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

23,957 篇 会议
411 篇 期刊文献
285 册 图书
1 篇 学位论文
1 篇 科技报告

馆藏范围

24,655 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

14,508 篇 工学
- 13,378 篇 计算机科学与技术...
- 5,960 篇 软件工程
- 2,508 篇 电气工程
- 2,169 篇 信息与通信工程
- 916 篇 控制科学与工程
- 531 篇 电子科学与技术（可...
- 412 篇 机械工程
- 327 篇 生物工程
- 261 篇 动力工程及工程热...
- 219 篇 仪器科学与技术
- 207 篇 生物医学工程（可授...
- 155 篇 材料科学与工程（可...
- 152 篇 力学（可授工学、理...
- 150 篇 建筑学
- 147 篇 土木工程
- 123 篇 网络空间安全
- 117 篇 环境科学与工程（可...
- 112 篇 交通运输工程
2,958 篇 理学
- 2,035 篇 数学
- 450 篇 物理学
- 396 篇 生物学
- 343 篇 系统科学
- 313 篇 统计学（可授理学、...
- 146 篇 化学
2,039 篇 管理学
- 1,503 篇 管理科学与工程(可...
- 712 篇 工商管理
- 668 篇 图书情报与档案管...
249 篇 医学
- 190 篇 临床医学
- 111 篇 基础医学(可授医学...
173 篇 经济学
- 172 篇 应用经济学
154 篇 法学
85 篇 农学
83 篇 教育学
41 篇 文学
11 篇 军事学
8 篇 艺术学

主题

2,979 篇 distributed comp...
1,753 篇 parallel process...
1,702 篇 concurrent compu...
1,630 篇 cloud computing
1,226 篇 computational mo...
1,084 篇 computer archite...
949 篇 grid computing
932 篇 computer science
791 篇 application soft...
753 篇 computer network...
615 篇 scalability
519 篇 distributed data...
515 篇 algorithm design...
512 篇 hardware
500 篇 peer to peer com...
497 篇 parallel algorit...
487 篇 high performance...
451 篇 software enginee...
451 篇 parallel computi...
439 篇 artificial intel...

机构

52 篇 university of ch...
41 篇 college of compu...
39 篇 institute of com...
37 篇 college of intel...
36 篇 department of co...
31 篇 department of co...
29 篇 school of comput...
28 篇 national laborat...
28 篇 natl univ def te...
27 篇 school of comput...
24 篇 school of comput...
24 篇 shandong provinc...
24 篇 institute of inf...
23 篇 institute of par...
22 篇 univ chinese aca...
21 篇 university of sc...
21 篇 school of comput...
20 篇 shanghai jiao to...
20 篇 department of co...
20 篇 school of comput...

作者

35 篇 li dongsheng
30 篇 liu jie
29 篇 dongsheng li
27 篇 duerr frank
26 篇 m. takizawa
26 篇 rajkumar buyya
26 篇 zomaya albert y.
24 篇 fahringer thomas
21 篇 jack dongarra
19 篇 yang yang
18 篇 li kenli
18 篇 wei li
18 篇 prodan radu
17 篇 wang guojun
17 篇 badia rosa m.
16 篇 liu yang
16 篇 p. banerjee
16 篇 dou yong
15 篇 lei wang
15 篇 xuejun yang

语言

24,330 篇 英文
224 篇 其他
87 篇 中文
17 篇 俄文
2 篇 土耳其文
2 篇 乌克兰文
1 篇 德文
1 篇 西班牙文
1 篇 法文

检索条件"任意字段=International Conference on Advances in Parallel and Distributed Computing"

共 24655 条记录，以下是581-590 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 Private Blockchain-based distributed Ledger Storage Structure for Enhancing Data Security of Academic Documents 14

A Private Blockchain-based Distributed Ledger Storage Struct...

引用

14th international conference on advances in computing, Control, and Telecommunication Technologies, ACT 2023

作者： Kumutha, K. Jayalakshmi, S. Kalpana, Y. Department of computer Applications Tagore College of Arts and Science Chennai India Department of computer Applications VIMT Chennai India Department of Information Technology VISTAS Chennai India

Initially the Blockchain technology was used to implement different digital currencies. Nowadays blockchain is adopted as a common technology to be used in various business applications. Blockchain based solutions have underlying features like security, tamper proof, transparency and consensus. Apart from that, history of data can be maintained on a blockchain network that can be retrieved from any place and at any time. Blockchain provides immutability which is a solution to avoid faking of certificates. This Paper presents a blockchain based solution to issue certificates and prevent fake certification by using digital signature to enhance the data security long with proof of validity smart contract is used to access the blockchain network with valid key. The proposed permissioned blockchain based academic certificate repository system provides and manages degree certificates as assets for educational institutes. Academic certificates and e-certificates can be securely shared and distributed by students and learning institutes through this application. © Grenze Scientific Society, 2023.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Bi-level Sampling: Improved Clients Selection in Heterogeneous Settings for Federated Learning

Bi-level Sampling: Improved Clients Selection in Heterogeneo...

