检索结果-内蒙古大学图书馆

Optimal Design and Mechanical Simulation of Rubber bushing with Convex Hull Structure Based on Bionics

Journal of Bionic engineering 2023年第5期20卷 2018-2029页

作者： Ce Liang Min Li Jicai Liang Shaoqiang Wang Qigang Han Yi Li Key Laboratory of Automobile Materials Ministry of Educationand College of Materials Science and EngineeringJilin UniversityChangchun130025China Roll Forging Research Institute Jilin UniversityChangchun130025China School of Computer Science and Technology Changchun UniversityChangchun130022China

Inspired by the safe landing of cats falling from high altitudes,a bionic flexible rubber bushing structure is proposed and its motion characteristics are systematically studied to explore its potential application in the suppression of *** convex hull structure on the bushing surface is abstracted from the cat’s claw pad,and the hyper-viscoelastic model is selected as the constitutive model of the rubber *** addition,the design with the best vibration damping effect is finally obtained by reasonably adjusting the amount of radial compression and distribution of bionic ***,under the same conditions,the test results of the dynamic characteristics of the bushing verify the accuracy of the simulation *** results show that the convex hull bionic structure designed in this paper can effectively change the motion characteristics of the rubber bushing under various working conditions,which provides new inspiration or potential possibility for the design of rubber bushing in the future.

关键词： Rubber bushing Bionic design Finite element analysis Vibration isolator Radial compression

来源：评论

学校读者我要写书评

暂无评论

An image segmentation fusion algorithm based on density peak clustering and Markov random field

引用

Multimedia Tools and Applications 2024年第37期83卷 85331-85355页

作者： Feng, Yuncong Liu, Wanru Zhang, Xiaoli Zhu, Xiaoyan College of Computer Science and Engineering Changchun University of Technology Jilin Changchun130012 China Artificial Intelligence Research Institute Changchun University of Technology Jilin Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Jilin Changchun130012 China College of Computer Science and Technology Jilin University Jilin Changchun130012 China

Image segmentation is a crucial task in the field of computer vision. Markov random fields (MRF) based image segmentation method can effectively capture intricate relationships among pixels. However, MRF typically requires an initial labeling field, and the number of classifications needs to be manually selected. To tackle these issues, we propose a novel medical image segmentation algorithm based on density peak clustering (DPC) and Markov random fields. Firstly, we improve DPC to make it applicable to grayscale images, named GIDPC. In the GIDPC method, local gray density and gray bias are defined to enable the automatic determination of the number of classifications. Then, GIDPC and MRF are combined to achieve image segmentation. Furthermore, a segmentation fusion method is employed to enhance the accuracy of image segmentation. We conduct comparison experiments on the whole brain atlas image library. Our proposed algorithm achieves high average values in uniformity measure, accuracy, precision and sensitivity, respectively. Experimental results demonstrate that the proposed algorithm outperforms other image segmentation methods. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Real-time all-frequency global llumination with radiance caching

引用

Computational Visual Media 2024年第5期10卷 923-936页

作者： Youxin Xing Gaole Pan Xiang Chen Ji Wu Lu Wang Beibei Wang School of Software Shandong UniversityJinan 250101China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China

Global illumination(GI)plays a crucial role in rendering realistic results for virtual exhibitions,such as virtual car *** scenarios usually include all-frequency bidirectional reflectance distribution functions(BRDFs),although their geometries and light configurations may be *** allfrequency BRDFs in real time remains challenging due to the complex light *** approaches,including precomputed radiance transfer,light probes,and the most recent path-tracing-based approaches(ReSTIR PT),cannot satisfy both quality and performance requirements ***,we propose a practical hybrid global illumination approach that combines ray tracing and cached GI by caching the incoming radiance with *** approach can produce results close to those of ofline renderers at the cost of only approximately 17 ms at runtime and is robust over all-frequency *** approach is designed for applications involving static lighting and geometries,such as virtual exhibitions.

