thus, methods based on both the anterior-posterior (AP) and lateral (LAT) X-ray image views have been proposed to alleviate occlusion problems and achieve better keypoint detection performance. Although some progress has been made with these dual-view methods, they do not effectively exploit a priori knowledge of the spine and hence cannot adequately account for the structural correlation of the vertebrae across views. In this paper, a new dual-view fusion network (DVFNet) framework is proposed for keypoint detection in spinal X-ray images. This framework obtains structural correlations between AP and LAT views of the spine based on a priori spine knowledge represented by high-level semantic features. Meanwhile, the proposed framework combines local and global features extracted respectively by a local subnetwork and a global subnetwork. On the one hand, the local subnetwork is constructed as an enhanced codec structure based on both the AP and LAT views. This subnetwork is trained to output local features that contain both joint semantic features of the two views and independent fine-grained features of each individual view. This scheme leads to accurate keypoint estimation locally. On the other hand, the global subnetwork utilizes a self-attention mechanism to extract view-specific global features based on either the AP view or the LAT view in order to eliminate ambiguity, and reduce confusion on keypoint locations. Further, we propose a weighted feature fusion (WFF) module for adaptive fusion of the local and global features. We evaluated the DVFNet model on a private dataset and found that our proposed metho

关键词：

来源：评论

学校读者我要写书评

暂无评论

A cross Transformer for image denoising

arXiv

引用

arXiv 2023年

作者： Tian, Chunwei Zheng, Menghua Zuo, Wangmeng Zhang, Shichao Zhang, Yanning Lin, Chia-Wen School of Software Northwestern Polytechnical University Shaanxi Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Xi’an710129 China School of Computer Science and Technology Harbin Institute of Technology Heilongjiang Harbin150001 China Peng Cheng Laboratory Shenzhen518055 China School of Computer Science and Engineering Central South University Hunan Changsha410083 China School of Computer Science Northwestern Polytechnical University Shaanxi Xi’an710129 China Department of Electrical Engineering The Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan

Deep convolutional neural networks (CNNs) depend on feedforward and feedback ways to obtain good performance in image denoising. However, how to obtain effective structural information via CNNs to efficiently represent given noisy images is key for complex scenes. In this paper, we propose a cross Transformer denoising CNN (CTNet) with a serial block (SB), a parallel block (PB), and a residual block (RB) to obtain clean images for complex scenes. A SB uses an enhanced residual architecture to deeply search structural information for image denoising. To avoid loss of key information, PB uses three heterogeneous networks to implement multiple interactions of multi-level features to broadly search for extra information for improving the adaptability of an obtained denoiser for complex scenes. Also, to improve denoising performance, Transformer mechanisms are embedded into the SB and PB to extract complementary salient features for effectively removing noise in terms of pixel relations. Finally, a RB is applied to acquire clean images. Experiments illustrate that our CTNet is superior to some popular denoising methods in terms of real and synthetic image denoising. It is suitable to mobile digital devices, i.e., phones. Codes can be obtained at https://***/hellloxiaotian/CTNet. Copyright © 2023, The Authors. All rights reserved.

关键词： Image denoising

来源：评论

学校读者我要写书评

暂无评论

IIESC-Net: Incorporating Implicit and Explicit Structural Constraints for Hip Joint Landmark Detection in pelvic X-ray

IIESC-Net: Incorporating Implicit and Explicit Structural Co...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jing Zhang Lijun Guo Lixin Ni Xiuchao He Jianhua Wang Rong Zhang The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China The Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China The Department of Radiology The Affiliated Hospital of Medicine School of Ningbo University Ningbo China

The hip joint, a vital weight-bearing joint in the human body, is susceptible to various hip-related diseases. The accurate identification of anatomical landmarks in the hip joint is essential for both disease diagnosis and surgical planning. However, these landmarks are often inconspicuous in X-ray images, where irrelevant background interference increases detection difficulty. In this study, we proposed an IIESC-Net model that combined local and global features, enabling a hierarchical understanding of the implicit structural characteristics of the hip joint. Additionally, drawing from domain expertise based on the explicit physiological structure of the hip joint, we designed a Hip Morphology-Aware loss function to constrain large landmark errors through the application of high-confidence landmarks with robust distinctive identification, thereby achieving accuracy in automatic detection. Furthermore, we constructed a dataset comprising of 843 pelvic X-ray images. The experimental results demonstrated a substantial enhancement in hip joint landmark detection accuracy attributed to the proposed IIESC-Net. This innovation established state-of-the-art performance, notably excelling in attaining heightened successful detection rates under stringent error tolerance. This achievement has profound practical implications for clinical applications.

关键词：

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：