检索结果-内蒙古大学图书馆

2011 International Green Computing Conference, IGCC 2011

作者： Liu, Zhuo Zhou, Jian Yu, Weikuan Wu, Fei Qin, Xiao Xie, Changsheng Wuhan National Laboratory for Optoelectronics Key Laboratory of Data Storage Systems Ministry of Education China Wuhan National Laboratory for Optoelectronics School of Computer Sci. and Tech. Huazhong University of Sci. and Tech. Hubei Wuhan 430074 China Department of Computer Sci. and Software Engineering Auburn University AL 36830 United States

ISBN: (纸本)9781457712203

Energy consumption is becoming a growing concern in data centers. Many energy-conservation techniques have been proposed to address this problem. However, an integrated method is still needed to evaluate energy efficiency of storage systems and various power conservation techniques. Extensive measurements of different workloads on storage systems are often very time-consuming and require expensive equipments. We have analyzed changing characteristics such as power and performance of stand-alone disks and RAID arrays, and then defined MIND as a black box power model for RAID arrays. MIND is devised to quantitatively measure the power consumption of redundant disk arrays running different workloads in a variety of execution modes. In MIND, we define five modes (idle, standby, and several types of access) and four actions, to precisely characterize power states and changes of RAID arrays. In addition, we develop corresponding metrics for each mode and action, and then integrate the model and a measurement algorithm into a popular trace tool - blktrace. With these features, we are able to run different IO traces on large-scale storage systems with power conservation techniques. Accurate energy consumption and performance statistics are then collected to evaluate energy efficiency of storage system designs and power conservation techniques. Our experiments running both synthetic and real-world workloads on enterprise RAID arrays show that MIND can estimate power consumptions of disk arrays with an error rate less than 2%. © 2011 IEEE.

关键词： Electric power utilization

来源：评论

学校读者我要写书评

暂无评论

Feature Extraction of 3D Visualized Images based on Multiscale Measurement

Feature Extraction of 3D Visualized Images based on Multisca...

引用

2023年第三届创新人才培养与可持续发展国际学术会议

作者： Haixiao Gong Siqi Zhou School of Data Science & Software Engineering Wuzhou University Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University

3D visualization image can improve the recognition ability of massive images, and extracting the features of 3D visualization image can further enhance the image processing ability. Firstly, the 3D visualization image is segmented by multi-scale, and then the basic parameters are obtained. Finally, the 3D visualization image feature is extracted by region growing method. The method of feature extraction designed by realizing the discovery has higher accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Social-Aware Edge Caching for UAV-Assisted Metaverse Systems

Social-Aware Edge Caching for UAV-Assisted Metaverse Systems

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Ya Li Guoquan Wu Jianhang Tang State Key Laboratory of Public Big Data Guizhou University China School of Information Science and Engineering Yanshan University China

Metaverse is envisaged as an evolving Internet paradigm that allows people to play, work, and socialize in a shared and virtual ecosystem with immersive and seamless experiences. However, multiple users will access the metaverse world for diverse scenes simultaneously due to its social property. How to provide high-quality and low-latency metaverse services for massive concurrent users is a crucial problem. In this work, a novel social-aware edge caching (SEC) framework is proposed for metaverse systems, where metaverse scenes are divided into massive environment panoramic frames and dynamic objects with different priorities. An unmanned aerial vehicle (UAV)-assisted edge server is deployed to cache the environment panoramic frames, while the dynamic objects are rendered on head-mounted displays (HM Ds). A synchronous advantage actor-critic (SA2C) algorithm is developed to generate caching solutions with low time complexity by considering the collective behaviors and social dynamics for requesting similar scenes. Finally, we provide some simulation experiments by leveraging a real-world dataset. The numerical results reveal that the proposed algorithm can reduce the service time and increase the cache hit rate significantly by comparing it with two benchmark caching algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ETO Meets Scheduling: Learning key knowledge from Single-Objective Problems to Multi-Objective Problem

ETO Meets Scheduling: Learning Key Knowledge from Single-Obj...

引用

Chinese Automation Congress (CAC)

作者： Wendi Xu Xianpeng Wang College of Information Science and Engineering Northeastern University Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education China

ISBN: (纸本)9781665426480

Evolutionary transfer optimization(ETO) serves as "a new frontier in evolutionary computation research", which will avoid zero reuse of experience and knowledge from solved problems in traditional evolutionary computation. In schedule-ing applications via ETO, a highly competitive "meeting" framework between them could be constituted towards both intelligent scheduling and green scheduling, especially for carbon neutrality within the context of *** the best of our knowledge, our study on scheduling here, is the 1 st work of ETO for complex optimization when multi-objective problem "meets" single-objective problems in combinatorial case (not multitasking optimization). More specifically, key knowledge like positional building blocks clustered, could be learned and transferred for permutation flow shop scheduling problem (PFSP). Empirical studies on well-studied benchmarks validate relatively firm effectiveness and great potential of our proposed ETO-PFSP framework.