关键词： real-time global illumination all-frequency BRDFs Haar wavelets radiance caching

来源：评论

学校读者我要写书评

暂无评论

Image Guidance Encoder-Decoder Model in Image Captioning and Its Application

IAENG International Journal of Computer Science

引用

IAENG International Journal of computer science 2024年第9期51卷 1385-1392页

作者： Yang, Zhen Zhou, Ziwei Wang, Chaoyang Xu, Liang School of Applied Technology University of Science and Technology Liaoning Anshan China School of Computer and Software Engineering University of Science and Technology Liaoning Anshan China School of Computer and Software Engineering University of Science and Technology Liaoning Anshan China

This paper introduces a new network model - the Image Guidance Encoder-Decoder Model (IG-ED), designed to enhance the efficiency of image captioning and improve predictive accuracy. IG-ED, a fusion of the convolutional network VGGNet-16 and the long short-term memory network (LSTM), is designed based on the encoder-decoder structure. The image captioning performance sees significant enhancements when leveraging the IG-ED network model. The network training process unfolds in a series of steps. Initially, the input image undergoes convolution via the VGGNet-16 network, producing a 512-dimensional vector. Concurrently, each word in the image's caption is encoded to generate a corresponding 512-dimensional vector consistent with the image feature dimension. These two vectors form the input for the decoding process. Subsequently, the vectors are fed into the redesigned fusion LSTM (F-LSTM) network at different time steps to gradually train the parameters of the IG-ED framework. The training process is completed by utilizing a loss function for determining convergence. Evaluation of the IG-ED model's performance is conducted using CIDEr and seven other evaluation metrics on the MSCOCO 2014 dataset. The results exhibit substantial improvements over the "Adaptive Attention Mode" network and "Neural Talk" network. Additionally, the parameter count of the IG-ED architecture is significantly reduced compared to the "Adaptive Attention Mode" network, leading to decreased computational resource requirements and enabling edge computing on the neural network. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Fake Face Detection Based on Fusion of Spatial Texture and High-Frequency Noise

引用

Chinese Journal of Electronics 2025年第1期34卷 212-221页

作者： Dengyong Zhang Feifan Qi Jiahao Chen Jiaxin Chen Rongrong Gong Yuehong Tian Lebing Zhang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Changsha University of Science and Technology School of Computer and Communication Engineering Changsha University of Science and Technology Changsha Social Work College Changkuangao Beijing Technology Co. Ltd. School of Computer and Artificial Intelligence Huaihua University

The rapid development of the Internet has led to the widespread dissemination of manipulated facial images, significantly impacting people's daily lives. With the continuous advancement of Deepfake technology, the generated counterfeit facial images have become increasingly challenging to distinguish. There is an urgent need for a more robust and convincing detection method. Current detection methods mainly operate in the spatial domain and transform the spatial domain into other domains for analysis. With the emergence of transformers, some researchers have also combined traditional convolutional networks with transformers for detection. This paper explores the artifacts left by Deepfakes in various domains and, based on this exploration, proposes a detection method that utilizes the steganalysis rich model to extract high-frequency noise to complement spatial features. We have designed two main modules to fully leverage the interaction between these two aspects based on traditional convolutional neural networks. The first is the multi-scale mixed feature attention module, which introduces artifacts from high-frequency noise into spatial textures, thereby enhancing the model's learning of spatial texture features. The second is the multi-scale channel attention module, which reduces the impact of background noise by weighting the features. Our proposed method was experimentally evaluated on mainstream datasets, and a significant amount of experimental results demonstrate the effectiveness of our approach in detecting Deepfake forged faces, outperforming the majority of existing methods.

关键词： Deepfakes Adaptation models Attention mechanisms Noise Transforms Transformers Feature extraction Internet Convolutional neural networks Faces

来源：评论

学校读者我要写书评

暂无评论

Privacy-preserving recommendation with coarse-grained spatiotemporal contexts

引用

science China(Information sciences) 2025年第4期68卷 66-81页

作者： Lei CHEN Chen GAO Jiahuan LEI Xiaoyi DU Xinlei SHI Hengliang LUO Depeng JIN Yong LI Meng WANG Department of Electronic Engineering BNRist Tsinghua University Meituan Inc. School of Computer Science and Information Engineering Hefei University of Technology

