检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

4,548 篇 会议
82 篇 期刊文献
15 册 图书

馆藏范围

4,645 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,559 篇 工学
- 2,365 篇 计算机科学与技术...
- 1,164 篇 软件工程
- 494 篇 电气工程
- 407 篇 信息与通信工程
- 213 篇 控制科学与工程
- 212 篇 电子科学与技术（可...
- 98 篇 网络空间安全
- 80 篇 动力工程及工程热...
- 80 篇 生物工程
- 68 篇 光学工程
- 65 篇 机械工程
- 56 篇 生物医学工程（可授...
- 36 篇 建筑学
- 30 篇 化学工程与技术
- 29 篇 环境科学与工程（可...
614 篇 理学
- 375 篇 数学
- 144 篇 物理学
- 93 篇 生物学
- 74 篇 系统科学
- 69 篇 统计学（可授理学、...
465 篇 管理学
- 346 篇 管理科学与工程(可...
- 134 篇 图书情报与档案管...
- 129 篇 工商管理
- 65 篇 公共管理
111 篇 法学
- 103 篇 社会学
104 篇 医学
- 73 篇 公共卫生与预防医...
- 31 篇 临床医学
- 29 篇 基础医学(可授医学...
65 篇 文学
- 65 篇 新闻传播学
39 篇 经济学
- 38 篇 应用经济学
17 篇 教育学
10 篇 农学
1 篇 艺术学

主题

1,194 篇 computer archite...
426 篇 hardware
344 篇 high performance...
295 篇 computational mo...
255 篇 concurrent compu...
236 篇 application soft...
214 篇 computer science
205 篇 parallel process...
179 篇 distributed comp...
178 篇 costs
171 篇 delay
170 篇 grid computing
168 篇 bandwidth
164 篇 field programmab...
154 篇 resource managem...
153 篇 cloud computing
144 篇 computer network...
142 篇 throughput
129 篇 processor schedu...
125 篇 scalability

机构

22 篇 institute of com...
16 篇 graphic era deem...
14 篇 chitkara univers...
13 篇 university of ch...
11 篇 college of compu...
10 篇 school of comput...
10 篇 computer science...
9 篇 georgia inst tec...
9 篇 computer systems...
9 篇 intel corp santa...
8 篇 department of co...
8 篇 department of el...
8 篇 ibm thomas j. wa...
8 篇 barcelona superc...
8 篇 mathematics and ...
8 篇 quantum universi...
8 篇 中国电子科技集团...
8 篇 mathematics and ...
8 篇 key laboratory o...
8 篇 univ fed rio gra...

作者

14 篇 navaux philippe ...
10 篇 satvik vats
9 篇 vats satvik
9 篇 i. foster
9 篇 d.k. panda
8 篇 dhabaleswar k. p...
8 篇 dongarra jack
8 篇 loh gabriel h.
8 篇 guedes dorgival
8 篇 viktor k. prasan...
8 篇 prasanna viktor ...
8 篇 mutlu onur
7 篇 shiva mehta
7 篇 borin edson
7 篇 chong frederic t...
7 篇 torrellas josep
7 篇 kim nam sung
7 篇 li chao
7 篇 zhou huiyang
7 篇 ferreira renato

语言

4,522 篇 英文
101 篇 其他
20 篇 中文
3 篇 葡萄牙文
1 篇 法文

检索条件"任意字段=15th Symposium on Computer Architecture and High Performance Computing"

共 4645 条记录，以下是531-540 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

performance Analysis of Breast Cancer Predictor using Machine Learning Techniques

Performance Analysis of Breast Cancer Predictor using Machin...

引用

International Conference on computing and Networking Technology (ICCNT)

作者： Raj Sinha Meeta Patel Sandeep Gupta Keshav Kumar Sinha Prateeksha School of Computer Applications Lovely Professional University Punjab India Bhagwan Mahavir lnstitute of Medical Sciences Pawapuri Nalanda Bihar India Department of Electrical Engineering Graphic Era (Deemed to be University) Dehradun Uttarakhand India Department of Pharmacology Radiation Oncologist Patna Medical College Patna Bihar India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

In women, breast cancer stands as a leading cause of death among all types of cancer globally. Death rates can be mitigated through early prediction of breast cancer. Various machine learning techniques play a significant role in detecting breast cancer at an early stage. It is essential to develop a machine learning model with high accuracy and precision to predict breast cancer disease effectively. this paper employs various machine learning techniques to predict breast cancer. the performance evaluation of these techniques is conducted in terms of precision, accuracy, and F1-score. the Extra Trees Classifier emerged with the highest accuracy, reaching 97.23%.