关键词： Job shop scheduling Automation Processor scheduling Green buildings Evolutionary computation Benchmark testing Multitasking

来源：评论

学校读者我要写书评

暂无评论

Cross-Domain Person Re-identification Combining Feature Concatenation and Attention

Cross-Domain Person Re-identification Combining Feature Conc...

引用

作者： Feng Pan Lin Wang Yansha Zhang Jie Wang College of Data Science and Information Engineering Guizhou Minzu University Key Laboratory of Pattern Recognition and Intelligent System of Guizhou Province

To improve the insufficient generalization and poor cross-domain capability of the existing direct cross-dataset person re-identification methods,a cross-domain person re-identification method combining feature concatenation and attention(FCANet) is *** deep features of the network are concatenated to complement the feature information and obtain discriminatively feature,and the position attention module is introduced to enhance the data feature representation capability of the cross-domain task,using the joint training network of label smooth cross-entropy loss and triplet loss,model training in the source domain,and directly deploy to the target domain for *** verify the performance of the proposed method,it was experimented on three public datasets of Market1501,DukeMTMC-reID and MSMT17,which mAP and Rank1can reach 51.4%and 62.7% on *** results show that the proposed method has good performance in improving the generalization of cross-domain tasks,and the recognition accuracy outperforms the domain generalization algorithms of comparison.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Tunable electromagnetically induced transparency via graphene in microwave band

Tunable electromagnetically induced transparency via graphen...

引用

2019 International Symposium on Antennas and Propagation, ISAP 2019

作者： Wang, Jian Wei Guo Liu, Zhen Lu, Wei Bing Chen, Hao Zhang, An Qi Southeast University State Key Laboratory of Millimeter Waves School of Information Science and Engineering Nanjing China Xinyun Electronic Comp. and Dev. Co Ltd Guiyang550018 China School of Big Data and Computor Science Guizhou Normal University Guiyang550001 China School of Cyber Science and Engineering Southeast University Nanjing210096 China

ISBN: (纸本)9787900914040

The phenomenon of electromagnetic induced transparency (EIT) based on graphene in microwave band has seldom been studied due to its shortcomings in frequency modulation in this band. However, based on the excellent tunability of graphene, EIT with adjustable amplitude in microwave frequency band is still applicable. In this letter, a tunable EIT structure based on graphene in microwave band has been proposed, which has a transparent window at 1.6 GHz with a tunable transparency from about 40% to 85% adjusting the sheet resistance of graphene. The result shows that, the proposed structure has excellent adjustability and switching characteristics. © 2019 Antenna Branch of Chinese Institute of Electronics.

关键词： Graphene

来源：评论

学校读者我要写书评

暂无评论

Leveraging social connections to improve personalized ranking for collaborative filtering 14

Leveraging social connections to improve personalized rankin...

引用

23rd ACM International Conference on Information and knowledge Management, CIKM 2014

作者： Zhao, Tong McAuley, Julian King, Irwin Shenzhen Key Laboratory of Rich Media Big Data Analytics and Applications Shenzhen Research Institute Chinese University of Hong Kong Shenzhen China Department of Computer Science and Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong Department of Computer Science and Engineering UC San Diego San DiegoCA United States

ISBN: (纸本)9781450325981

Recommending products to users means estimating their preferences for certain items over others. This can be cast either as a problem of estimating the rating that each user will give to each item, or as a problem of estimating users' relative preferences in the form of a ranking. Although collaborative-filtering approaches can be used to identify users who rate and rank products similarly, another source of data that informs us about users' preferences is their set of social connections. Both rating- and ranking-based paradigms are important in real-world recommendation settings, though rankings are especially important in settings where explicit feedback in the form of a numerical rating may not be available. Although many existing works have studied how social connections can be used to build better models for rating prediction, few have used social connections as a means to derive more accurate ranking-based models. Using social connections to better estimate users' rankings of products is the task we consider in this paper. We develop a model, SBPR (Social Bayesian Personalized Ranking), based on the simple observation that users tend to assign higher ranks to items that their friends prefer. We perform experiments on four real-world recommendation data sets, and show that SBPR outperforms alternatives in ranking prediction both in warm- and cold-start settings. Copyright 2014 ACM.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Hyperspectral Image Classification Method Based on Spiking Neural Network

arXiv

引用

arXiv 2024年

作者： Liu, Yang Li, Yahui Li, Rui Zhou, Liming Dang, Lanxue Mu, Huiyu Ge, Qiang Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information Engineering Henan University Kaifeng475004 China

