检索结果-内蒙古大学图书馆

Efficient Scheduling Mapping Algorithm for Row Parallel Coarse-Grained Reconfigurable Architecture

Tsinghua science and Technology 2021年第5期26卷 724-735页

作者： Naijin Chen Zhen Wang Ruixiang He Jianhui Jiang Fei Cheng Chenghao Han School of Computer and Information Science Anhui Polytechnic UniversityWuhu 241000China School of Computer Science and Technology Shanghai University of Electric PowerShanghai 200090China School of Software Engineering Tongji UniversityShanghai 201804China

Row Parallel Coarse-Grained Reconfigurable Architecture(RPCGRA)has the advantages of maximum parallelism and programmable *** an efficient algorithm to map the diverse applications onto RPCGRA is difficult due to a number of RPCGRA hardware *** solve this problem,the nodes of the data flow graph must be partitioned and scheduled onto the *** this paper,we present a Depth-First Greedy Mapping(DFGM)algorithm that simultaneously considers the communication costs and the use times of the Reconfigurable Cell Array(RCA).Compared with level breadth mapping,the performance of DFGM is *** percentage of maximum improvement in the use times of RCA is 33%and the percentage of maximum improvement in non-original input and output times is 64.4%(Given Discrete Cosine Transfor 8(DCT8),and the area of reconfigurable processing unit is 56).Compared with level-based depth mapping,DFGM also obtains the lowest averages of use times of RCA,non-original input and output times,and the reconfigurable time.

关键词： temporal mapping Reconfigurable Cell Array(RCA) listed scheduling communication costs

来源：评论

学校读者我要写书评

暂无评论

Discrete Geometric Coded Data Layout for Large-scale Object Storage Systems 21

Discrete Geometric Coded Data Layout for Large-scale Object ...

引用

21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International Conference on Big Data and Cloud Computing, 16th IEEE International Conference on Social Computing and Networking and 13th International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Tian, Yi Xu, Guangping Yang, Hongzhang Ni, Yue Cao, JiaXin Yang, Lei Tianjin University of Technology School of Computer Science and Engineering Tianjin China Novel Software Technology Tianjin Key Laboratory of Intelligence Computing Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China Information Technology Co. Ltd. China

ISBN: (纸本)9798350329223

Regenerating codes are new network codes proposed to reduce the data required for fault repair, which can improve the recovery efficiency of faulty nodes in data storage systems. However, unlike Reed-Solomon code, which repairs at the granularity of bytes, regenerating codes require data stored in large chunks but leads to severe read amplification, which reads out excess data when degraded read objects and increases degraded read time. That reflects a mutual constraint between improving recovery efficiency and degraded read performance, as manifested in the amplification of data reads, a vital issue considered in this *** solve this problem, we propose a new type of data layout - discrete geometric, which splits the object into a series of geometric sequences of data blocks. They are placed discretely into corresponding containers on the disks at different nodes, with containers of the same size made into a strip for encoding. The discrete characteristic ensures lower repair costs for degraded reads. The geometric characteristic ensures the repair performance of regenerating codes by large blocks, and read amplification can be mitigated through small blocks. To reduce IOPS for discrete geometric, we propose Discrete Geometric-Locally Regenerating Codes (DG-LRCs), guaranteeing lower degraded read latency while improving recovery *** results show that the degraded read time of DG-LRCs compared to regenerating codes combined with geometric partitioning is 22.56% lower at 2Gbpsand 60.56% lower at 4Gbps, and the recovery performance is 7.04 times better than that of RS code. © 2023 IEEE.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Prediction of global mean temperature based on SARIMA combined model 4

Prediction of global mean temperature based on SARIMA combin...