关键词： performance evaluation Analytical models Accuracy Predictive models Feature extraction Breast cancer Data models performance analysis Reliability Random forests

来源：评论

学校读者我要写书评

暂无评论

Hyperdimensional computing vs. Neural Networks: Comparing architecture and Learning Process

Hyperdimensional Computing vs. Neural Networks: Comparing Ar...

引用

IEEE International symposium on Quality Electronic Design

作者： Dongning Ma Cong Hao Xun Jiao Villanova University Georgia Institute of Technology

ISBN: (数字)9798350309270

ISBN: (纸本)9798350309287

Hyperdimensional computing (HDC) has obtained abundant attention as an emerging non von Neumann computing paradigm. Inspired by the way human brain functions, HDC leverages high dimensional patterns to perform learning tasks. Compared to neural networks, HDC has shown advantages such as energy efficiency and smaller model size, but sub-par learning capabilities in sophisticated applications. Recently, researchers have observed when combined with neural network components, HDC can achieve better performance than conventional HDC models. this motivates us to explore the deeper insights behind theoretical foundations of HDC, particularly the connection and differences with neural networks. In this paper, we make a comparative study between HDC and neural network to provide a different angle where HDC can be derived from an extremely compact neural network trained upfront. Experimental results show such neural network-derived HDC model can achieve up to 21% and 5% accuracy increase from conventional and learning-based HDC models respectively. this paper aims to provide more insights and shed lights on future directions for researches on this popular emerging learning scheme.

关键词： Training Analytical models Computational modeling computer architecture Brain modeling Energy efficiency Task analysis

来源：评论

学校读者我要写书评

暂无评论

CCS: A Motif-Based Storage Format for Micro-execution Dependence Graph 15th

CCS: A Motif-Based Storage Format for Micro-execution Depend...

引用

15th International symposium on Advanced Parallel Processing Technologies, APPT 2023

作者： Zheng, Yawen Han, Chenji Zhang, Tingting Yang, Chao Wang, Jian State Key Lab of Processors ICT CAS Beijing China Institute of Computing Technology CAS Beijing China University of Chinese Academy of Sciences Beijing China Loongson Technology Corporation Limited Beijing China Electric Power Research Institute of State Grid Liaoning Electric Power Co Ltd Shenyang China

ISBN: (纸本)9789819978717

Micro-execution dependence graphs model the program execution on a microprocessor as relationships of micro-execution events intra- and inter-instructions for performance analysis. Each instruction constitutes a motif whose structure is defined by the dependence graph model. With the size of the application increasing dramatically, storing a large-scale dependence graph with billions of instructions becomes difficult. However, popular graph storage formats, such as CSR and CSC, are inefficient for motifs. And the current motif-based compression methods involve the time-consuming process of subgraph isomorphism checking, which is NP-hard. To reduce redundancy, we propose a novel motif-based lossless storage format called compressed common subgraph (CCS) for micro-execution dependence graphs. the key idea is to divide the graph into the intra- and inter-motif parts and compress the common subgraph structures in the intra-motif part by storing the same structures only once. Our method avoids subgraph isomorphism checking because the motifs (instructions) are regularly arranged. Furthermore, the CCS format has two variant implementations, compressed common single subgraph (CCSS) and compressed common multiple subgraphs (CCMS) to adapt to various dependence graph models. Experimental results show that our CCSS and CCMS formats use 16.66% and 8.67% less memory size than the CSC graph format, respectively. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Set theory

来源：评论

学校读者我要写书评

暂无评论

Albireo: Energy-Efficient Acceleration of Convolutional Neural Networks via Silicon Photonics 21

Albireo: Energy-Efficient Acceleration of Convolutional Neur...