Convolutional neural network (CNN) performs well in Hyperspectral Image (HSI) classification tasks, but its high energy consumption and complex network structure make it difficult to directly apply it to edge computing devices. At present, spiking neural networks (SNN) have developed rapidly in HSI classification tasks due to their low energy consumption and event driven characteristics. However, it usually requires a longer time step to achieve optimal accuracy. In response to the above problems, this paper builds a spiking neural network (SNN-SWMR) based on the leaky integrate-and-fire (LIF) neuron model for HSI classification tasks. The network uses the spiking width mixed residual (SWMR) module as the basic unit to perform feature extraction operations. The spiking width mixed residual module is composed of spiking mixed convolution (SMC), which can effectively extract spatial-spectral features. Secondly, this paper designs a simple and efficient arcsine approximate derivative (AAD), which solves the non-differentiable problem of spike firing by fitting the Dirac function. Through AAD, we can directly train supervised spike neural networks. Finally, this paper conducts comparative experiments with multiple advanced HSI classification algorithms based on spiking neural networks on six public hyperspectral data sets. Experimental results show that the AAD function has strong robustness and a good fitting effect. Meanwhile, compared with other algorithms, SNN-SWMR requires a time step reduction of about 84%, training time, and testing time reduction of about 63% and 70% at the same accuracy. This study solves the key problem of SNN based HSI classification algorithms, which has important practical significance for promoting the practical application of HSI classification algorithms in edge devices such as spaceborne and airborne devices. © 2024, CC BY.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Cost-sensitive multi-layer perceptron for binary classification with imbalanced data

Cost-sensitive multi-layer perceptron for binary classificat...

引用

第37届中国控制会议

作者： Zheng Liu Sen Zhang Wendong Xiao Yan Di School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical EngineeringUniversity of Science and Technology Beijing

Currently, class imbalance has been a challenge for classification due to its highly imbalanced instances of distinct classes. With the advantage in quantity, the majority classes can get high accuracy in classification while many instances belonging to minority classes are inclined to be classified as majority classes. In this paper, we propose a novel cost-sensitive method based on multi-layer perceptron（CMMLP） for binary classification with imbalanced data. The proposed cost matrix is used to modify the construction of loss function so as to encourage classifier to pay more attention to the accuracy of minority class by minimizing training error. In order to verify the effectiveness of CMMLP, CMMLP is applied to some benchmark datasets and Click-Through Rate（CTR） prediction datasets. Experimental results illustrate that the new cost-sensitive approach can achieve better performance for binary classification with imbalanced data than the original MLP（OMLP）.

关键词： Imbalance learning Binary classification CMMLP CTR prediction

来源：评论

学校读者我要写书评

暂无评论

LUOJIA Explorer: An Auto-UAV for Unexposed Space Exploration

LUOJIA Explorer: An Auto-UAV for Unexposed Space Exploration

引用

2024 Symposium on Spatial Information to Empower the Metaverse

作者： Sun, Shangzhe Chen, Chi Yang, Bisheng Li, Liuchun Xu, Yuhang Jin, Ang State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China Engineering Research Center for Spatio-temporal Data Smart Acquisition and Application Ministry of Education of China China Institute of Artificial Intelligence in Geomatics Wuhan University Wuhan China Institute of Artificial Intelligence School of Computer Science Wuhan University Wuhan China

With the advancement of technology, unexposed spaces have emerged as a new type of strategic area, attracting significant attention from researchers. These spaces often present complex environments, such as extreme lighting variations, irregular geometries, and the lack of external positioning signals, making human entry hazardous. Fortunately, advancements in robotics and artificial intelligence have enabled unmanned systems to mitigate these challenges, allowing for safer exploration of unexposed spaces. UAVs, as vital unmanned system platforms, are extensively used across various industrial scenarios and are particularly effective for detecting unexposed spaces. To facilitate automated exploration of these areas, we propose the autonomous UAV system, LUOJIA Explorer. Equipped with a LiDAR sensor, data transmission module, and external anti-collision devices to protect the aircraft, LUOJIA Explorer is designed for effective unexposed space detection. We have integrated a laser point cloud positioning and mapping subsystem, along with a planning and control subsystem, into the LUOJIA Explorer. Through both simulation and actual experiments, the Luojia Explorer has demonstrated the capability to achieve stable flight based on self-positioning in unexposed spaces, with an exploration efficiency of 88.83 m3/s. © Author(s) 2024.

关键词： Aircraft accidents

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：