引用

4rth International Conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2024

作者： Li, Dongliang Chu, Chengxu Gao, Huihui Yang, Chenming Liu, Xin Huang, Zhenwu School of Humanities and Law Southwest Forestry University Kunming650224 China School of Mechanical Engineering and Automation Dalian Polytechnic University Dalian116034 China Data Science and Intelligent Media School Communication University of China Beijing100024 China School of Computer and Software Engineering Xihua University Chengdu610039 China

ISBN: (纸本)9781510681637

With the continuous development of human society, the global warming caused by greenhouse gas emissions is becoming more and more serious. In order to better cope with global warming, this paper uses the SARIMA model to predict global temperature. Then, SARIMA (1,1,1) (1,1,1) model is established to forecast the temperature. It is found that the temperature in 2050 and 2100 will not reach 20℃, and the global average temperature is expected to reach 20℃ in about 2180. Through model evaluation, it is found that the R-square of SARIMA model is 0.87. © 2024 SPIE.

关键词： Global warming

来源：评论

学校读者我要写书评

暂无评论

Correlation Fusion with Instance-level Auto-weighted for Multi-view Graph Clustering 25

Correlation Fusion with Instance-level Auto-weighted for Mul...

引用

25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Chen, Xuan Chen, Zhikui Yao, Liang Ma, Shubin Li, Peng Yu, Shuo School of Software Dalian University of Technology Da'lian China School of Electrical Engineering Anhui Polytechnic University Wu'hu China School of Computer Science and Technology Dalian University of Technology Da'lian China

ISBN: (纸本)9798350330014

Multi-view graph clustering (MGC) has emerged as a hot research topic due to its effectiveness. Previous works mainly focus on the fusion of similarity graphs to exploit the complementary and consistent. However, these approaches suffer from three shortcomings: 1) The distance similarity estimate by the linear Euclidean metric may be incorrect in revealing the association relationship of heterogeneous multi-view samples. 2) Most of them often weight the whole view to balance the effect of different views, which ignores the importance of local samples. 3) They fail to preserve the inherent manifold structure between views via directly applying similarity matrix fusion to obtain a consistent graph. To fill these gaps, this paper proposed a novel framework called correlation fusion with instance-level auto-weighted for MGC (CFIMGC). In particular, the Spearman distance is leveraged to effectively characterize the versatile correlation matrix. The sample-level auto-weighted fusion mechanism is presented for flexible assigning weight values to different sample-wise relations in intra-view and inter-view, through which the complementary of numerous correlation matrices is appropri-ately explored to produce a consistent correlation matrix. What's more, a probability graph is adaptively learned based on the fusion correlation matrix for constructing a clustering-friendly similarity graph. Meanwhile, an alternating iteration algorithm is devised to address the non-convex joint optimization problem. Comprehensive experiment results on seven widely used but challenging multi-view datasets demonstrate that the proposed method yields superiority in clustering performance against six state-of-the-art counterparts. © 2023 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

computer-Vision-Based Non-Contact Paste Concentration Measurement*

Computer-Vision-Based Non-Contact Paste Concentration Measur...

引用

2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Liang, Tailin Yuan, Zhaolin School of Computer Science and Engineering Beihang University State Key Laboratory of Software Development Environment Beijing China Research Institute of Advanced Manufacturing Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350378658

For monitoring the paste concentration, existing techniques, such as ultrasonic concentration meters and neutron meters, suffer from radiation hazards and low precision in high concentrations. This paper proposes a novel non-contact concentration measurement method based on deep learning. With the dataset collected by preparing the paste with different concentrations and taking photographs from the paste surface, a convolutional neural network is trained to extract the features from images and predict the concentration. The experiments indicate that the measurement accuracy is close to 88.79 % for the manual stirring paste dataset and 91.42 % for the automatic stirring paste dataset, which are sufficient in industrial applications. As a substitution of traditional concentration measurement instruments, the proposed vision-based concentration measurement method is non-contact and its accuracy is sufficient in industrial applications. © 2024 IEEE.

关键词： Radiation hazards

来源：评论

学校读者我要写书评

暂无评论

Infinity-Norm Weighted Low-Order Sparse Iterative DOA Estimation under Impulsive Noise

Infinity-Norm Weighted Low-Order Sparse Iterative DOA Estima...