引用

ACM/IEEE 48th Annual International symposium on computer architecture (ISCA)

作者： Shiflett, Kyle Karanth, Avinash Bunescu, Razvan Louri, Ahmed Ohio Univ Athens OH 45701 USA Univ N Carolina Charlotte NC USA George Washington Univ Washington DC 20052 USA

ISBN: (纸本)9781665433334

With the end of Dennard scaling, highly-parallel and specialized hardware accelerators have been proposed to improve the throughput and energy-efficiency of deep neural network (DNN) models for various applications. However, collective data movement primitives such as multicast and broadcast that are required for multiply-and-accumulate (MAC) computation in DNN models are expensive, and require excessive energy and latency when implemented with electrical networks. this consequently limits the scalability and performance of electronic hardware accelerators. Emerging technology such as silicon photonics can inherently provide efficient implementation of multicast and broadcast operations, making photonics more amenable to exploit parallelism within DNN models. Moreover, when coupled with other unique features such as low energy consumption, high channel capacity with wavelength-division multiplexing (WDM), and high speed, silicon photonics could potentially provide a viable technology for scaling DNN acceleration. In this paper, we propose Albireo, an analog photonic architecture for scaling DNN acceleration. By characterizing photonic devices such as microring resonators (MRRs) and Mach-Zehnder modulators (MZM) using photonic simulators, we develop realistic device models and outline their capability for system level acceleration. Using the device models, we develop an efficient broadcast combined with multicast data distribution by leveraging parameter sharing through unique WDM dot product processing. We evaluate the energy and throughput performance of Albireo on DNN models such as ResNet18, MobileNet and VGG16. When compared to current state-of-the-art electronic accelerators, Albireo increases throughput by 110X, and improves energy-delay product (EDP) by an average of 74 X with current photonic devices. Furthermore, by considering moderate and aggressive photonic scaling, the proposed Albireo design shows that EDP can be reduced by at least 229 X.

关键词： optical computing silicon photonics hardware acceleration deep neural networks

来源：评论

学校读者我要写书评

暂无评论

UFC: A Unified Accelerator for Fully Homomorphic Encryption

UFC: A Unified Accelerator for Fully Homomorphic Encryption

引用

IEEE/ACM International symposium on Microarchitecture (MICRO)

作者： Minxuan Zhou Yujin Nam Xuan Wang Youhak Lee Chris Wilkerson Raghavan Kumar Sachin Taneja Sanu Mathew Rosario Cammarota Tajana Rosing Illinois Institute of Technology University of California San Diego Intel Labs

ISBN: (数字)9798350350579

ISBN: (纸本)9798350350586

Fully homomorphic encryption (FHE) is crucial for post-quantum privacy-preserving computing. Researchers have proposed various FHE schemes that excel at different encrypted computations, such as single-instruction multiple-data (SIMD) arithmetic or arbitrary single-data functions. Hybrid-scheme FHE, which exploits appropriate schemes for specific tasks, is essential for real-world applications requiring optimal performance and accuracy. However, existing FHE accelerators only adopt scheme-specific custom designs, leading to inefficiency or lack of capability to support applications in hybrid FHE settings. In this work, we propose a Unified FHE aCcelerator (UFC) that provides better performance and cost-efficiency than prior scheme-specific accelerators on hybrid FHE applications. Our design process involves a comprehensive analysis of processing flows to abstract the primitives covering all operations in hybrid FHE applications. the UFC architecture primarily comprises hardware function units for these primitives, diverging from the deeply pipelined units in previous designs. this approach enables high hardware utilization across different FHE schemes. Further-more, we propose several algorithm-hardware co-optimizations to minimize the hardware cost of supporting various data shuffling patterns in FHE. this enables high-throughput implementation of function units that provide good cost efficiency. We also propose several compiler-level optimizations to achieve high hardware utilization of the unified architecture for computing FHE data in various algorithmic parameter settings. We evaluate the performance of UFC on different FHE programs, including scheme-specific and hybrid-scheme workloads. Our experiments show that UFC provides up to 6.0 × speedup and 1.6 × delay-energy-area efficiency improvement over state-of-the-art FHE accelerators.

