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

10,083 篇 会议
268 篇 期刊文献
37 册 图书

馆藏范围

10,388 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

7,284 篇 工学
- 5,754 篇 计算机科学与技术...
- 3,640 篇 软件工程
- 1,365 篇 信息与通信工程
- 1,287 篇 电气工程
- 877 篇 控制科学与工程
- 825 篇 电子科学与技术（可...
- 465 篇 机械工程
- 462 篇 生物工程
- 392 篇 光学工程
- 370 篇 动力工程及工程热...
- 365 篇 生物医学工程（可授...
- 288 篇 仪器科学与技术
- 258 篇 化学工程与技术
- 239 篇 交通运输工程
- 230 篇 网络空间安全
- 206 篇 材料科学与工程（可...
- 193 篇 土木工程
- 188 篇 建筑学
- 184 篇 安全科学与工程
2,754 篇 理学
- 1,410 篇 数学
- 868 篇 物理学
- 503 篇 生物学
- 362 篇 统计学（可授理学、...
- 342 篇 化学
- 240 篇 系统科学
1,333 篇 管理学
- 819 篇 管理科学与工程(可...
- 629 篇 图书情报与档案管...
- 366 篇 工商管理
444 篇 医学
- 346 篇 临床医学
- 192 篇 基础医学(可授医学...
186 篇 教育学
143 篇 法学
126 篇 经济学
48 篇 农学
41 篇 军事学
31 篇 文学
11 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

1,028 篇 program processo...
729 篇 computer archite...
423 篇 computational mo...
386 篇 hardware
341 篇 high performance...
258 篇 parallel process...
237 篇 computer science
193 篇 optimization
172 篇 benchmark testin...
164 篇 concurrent compu...
163 篇 application soft...
159 篇 runtime
149 篇 bandwidth
146 篇 computer vision
132 篇 deep learning
129 篇 registers
129 篇 libraries
122 篇 scalability
122 篇 parallel program...
121 篇 throughput

机构

70 篇 college of compu...
57 篇 school of comput...
56 篇 university of ch...
45 篇 school of comput...
34 篇 department of co...
32 篇 college of compu...
31 篇 univ chinese aca...
30 篇 school of comput...
30 篇 tsinghua univers...
27 篇 school of comput...
25 篇 school of data a...
23 篇 college of compu...
23 篇 computer network...
23 篇 high energy astr...
22 篇 graduate school ...
21 篇 graduate school ...
20 篇 center for astro...
20 篇 department of ph...
20 篇 department of ph...
20 篇 the graduate sch...

作者

24 篇 ikeda d.
23 篇 belz j.w.
22 篇 jui c.c.h.
22 篇 oshima a.
22 篇 tsuda r.
22 篇 kim j.h.
22 篇 bergman d.r.
22 篇 allen m.
22 篇 matsuyama t.
22 篇 wong t.
22 篇 ishii t.
22 篇 kim s.w.
22 篇 takamura m.
22 篇 yashiro k.
22 篇 kadota k.
22 篇 mayta r.
22 篇 ozawa s.
22 篇 kasami s.
22 篇 rodriguez d.c.
22 篇 fujisue k.

语言

9,497 篇 英文
851 篇 其他
67 篇 中文
3 篇 西班牙文
2 篇 土耳其文

检索条件"任意字段=Conference on High Performance Computer Modernization Program"

共 10388 条记录，以下是991-1000 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：

A Profiling-Based Approach to Cache Partitioning of program Data 23rd

A Profiling-Based Approach to Cache Partitioning of Progra...

引用

23rd International conference on Parallel and Distributed Computing, Applications, and Technologies, PDCAT 2022

作者： Breiter, Sergej Weidendorfer, Josef Chung, Minh Thanh Fürlinger, Karl MNM Team Ludwig-Maximilians-Universität München Munich Germany Garching Germany

ISBN: (纸本)9783031299261

Cache efficiency is important to avoid unnecessary data transfers and to keep processors active. Cache partitioning, a technique to virtually divide a cache into multiple partitions, has become available in recent hardware. Cache partitioning can improve efficiency by isolating data with high temporal locality to avoid its early eviction before reuse. However, deciding on the partitioning is challenging, because it depends on the locality of reference. To facilitate the decision-making, we propose a profiling-based approach that measures locality, providing knowledge for cache partitioning without requiring manual code analysis. We present a profiling tool and confirm its benefits through experiments on Fujitsu’s A64FX processor, which supports the cache partitioning mechanism called sector cache. Our results show ways to optimize program codes to improve cache efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data transfer

来源：评论

学校读者我要写书评

暂无评论

Efficient Checkpoint under Unstable Power Supplies on NVM based Devices 24

Efficient Checkpoint under Unstable Power Supplies on NVM ba...