The behavior of users on online life service platforms like Meituan and Yelp often occurs within specific finegrained spatiotemporal contexts(i.e., when and where). Recommender systems, designed to serve millions of users, typically operate in a fully server-based manner, requiring on-device users to upload their behavioral data, including fine-grained spatiotemporal contexts, to the server, which has sparked public concern regarding privacy. Consequently, user devices only upload coarse-grained spatiotemporal contexts for user privacy protection. However, previous research mostly focuses on modeling fine-grained spatiotemporal contexts using knowledge graph convolutional models, which are not applicable to coarse-grained spatiotemporal contexts in privacy-constrained recommender systems. In this paper, we investigate privacy-preserving recommendation by leveraging coarse-grained spatiotemporal contexts. We propose the coarse-grained spatiotemporal knowledge graph for privacy-preserving recommendation(CSKG), which explicitly models spatiotemporal co-occurrences using common-sense knowledge from coarse-grained contexts. Specifically, we begin by constructing a spatiotemporal knowledge graph tailored to coarse-grained spatiotemporal contexts. Then we employ a learnable metagraph network that integrates common-sense information to filter and extract co-occurrences. CSKG evaluates the impact of coarsegrained spatiotemporal contexts on user behavior through the use of a knowledge graph convolutional network. Finally, we introduce joint learning to effectively learn representations. By conducting experiments on two real large-scale datasets,we achieve an average improvement of about 11.0% on two ranking metrics. The results clearly demonstrate that CSKG outperforms state-of-the-art baselines.

关键词： privacy-preserveing coarse-grained spatiotemporal contexts recommender systems

来源：评论

学校读者我要写书评

暂无评论

Controllable photooxidation of 1-phenylethanol integrated with hydrogen evolution by a polyoxometalate/ZnIn_(2)S_(4)/WO_(3)catalytic system

引用

Nano Research 2025年第4期18卷 116-124页

作者： Jiaxin Yang Yongkang Liu Yun Qin Zhenheng Diao Yuanyuan Dong Hongjin Lv School of Chemical Engineering Advanced Institute of Materials ScienceChangchun University of TechnologyChangchun 130012China MOE Key Laboratory of Cluster Science Beijing Key Laboratory of Photoelectric/Electrophotonic Conversion MaterialsSchool of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing 102488China

The photocatalytic oxidation of 1-phenylethanol coupling with hydrogen evolution represents a promising strategy for the full utilization of the photogenerated electrons and holes to accomplish the maximum conversion of solar energy into chemical *** date,however,the controllable of reaction path and product distribution has yet not to be ***,we report an efficient coupled catalytic system composed of ZnIn_(2)S_(4)/WO_(3)S-scheme heterojunction and Ni-containing polyoxometalate([Ni_(4)(H_(2)O)_(2)(PW_(9)O_(34))_(2)]^(10-)(Ni_(4)P_(2))),which exhibited excellent photocatalytic activities towards the oxidation valorization of 1-phenylethanol coupling with hydrogen *** addition of Ni_(4)P_(2)can efficiently control the product ***,1-phenylethanol was preferentially converted to pinacol(86.0% selectivity)via C-C coupling over ZnIn_(2)S_(4)/WO_(3)S-scheme heterojunction accompanied by hydrogen production(202.4μmol),whereas it would be converted to acetophenone(93.8% selectivity)by photogenerated holes with concomitant hydrogen formation(183.1μmol)over the coupled Ni_(4)P_(2)/ZnIn_(2)S_(4)/WO_(3) catalytic *** studies revealed that the hydrogen evolution cocatalyst Ni4P2,with its excellent electron storage capacity,can compete with the oxidation product acetophenone for electrons,and thus its addition can significantly inhibit the reduction of acetophenone,resulting in the inability to generate the coupling product pinacol.

关键词： S-scheme heterojunction ZnIn_(2)S_(4) polyoxometalates dehydrocoupling hydrogen evolution photocatalysis

来源：评论

学校读者我要写书评

暂无评论

A Multi-Resolution Feature Fusion Method for Pedestrian Re-identification

IAENG International Journal of Computer Science

引用

IAENG International Journal of computer science 2024年第9期51卷 1393-1403页

作者： Qin, Haitian Xu, Yang Chen, Xupeng School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China