关键词： Costs Microarchitecture Single instruction multiple data Scalability computer architecture Hardware Cryptography Homomorphic encryption Optimization Arithmetic

来源：评论

学校读者我要写书评

暂无评论

Fleet in the Loop: An Open Source approach for design and test of resilient vehicle architectures

Fleet in the Loop: An Open Source approach for design and te...

引用

International symposium on Autonomous Decentralized Systems (ISADAS)

作者： Daniel Grimm Marc Schindewolf Eric Sax Institut für Technik der Informationsverarbeitung (ITIV) Karlsruhe Institute of Technology Karlsruhe Germany

Due to the increasing automation and connectivity of future, software-defined vehicles, the interest in safety and security in this field is growing. In contrast to automated driving functions, which today are only tested and approved for specific operating conditions, the vehicle must be safe and secure in any situation, even if there is a malfunction or intentional manipulation. Resilient software and hardware architectures for vehicles are, therefore, a research topic of growing importance. However, due to the holistic nature of this approach, researching and testing these systems is fraught with challenges. For example, once Machine Learning-based approaches come into play, large amounts of data are required. At the same time, tests of the systems need to take into account the whole vehicle and its ecosystem and be scalable and user-friendly. this work, therefore, presents a new simulation-based method for testing and developing functions for software-defined connected vehicles. the focus is especially on safety and security in combination with cloud services and the consideration of the vehicle fleet. the technologies are presented in detail, relying mainly on the simulator CARLA, the virtualization with Proxmox, and ROS2-based vehicle functions. What differentiates this approach from others is the purely virtual and open-source approach, which increases the availability for others. Results are shown based on early quantitative measures and on outlining two exemplary use cases.

关键词： Cloud computing Connected vehicles Ecosystems computer architecture Software Hardware Safety

来源：评论

学校读者我要写书评

暂无评论

Chinese named entity recognition based on Heterogeneous Graph and Dynamic Attention Network

Chinese named entity recognition based on Heterogeneous Grap...

引用

International symposium on Autonomous Decentralized Systems (ISADAS)

作者： Yuke Wang Ling Lu Wu Yang Yinong Chen School of Computer Science and Engineering Chongqing University of Technology Chongqing China Chongqing University of technology No. 69 Hongguang Avenue Banan District Chongqing China School of Computing and Augmented Intelligence Arizona State University Tempe USA

Abstract Lexicon have been proved to enhance character representation to help Chinese named entity recognition (NER) model distinguish entities. Although lexicon information includes both semantic and boundary information of words, existing studies usually use only part of them and has low utilization of lexicon information. To efficiently extract dictionary features and integrate character representation, we propose a Heterogeneous Graph and Dynamic Attention Network (HGDAN), aiming at fusing contextual information and capturing dynamic associations between characters and words, thus improving the performance of Chinese NER. PGDNA uses the boundary information of the dictionary to construct a heterogeneous graph and uses the graph attention method to extract semantic information, as well as suppressing lexical noise through the gating unit. In addition, we found the traditional attention model has a non-zero attention problem that will distract the attention of the model, and proposed a simple and effective method to solve it. Experiments on the performance and inference speed of HGDAN on four Chinese datasets have proved its superiority.

关键词： Dictionaries Semantics Maintenance engineering Feature extraction Data mining Character recognition

来源：评论

学校读者我要写书评

暂无评论

A Bald Eagle Search Optimization Based Weighted Rank Aggregation Method for Microarray Data Classification 23

A Bald Eagle Search Optimization Based Weighted Rank Aggrega...