引用

24th IEEE International conference on high performance Computing and Communications, 8th IEEE International conference on Data Science and Systems, 20th IEEE International conference on Smart City and 8th IEEE International conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Liu, Jialin Sha, Edwin Zhuge, Qingfeng Xu, Rui Song, Yuhong School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (纸本)9798350319934

In smart cities, many embedded devices' power supply lacks stability, e.g., solar panel, since they are used outdoors. In these systems, power failures can cause data lost if the data is kept on volatile media like DRAM. Thus, using a backup mechanism to record the program status is necessary for the program going forward. Non-volatile memory (NVM) provides systems with a convenient method to persist the programs' status. However, NVM is notorious for poor write endurance. In this paper, we propose an automatic checkpoint mechanism that can reduce NVM write wear. Firstly, the checkpoint trigger code is instrumented into every basic block to achieve automatic runtime checkpoint activation. Then, when the program triggers checkpoint, the checkpoint procedure incrementally updates program state's backup to reduce redundant NVM writes. In this step, we select what to back up by determining the activated stack frame. Also, our mechanism has two backup copies to avoid power loss corrupting the backup content by interrupting the checkpoint procedure. Finally, we design an update log queue to fine-grained update of global data so that the NVM write can be reduced. Experiments show that our mechanism can effectively reduce total NVM write overhead with acceptable execution overhead. © 2022 IEEE.

关键词： Dynamic random access storage

来源：评论

学校读者我要写书评

暂无评论

Impact Analysis of NUMA-Aware Flow Placement Based on Network Flow Size in Multicore Systems 15

Impact Analysis of NUMA-Aware Flow Placement Based on Networ...

引用

15th International conference on Information and Communication Technology Convergence, ICTC 2024

作者： Jang, Junseo Hwang, Jaehyun Sungkyunkwan University Department of Semiconductor Convergence Engineering Suwon Korea Republic of Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350364637

This paper analyzes the impact of Direct Cache Access (DCA) within a multicore Non-Uniform Memory Access (NUMA) framework on network packet processing efficiency in Linux systems. By strategically placing network flows based on their characteristics and NUMA locality, we examine the performance dynamics of integrating and distributing long and short flows across different NUMA nodes. Utilizing Advanced Receive Flow Steering (aRFS) to differentiate and steer flows, we provide insights into the benefits of leveraging DCA for long flows and using DMA for short flows. Our study reveals significant improvements in network throughput by reducing data copying overheads, highlighting optimized traffic management strategies for high-demand data centers. © 2024 IEEE.

关键词： Linux

来源：评论

学校读者我要写书评

暂无评论

ASIMSA: Advanced Semantic Information Guided Multi-Scale Alignment Framework for Medical Vision-Language Pretraining 9

ASIMSA: Advanced Semantic Information Guided Multi-Scale Ali...

引用

9th IEEE International conference on Computational Intelligence and Applications, ICCIA 2024

作者： Xiao, Shuai Zhang, Yangyang Jiang, Liming Wang, Zhengxia School of Computer Science and Technology Hainan University China School of Information and Communication Engineering Hainan University China Software Co. Ltd. China

ISBN: (纸本)9798350352214

Medical Visual Language Pretraining (MVLP) utilizes textual reports for weak supervision to improve the learning of medical visual representations, showing promise in various medical image analysis tasks. While previous studies have focused on image and report correspondences within the same instances, they have overlooked high-level semantic associations, such as disease-level semantic correspondences, across different instances. To address this issue, we propose an Advanced Semantic Information Guided Multi-Scale Alignment Framework (ASIMSA) with two main modules: 1) Image-Report Alignment (IRA) module for learning shared representations between image and report of the same instance, and 2) Disease-Entity Alignment (DEA) module for learning disease entity correspondences across different instances. Extensive experiments on zero-shot classification, fine-tune classification, and semantic segmentation tasks validate the effectiveness of our proposed method, demonstrating its stable and superior performance. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

From Non-Expert to Expert: Recurrent Refined Learning for Medical Image Segmentation

From Non-Expert to Expert: Recurrent Refined Learning for Me...