引用

IEEE international Performance, computing, and Communications conference (IPCCC)

作者： Xiao, Danyang Zhan, Congcong Li, Jialun Wu, Weigang Sun Yat Sen Univ Guangzhou Peoples R China

ISBN: (纸本)9798350302936

Client selection (a.k.a., client sampling) is one of the hot topics in Federated Learning (FL). In each communication round, selecting some clients to participate in aggregation can effectively reduce the communication overhead caused by exchanging model parameters. However, due to statistical heterogeneity in FL, selecting clients randomly may affect the performance of aggregated global models. existing approaches regarding client selection firstly cluster clients and then sample(select) some representative clients from each cluster. However, these clusteringbased approaches may be either time-intensive or high complexity. To address these issues, In this paper, we introduce Bi-level Sampling, a clustering-based approach for client selection. After multinomial distribution sampling, Bi-level Sampling clusters clients based on weighted per-label mean class scores and then selects participating clients for federated learning in each round. Bi-level Sampling can lead to better client representativity and the reduced variance of the client's stochastic aggregation weights in FL. Our approach can be integrated into typical FL frameworks. Experimental results show that, compared with state-of-the-art approaches, our approach demonstrates significantly more stable and accurate convergence behavior-getting higher test accuracy and less training time, especially in highly Non-IID settings.

关键词： federated learning clients selection clustering parallel training distributed machine learning

来源：评论

学校读者我要写书评

暂无评论

Formalization and Verification of the Zab Protocol Using CSP 24th

Formalization and Verification of the Zab Protocol Using CSP

引用

24th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2023

作者： Dong, Wenting Yin, Jiaqi Chen, Sini Zhu, Huibiao Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Northwestern Polytechnical University Xi’an China

ISBN: (纸本)9789819982103

ZooKeeper Atomic Broadcast (Zab) is a high-performance atomic broadcast protocol, which is a key component of Apache ZooKeeper. By ensuring strong consistency and fault tolerance, the Zab protocol plays a crucial role in building robust and resilient distributed systems. However, the correctness and reliability of the Zab protocol have received limited attention in research. Thus, we employ Communicating Sequential Processes (CSP) to analyze and evaluate of the Zab protocol’s properties and behavior. We utilize Process Analysis Toolkit (PAT) to verify six important properties, including Deadlock Freedom, Divergence Freedom, Data Reachability, Consistency, Sequentiality and Atomicity. The verification results demonstrate that the Zab protocol provides assurance of correctness and reliability. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fault tolerance

来源：评论

学校读者我要写书评

暂无评论

Serverledge: Decentralized Function-as-a-Service for the Edge-Cloud Continuum 21

Serverledge: Decentralized Function-as-a-Service for the Edg...

引用

21st IEEE international conference on Pervasive computing and Communications (PerCom)

作者： Russo, Gabriele Russo Mannucci, Tiziana Cardellini, Valeria Lo Presti, Francesco Univ Roma Tor Vergata I-00133 Rome Italy

ISBN: (纸本)9781665453783

As the Function-as-a-Service (FaaS) paradigm enjoys growing popularity within Cloud-based systems, there is increasing interest in moving serverless functions towards the Edge, to better support geo-distributed and pervasive applications. However, enjoying both the reduced latency of Edge and the scalability of FaaS requires new architectures and implementations to cope with typical Edge challenges (e.g., nodes with limited computational capacity). While first solutions have been proposed for Edge-based FaaS, including light function sandboxing techniques, we lack a platform with the ability to span both Edge and Cloud and adaptively exploit both. In this paper, we present Serverledge, a FaaS platform designed for the Edge-to-Cloud continuum. Serverledge adopts a decentralized architecture, where function invocation requests can be fully served within Edge nodes. To cope with load peaks, Serverledge also supports vertical (i.e., from Edge to Cloud) and horizontal (i.e., among Edge nodes) computation offloading. Our evaluation shows that Serverledge outperforms Apache OpenWhisk in an Edge-like scenario and has competitive performance with state-of-the-art frameworks optimized for the Edge, with the advantage of built-in support for vertical and horizontal offloading.

关键词： serverless edge computing offloading

来源：评论

学校读者我要写书评

暂无评论

Real-Time Thyroid Nodule Precise MIoT Leveraging Quad-Node Raspberry Pi Clusters and NVIDIA Jetson Nano for Edge AI 3

Real-Time Thyroid Nodule Precise MIoT Leveraging Quad-Node R...

引用

3rd international conference on computing, Communication, Perception and Quantum Technology, CCPQT 2024

作者： Liu, Xian-Xian Tan, Lijian Yang, Jie Department of Computer and Information Science University of Macau China College of Intelligent Manufacturing Chongqing Industry and Trade Polytechnic Chongqing China College of Artificial Intelligence Chongqing Industry and Trade Polytechnic Chongqing China

ISBN: (纸本)9798331528386

This study introduces the thyroid nodule segmentation grid search based local patch learning (GS-LPL) network as an effective IoT solution for real-time, precise thyroid cancer segmentation. Utilizing the Turing PI and NVIDIA Jetson Nano, we developed a quadruple node distributed computing cluster for real-time cancer segmentation through parallel and distributed computing. GS-LPL features a lightweight neural network, optimized for mini-supercomputers, enabling efficient model training and deployment. The NVIDIA Jetson Nano supports real-time high-definition video processing, ideal for low-powered intelligent video analytics like Network Video Recorders (NVR). Our model is also deployable on mobile devices with limited resources. Experimental results validate our model’s fast, efficient, and accurate performance in thyroid nodule cancer segmentation. © 2024 IEEE.