引用

2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023

作者： Zhang, Yongqing Liu, Zhiqiang Wang, Weidong Li, Hui Shi, Wentao School of Physics and Electronic Information Engineering Henan Polytechnic University Jiaozuo454003 China School of Computer Science and Technology Henan Polytechnic University Jiaozuo454003 China School of Software Henan Polytechnic University Jiaozuo454003 China Ocean Institute Northwestern Polytechnical University Taicang215400 China

ISBN: (纸本)9798350316728

This paper investigates the subject of the direction of arrival (DOA) estimation with acoustic vector sensor array (AVSA) under impulsive noise. A low-order-based variant of the typical sparse reconstruction method is designed to address this challenge. The proposed scheme successively weights the array output snapshots using the infinity norm to remove high outliers. Subsequently, the Frobenius norm based approach is extended to lower order, and a new cost function is created to address the impulse characteristics of the residual. Finally, the expression of the signal power is quantified, and DOA is approximated on the signal power by spectral peak search mechanism. Numerical results demonstrate that the proposed algorithm offers significant performance enhancements over some current techniques in impulsive noise scenarios. © 2023 IEEE.

关键词： Impulse noise

来源：评论

学校读者我要写书评

暂无评论

CESFusion: Cross-Frequency Enhanced Spatial—Spectral Fusion Network for Hyperspectral and Multispectral Image Fusion

引用

IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Zhang, Haozheng Yang, Yanhong Li, Chaoyang Lu, Yanjie Zhang, Guodao Chen, Shengyong Tianjin University of Technology School of Computer Science and Engineering Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin300384 China School of Computer Science and Engineering Tianjin300384 China Hangzhou Dianzi University Institute of Intelligent Media Computing Hangzhou310018 China

The fusion of hyperspectral and multispectral images (MSIs) involves integrating a high spectral resolution hyperspectral image (HSI) and a high spatial resolution MSI to generate an HSI with high-resolution HSI (HR-HSI). Existing HSI-MSI fusion methods primarily focus on information fusion within the spatial domain;however, few solutions have explored the employment of frequency analysis to enhance spatial resolution, limiting their capability for global perception. In this article, we propose an efficient and novel paradigm for HSI-MSI fusion through the cross-frequency enhanced spatial-spectral fusion network, named CESFusion, exploring the complementary fusion of information between the spatial and frequency domains. Specifically, we first present the cross-frequency fusion module (CFFM) to perform global analysis through the Fourier transform (FT) and effectively integrate and enhance the frequency domain information from both HSI and MSI. Subsequently, we propose the spectral modeling module (SpeMM) based on a state space model (SMM) to capture long-range spectral dependencies with linear complexity, and integrate it with the spatial residual block-based module (SRM) for joint spatial-spectral feature extraction. Finally, to enable sufficient interaction between the spatial and frequency domains, we adopt the cross-domain interaction module (CDIM), capturing and integrating complementary information from both domains. Moreover, a frequency-based loss function is purposely designed to further improve the restoration of global information. Extensive experiments conducted on both synthetic and real datasets demonstrate the superiority of our CESFusion, as evidenced by both quantitative and qualitative evaluation results. © 1980-2012 IEEE.

关键词： Image fusion

来源：评论

学校读者我要写书评

暂无评论

A Transformer Based Complex-YOLOv4-Trans for 3D Point Cloud Object Detection on Embedded Device 2

A Transformer Based Complex-YOLOv4-Trans for 3D Point Cloud ...