引用

2024 IEEE International conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Jiang, Ruohui Li, Changtai Ban, Xiaojuan Yin, Shihua Yao, Chao Guo, Yu Obaidat, Mohammad S. University of Science and Technology Beijing Beijing Advanced Innovation Center for Materials Genome Engineering Beijing China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing China Liaoning Academy of Materials Institute of Materials Intelligent Technology Shenyang China Second Affiliated Hospital Guangxi Medical University Nanning China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China University of Jordan King Abdullah Ii School of Information Technology Amman Jordan Amity University UP Noida India

ISBN: (纸本)9798350386226

Precise lesion segmentation is essential in computer-aided diagnosis and treatment. Prevalent deep-learning-based approaches need high-quality annotations to achieve satisfying performance. However, blurring effects and infiltration hamper the accurate delineation of lesions. A common solution is to divide the annotation process into initial annotation by non-specialized personnel and subsequent modification by expert physicians, where the latent correction patterns and non-expert labels are seldom utilized effectively. To explore their helpfulness, we propose ReReNet, a recurrent refined network for lesion segmentation that learns from non-expert to expert. It achieves progressively refined segmentation results through multiple iterations with tailored discrepancy-aware supervision. During training, as the iterative process perceives discrepancies between refining and expert labels, the model gradually grasps the knowledge of turning the barely correct into the clinically accurate. We validate ReReNet's capability on three medical image segmentation (MIS) datasets, including magnetic resonance (MR) and computed tomography (CT) modalities. Comparison results indicate that the proposed approach achieves superior performance by introducing the designed recurrent mechanism and outperforms mainstream methods, demonstrating the effectiveness of mining hidden correction patterns by utilizing non-expert information. © 2024 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Lossy Compression of Multi-Channel EEG and PPG Signals Based on Golomb-Rice Coding with Parameter Estimation

Lossy Compression of Multi-Channel EEG and PPG Signals Based...

引用

2024 International conference on Advanced Technologies for Communications, ATC 2024

作者： Wanasekara, Senura Hansaja Dung, Han Huy Nguyen, Ngoc Hung Nguyen, Van-Dinh College of Engineering and Computer Science Center for Environmental Intelligence VinUniversity Hanoi Viet Nam School of Electrical and Electronic Engineering Hanoi University of Science and Technology Viet Nam

ISBN: (纸本)9798350353983

The integration of electroencephalography (EEG) and photoplethysmography (PPG) in consumer-grade wearable devices is revolutionizing healthcare by enabling continuous health monitoring. However, these devices face significant challenges in terms of power consumption, computational complexity, and data storage, necessitating efficient data compression techniques. This paper proposes a modified Golomb-Rice coding method tailored for lossy compression of multi-channel EEG and PPG signals. By leveraging the statistical properties of filtered data and employing an optimized parameter estimation strategy, the proposed method achieves high compression ratios while minimizing computational overhead and preserving critical signal information. The proposed algorithm shifts data to handle negative values, scales and converts it into an appropriate format for encoding, and uses a novel parameter estimation technique to optimize the Golomb-Rice parameter. Extensive simulations on EEG and PPG datasets demonstrate that this parameter estimation method yields significantly better performance, improving both efficiency and processing speed. Results underscore the importance of preprocessing in data compression and provide a robust framework for future advancements in biomedical signal processing. © 2024 IEEE.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

Enhancing Data Collection in Wide-Area Internet of Things: A Comprehensive Low-Overhead Approach 22

Enhancing Data Collection in Wide-Area Internet of Things: A...

引用

22nd International conference on Optical Communications and Networks, ICOCN 2024

作者： Li, Anyi Zhang, Bin Peng, Wei Xu, Yuwei Zhao, Feng Zhao, Baokang Xin, Qin School of Computer National University of Defense Technology Changsha China University of the Faroe Islands Faroe Islands

ISBN: (纸本)9798350367652

The rapid development of the Internet of Things (IoT) has led to the widespread application of widearea IoT, which offers the advantages of low power consumption and wide coverage. Nevertheless, the scarcity of bandwidth resources poses a significant challenge to the data transmission efficiency of wide-area IoT. Furthermore, the data encoding algorithms currently employed for message payloads tend to exhibit high redundancy and low efficiency. In order to enhance the data transmission efficiency of widearea IoT, our research has yielded the following outcomes: (1) A Template-Based Data Encoding Algorithm (TempEncode) is proposed, which employs data templates to define the message structure. The data template is employed by both senders and receivers, enabling the message payload to be compressed and overhead reduced. (2), a Low Overhead and Enhancing Data Collection (LEAD) approach has been devised for wide-area IoT based on the Message Queuing Telemetry Transport (MQTT) protocol and integrating TempEncode with Robust Header Compression. The experimental results demonstrate that LEAD has reduced the packet size by approximately 50.2% on average in comparison to the original MQTT protocol, thereby achieving efficient data transmission performance. © 2024 IEEE.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

Spk2ImgMamba: Spiking Camera Image Reconstruction with Multi-Scale State Space Models

Spk2ImgMamba: Spiking Camera Image Reconstruction with Multi...