Pedestrian re-identification technology enables accurate identification of individuals and is widely used in modern intelligent video surveillance systems to aid law enforcement, including criminal apprehension and locating missing persons. However, variations in lighting, background, resolution, and other imaging conditions captured by different cameras create significant challenges in pedestrian feature extraction, often leading to poor recognition accuracy. To overcome these challenges, this paper presents a Multi-resolution Feature Fusion (MRFF) method for pedestrian re-identification, based on the Pedestrian Re-identification Relational Network (RNFPR). This approach incorporates the Coordinate Attention (CA) module into the DenseNet161 network to enhance feature extraction capabilities. Improving the discriminative and recognition accuracy of features requires learning and fusing pedestrian features from multiple low-resolution images. This process enhances the expressive power of feature maps, ultimately improving pedestrian recognition performance. Additionally, this method introduces a multi-resolution feature fusion module that segments and integrates multi-resolution features from image data. This enables the model to effectively combine feature information from various resolution levels, resulting in a more comprehensive feature representation. Experimental results show that the MRFF method achieves a 1.3% increase in mean Average Precision (mAP) and a 1.0% improvement in Rank-1 accuracy on the Market1501 dataset. For the DukeMTMC-reID dataset, it provides a 0.2% increase in mAP and a 0.7% enhancement in Rank-1 accuracy. Consequently, the MRFF approach results in an overall mAP increase of 0.7% on the DukeMTMC-ReID dataset, significantly improving pedestrian gender re-identification accuracy. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Security systems

来源：评论

学校读者我要写书评

暂无评论

Person Re-Identification Algorithm Based on Improved ResNet

引用

IAENG International Journal of Applied Mathematics 2024年第5期54卷 894-901页

作者： Shen, Wenrui Wang, Zhifeng School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China

Person Re-Identification falls within the scope of computer vision, acting a technique to ascertain the presence of a specified pedestrian within a video or image library. The related research is of great significance in real-world environments such as criminal investigation and statistical analysis of commercial foot traffic and has received extensive attention from the academic community. However, traditional methods such as manual extraction cannot adapt to large-scale data volumes, and deep learning-based methods at this stage suffer from interference in complex environments such as similar costumes, perspective changes, and occlusion. Therefore, in this paper, we investigate the above problems. Firstly, we expand the dataset by introducing random erasure-based preprocessing of pedestrian images to enhancing the robustness and generalization capability of neural networks. Secondly, a composite attention mechanism is introduced after the network residual layer to enhance the spatial information capability and feature expression. Finally, the union loss composed of Circle Loss, Ternary Loss, and Cross Entropy Loss was chosen for network training in the loss optimization phase. Findings from the experiments reveal that the improved method proposed in this experiment achieves 96.0%Rank-1 and 88.3%mAP in Market1501, which reflects the validity of the approach proposed in this manuscript, and provides valuable reference suggestions for Person Re-Identification related research. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Improved Infrared Road Object Detection Algorithm Based on Attention Mechanism in YOLOv8

IAENG International Journal of Computer Science

引用

IAENG International Journal of computer science 2024年第6期51卷 673-680页

作者： Luo, Zilong Tian, Ying School of Computer Science and Software Engineering University of Science and Technology Liaoning Liaoning114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China

In Currently, research in the field of infrared road object detection is primarily focused on enhancing model performance and robustness to address the challenges posed by complex real-world driving scenarios. In response to these challenges, this paper proposes an infrared road object detection algorithm based on an attention mechanism. By incorporating the CPCA module, which utilizes attention mechanisms, into the YOLOv8s model, the algorithm enhances the model’s focus on unobstructed areas and highly illuminated sections, extracting crucial feature information to improve both accuracy and robustness. Additionally, the original model’s downsampling layer is replaced with the Context Grided Network Block Downsampling (CGBD) module, which not only preserves feature edge information but also effectively handles local and contextual features, thereby enhancing the overall feature capturing capabilities of the model. To address the issue of equal aspect ratios in the model’s original loss function, the proposed algorithm adopts the superior Weighted Intersection over Union (WIoU). This not only addresses the shortcomings of the original loss function (CIoU) but also demonstrates increased sensitivity in classification tasks. Experimental results show that the improved algorithm, compared to YOLOv8s, achieves a 1.4% increase in mean average precision (mAP), along with notable improvements in precision and recall. Furthermore, when compared to mainstream model algorithms, the enhanced model significantly outperforms in infrared road object detection tasks, providing validation of its effectiveness. © (2024), (International Association of Engineers). All rights reserved.

关键词： Object detection

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：