引用

15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023

作者： Li, Wei Shi, Tengfei Wang, Linjie Xie, Weidong Key Laboratory of Intelligent Computing in Medical Image MIIC Northeastern University Ministry of Education China School of Computer Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9798400700385

the rapid development of microarray technology has generated a large amount of microarray data, and the classification of these data is meaningful for cancer diagnosis, treatment and prognosis. the classification of high-dimensional microarray data with small samples is a challenging problem, which usually requires feature selection methods to reduce the data dimensionality first. However, different feature selection methods usually generate different feature lists for the same data. Researchers need to choose among many feature selection methods, which reduces the research efficiency. therefore, rank aggregation method is used to generate a optimal list by aggregating all ordered feature lists generated by different feature selection methods. It can combine the advantages of multiple feature selection methods and does not prefer a particular method, so it is more robust to outliers, noises and errors. In this paper, we propose a weighted rank aggregation method based on the Bald Eagle Search optimization. A positional weight is designed to emphasize the importance of the top features in the list, so that the distance between lists can be measured more accurately. In addition, we improve the Bald Eagle Search algorithm for optimizing rank aggregation method to obtain a optimal ordered list. the experimental results on six public microarray datasets indicate that the features selected by our method can significantly improve the classification performance. © 2023 ACM.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning architecture for Recognizing Abnormal Activities of Groups Using Context and Motion Information 15th

A Deep Learning Architecture for Recognizing Abnormal Activi...

引用

15th International Conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2020

作者： Borja-Borja, Luis Felipe Azorín-López, Jorge Saval-Calvo, Marcelo Facul. de Ingen. Ciencias Físicas y Matemática Universidad Central del Ecuador Av. Universitaria Quito170129 Ecuador Computer Technology Department University of Alicante Alicante03080 Spain

ISBN: (纸本)9783030578015

Currently, the automation of activity recognition of a group of people in closed and open environments is a major problem, especially in video surveillance. It is becoming increasingly important to have computer vision architectures that allow automatic recognition of group activities to make decisions. this paper proposes a computer vision architecture capable of learning and recognizing abnormal group activities using the movements of the group in the scene. It is based on the Activity Description Vector, a descriptor capable of representing the trajectory information of a sequence of images as a collection of local movements that occur in specific regions of the scene. the proposal is based on the evolution of different versions of this descriptor towards the generation of images that will be input of a two-stream classifier capable of robustly classifying abnormal group activities. Moreover, it includes context information to provide extra information to classify the activities including it as the third stream of the classifier resulting in a robust architecture for one class classification problems. the architecture has been evaluated and compared with other approaches using Ped 1 and Ped 2 datasets, obtaining a high performance in abnormal group activity recognition. © 2021, the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

TC-GAN: A Transformer-based Conditional Generative Adversarial Network for Low-Dose SPECT Image Reconstruction 23

TC-GAN: A Transformer-based Conditional Generative Adversari...

引用

15th International Conference on Machine Learning and computing, ICMLC 2023

作者： Liang, Zengguo Li, Si School of Computer Science and Technology Guangdong University of Technology Guangdong Guangzhou China

ISBN: (纸本)9781450398411

Low-dose single photon emission computed tomography (SPECT) technology can reduce radiation damage to the subject but lead to reconstructed image quality degradation, such as severe noise and artifacts. Many existing works utilize convolutional neural networks (CNNs) to improve the quality of reconstructed images at low doses and demonstrate impressive performance. However, the intrinsic locality nature of convolutional operation limits the ability of CNNs to encode explicitly long-range dependencies. Combining the long-range dependencies effectively during reconstruction might improve the quality of reconstructed images. therefore, we designed a novel transformer-based network, dubbed TC-GAN, which combines the conditional generative adversarial network (CGAN) and CSwin Transformer for high-quality low-dose SPECT reconstruction. In TC-GAN, the CSwin transformer was integrated into the generator of CGAN as a strong feature extractor to establish the intra-relationships in the whole image and provide plenty of global contextual information for image reconstruction. the CGAN was used as the backbone of our network to synthesize reconstructed images with accurate structure and pixel-level details via adversarial training fashion. In the experiment, we used the Monte Carlo simulation software SIMIND to produce low-dose SPECT image datasets. the results show that the proposed method has better reconstruction performance than several recent methods. In terms of visual analysis, the proposed method maintains more accurate image structure and details while noise suppression. In terms of quantitative analysis, the proposed method obtains the best results in global image quality metrics. Our results suggest that the proposed network has good potential to reduce radiation dose without compromising the reconstructed image quality. © 2023 ACM.

关键词： Single photon emission computed tomography

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共465页 << < 50 51 52 53 54 55 56 57 58 59 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：