引用

2025 IEEE/CVF Winter conference on Applications of computer Vision, WACV 2025

作者： Yin, Jiaoyang Fan, Bin Xu, Chao Huang, Tiejun Shi, Boxin School of Computer Science Peking University State Key Lab of Multimedia Info. Processing China School of Computer Science Peking University Nat'l Eng. Research Ctr. of Visual Technology China School of Intelligence Science and Technology Peking University Nat'l Key Lab of General Ai China

ISBN: (纸本)9798331510831

As a bio-inspired vision sensor, the spiking camera has showcased remarkable capability in high-speed imaging with a sampling rate of 40,000 Hz. Reconstructing clear images from continuous spike streams, which is obtained by each photosensor continuously detecting photons and firing them asynchronously, has garnered significant attention. Despite promising results, existing spike-to-image reconstruction methods face challenges in balancing global receptive fields and efficient computation due to the inherent limitations of their backbones. Recently, due to powerful long-range modeling and linear complexity, the state space model (SSM) has emerged as a competitive alternative to CNNs and Transformers. In this paper, we propose a lightweight spike-to-image reconstruction network that harnesses Mamba as the backbone. Our approach sequentially executes three core modules: temporal information integration, spatial feature enhancement, and progressive image reconstruction. The former accumulates cues across diverse temporal windows to explore both long-term and short-term contexts. Subsequently, to model global dependencies while heightening local detail perception, we develop a multi-scale SSM block characterized by multi-scale multi-direction scanning, which effectively boosts spatial feature representations. Finally, intensity images are decoded progressively from the enhanced light-intensity features. Extensive experiments on both synthetic and real-captured data demonstrate that our approach achieves state-of-the-art performance, with only 10% of the network parameters and nearly two orders of magnitude less computational effort. The code will be available at https://***/interstellarH/Spk2ImgMamba. © 2025 IEEE.

关键词： Bioimaging

来源：评论

学校读者我要写书评

暂无评论

Unmanned Aerial Vehicle Assisted Timely Data Collection in IoT Networks with Faulty Sensors 16

Unmanned Aerial Vehicle Assisted Timely Data Collection in I...

引用

16th International conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Zhang, Dongliang Gong, Jie School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Guangdong Province Key Laboratory of Information Security Technology Guangzhou510006 China

ISBN: (纸本)9798350390643

Thanks to their low deployment costs and high flexibility, unmanned aerial vehicles (UAVs) have been widely applied for data collection in Internet of Things (IoT) networks. However, the unpredictable status updates from deployed sensor nodes (SN) and potential failures of SN can affect the freshness of information. In this paper, we investigate the UAV data collection in monitored areas with redundant SNs to alleviate the impact of potential SN failures. The SNs generate status updates at random time slots, which will be collected by UAVs and transmitted to a data center. In order to minimize the average age of synchronization (AoS) of the network and the UAV energy consumption, we formulate a Markov decision process and adopt dueling double deep Q network (D3QN) method to optimize UAV flight trajectories. Simulation results demonstrate that our method achieves better performance compared with baseline policies in environments where SN failures occur. © 2024 IEEE.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

An emotional EEG signal classification research based on deep learning 3

An emotional EEG signal classification research based on dee...

引用

3rd International conference on computer Vision, Image and Deep Learning and International conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Cai, Baoqing Quan, Wei Li, Qi Song, Yu Changchun University of Science and Technology School of Computer Science and Technology Changchun China Zhongshan Institute of Changchun University of Science and Technology Zhongshan China

ISBN: (纸本)9781665459112

For the task of classifying emotional EEG signals with rich high-dimensional features in the time and frequency domains, this paper proposes a novel deep learning algorithm, SincNet-E, inspired by the speech recognition model SincNet. The convolutional structure of SincNet is adapted so that it can be considered as consisting of two pooling layers alternately superimposed with three convolutional groups. Subsequently, the LSTM structure is added after the convolutional structure to enhance its extraction of time-dependent features in the signal data. This novel model effectively improves the classification performance of the deep learning algorithm for emotional EEG data, ultimately achieving an accuracy of about 83.89% without the need for manual feature extraction. © 2022 IEEE.

关键词： Convolutional neural networks

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500页 << < 96 97 98 99 100 101 102 103 104 105 > >>

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：