引用

2nd International Conference on Electrical engineering and computer Technology, ICEECT 2022

作者： Zhang, Jingfeng Song, Qingzeng Yu, Jing School of Computer Science and Technology Tiangong University Tianjin Tianjin300387 China School of Telecommunication Engineering Beijing Polytechnic Beijing Beijing100176 China

3D object detection is widely used in the field of autonomous driving. The embedded devices have few resources and low power consumption, so the existing 3D object detection algorithms are difficult to complete the detection task in the required time under some conditions. In this paper, the Complex-YOLOv4-Trans model is proposed to use point cloud data for 3D object detection. Firstly, a transformer encoder block is introduced to improve the structure of Backbone, which makes full use of its context information to improve detection accuracy. Secondly, the general convolution in Backbone is replaced with a depth-wise separable convolution, which effectively reduces the computational load of the model. Finally, Complete-IoU (CIoU) is used as the loss function, and then 8-bit model quantization is performed to speed up the inference. We select the KITTI dataset and deploy the model on NVIDIA Jetson Xavier NX by using TensorRT acceleration tools to test the methods. The mAP of Bird's Eye View for Car is 71.79%, the mAP for 3D Detection is 15.82%, and the FPS on the NX device is 42 frames. Experimental results show that our Complex-YOLOv4-Trans can perform real-time 3D object detection tasks on low-energy embedded devices. © Published under licence by IOP Publishing Ltd.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Fall Detection Algorithm for the Elderly based on YOLOv5s

Fall Detection Algorithm for the Elderly based on YOLOv5s

引用

2022 International Joint Conference on Information and Communication engineering, JCICE 2022

作者： Zhang, Tingting Zhou, Shengyi Li, Jianbin Sun, Haocheng Sun, Xiaotong Tiangong University School of Computer Science and Technology Tianjin300387 China Tiangong University School of Software Tianjin300387 China Tiangong University School of Electronics and Information Engineering Tianjin300387 China

ISBN: (数字)9781665460675

ISBN: (纸本)9781665460675

With the aggravation of the aging society, how to monitor the fall of the elderly living alone indoors is widely concerned by the society. In recent years, the monitoring methods based on environmental sensors and wearable portable devices have achieved good results in both quality and efficiency. However, the practical promotion of them is faced with the problems of complex equipment and high cost. This paper presents a fall behavior monitoring method for the elderly based on computer vision. Firstly, in the home environment, the elderly in the home scene are monitored by a network camera, and the video data is uploaded to the cloud to extract behavioral characteristics and judge whether they fall. Secondly, the YOLOv5s algorithm is used to train the target detection model and detect falls, which has the characteristics of fast, accurate and good robustness. We conducted experiments on a dataset of 1500 images to systematically analyze the strengths and weaknesses of our approach and training model. © 2022 IEEE.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Soft-Prompting with Graph-of-Thought for Multi-modal Representation Learning 30

Soft-Prompting with Graph-of-Thought for Multi-modal Represe...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Yang, Juncheng Li, Zuchao Xie, Shuai Yu, Wei Li, Shijun Du, Bo School of Computer Science Wuhan University Hubei Wuhan China National Engineering Research Center for Multimedia Software Hubei Wuhan China School of Electronic Information Engineering Henan Polytechnic Institute Henan Nanyang China JD Explore Academy Beijing China

ISBN: (纸本)9782493814104

The chain-of-thought technique has been received well in multi-modal tasks. It is a step-by-step linear reasoning process that adjusts the length of the chain to improve the performance of generated prompts. However, human thought processes are predominantly non-linear, as they encompass multiple aspects simultaneously and employ dynamic adjustment and updating mechanisms. Therefore, we propose a novel Aggregation-Graph-of-Thought (AGoT) mechanism for soft-prompt tuning in multi-modal representation learning. The proposed AGoT models the human thought process not only as a chain but also models each step as a reasoning aggregation graph to cope with the overlooked multiple aspects of thinking in single-step reasoning. This turns the entire reasoning process into prompt aggregation and prompt flow operations. Experiments show that our multi-modal model enhanced with AGoT soft-prompting achieves good results in several tasks such as text-image retrieval, visual question answering, and image recognition. In addition, we demonstrate that it has good domain generalization performance due to better reasoning. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Image enhancement

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：