关键词： Cluster computing

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Approach Using Cryptography and K-Least Significant Bit Steganography Algorithm in Cloud computing 1

A Hybrid Approach Using Cryptography and K-Least Significant...

引用

1st international conference on advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Goyal, Anshika Gupta, Bhumika VMSB Uttarakhand Technical University Dept. of Computer Science & Engineering Dehradun India G.B. Pant Institute of Engineering & Technology Dept. of Computer Science & Engineering Pauri India

ISBN: (纸本)9798331518578

The exponential growth of communication technologies has broadened the cloud computing ecosystem horizon to meet main communication needs. However, in-parallel upsurge in online attacks has alarmed industries to ensure optimal data security. The combination of steganography and cryptosystems has been recognized as an enhanced security model for data transfer among the main security systems now in use. In this paper, a hybrid approach using cryptography and K- Least Significant Bit Steganography algorithm in Cloud computing (HYBC-KLSBS-CC) are proposed. Initially, input text data is retrieved from cloud storage and compressed using Huffman Compression Coding (HCC) to reduce data size. The compressed data is then encrypted with a Hybrid Cryptography Algorithm (Hyb-MRFC-ALC), combining Modified Random Fibonacci Cryptography and Asymmetric Lightweight Cryptography to ensure robust encryption. Finally, encrypted data is embedded within an image using the K-Least Significant Bit (KLSB) steganography technique, providing additional layer of security. The proposed method enhances data confidentiality, integrity, and storage efficiency in cloud environments. The proposed HYBC-KLSBS-CC approach attains 26.89%, 29.49% and 18.64% lower PSNR and 26.89%, 29.49% and 18.64% lower MSE when analyzed through existing techniques like data security dependent on cryptography steganography related with OTP procedure and Huffman coding in the cloud environment (CS-OTP-CE), a novel hybrid cryptographic framework for secure data storage in cloud computing: Integrating AES-OTP and RSA with adaptive key management and Time-Limited access control (AES-OTP-RSA-CC) and Crypto-Stegno dependent model for securing medical information on IOMT platform (CS-SMI-IOMT). © 2025 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Maxwell's Demon in Tail-tolerant, Resource-efficient Serverless computing 28

Maxwell's Demon in Tail-tolerant, Resource-efficient Serverl...

引用

IEEE 28th international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Zhang, Huanyu Huang, Wenhao Zhao, Laiping Li, Keqiu Tianjin Univ Coll Intelligence & Comp Tianjin 300350 Peoples R China Tianjin Key Lab Adv Networking TANKLAB Tianjin 300350 Peoples R China

ISBN: (纸本)9781665473156

computing systems always face a "resource allocation dilemma" that shows the great difficulties in trading off resource efficiency for tail latency, due to the internal uncertainty of cluster status and execution behavior. Inspired by the imaginary "Maxwell's demon" in thermodynamics who can reduce the uncertainty through a per-gas molecule-level control policy, we consider the "one-to-one mapping" feature of serverless computing and build a novel resource allocator, named Maxwell, that can achieve low tail latency and high resource efficiency in serverless simultaneously. Like the "Maxwell's demon", Maxwell is able to optimize the resource allocation for every request. It observes the state of each request and makes decisions about the minimum resource allocation through a reinforcement learning predictor. As the per-request-grained control incurs significant overhead, we further design a pipeline for avoiding the accumulated effect on a workflow. Experimental results show that Maxwell not only saves up to 31% CPU resources but also reduces the standard deviation of latency by 1.9x. Its time overhead is negligible and the resource overhead is also limited when the query per second <= 500.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

PASCI : A Scalable Framework for Heterogeneous parallel Calculation of Dynamical Electron Correlation 24

PASCI : A Scalable Framework for Heterogeneous Parallel Calc...

引用

53rd international conference on parallel Processing (ICPP)

作者： Jin, Runfeng Liang, Wenhao Zhang, Haoyuan Song, Yinxuan Luo, Zhen Ma, Haibo Ma, Yingjin Jin, Zhong Chinese Acad Sci Univ Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China Nanjing Univ Nanjing Peoples R China Shandong Univ Sch Chem & Chem Engn Qingdao Inst Theoret & Computat Sci Qingdao Peoples R China Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China

ISBN: (纸本)9798400717932

Accurately calculating the electronic structure of strongly correlated chemical systems necessitates a detailed description of both static and dynamical electron correlations, posing a significant challenge in ab initio quantum chemistry. Although the high memory and computational demands generally limit these calculations to relatively modest systems, the advanced computational capabilities of modern GPUs provide new avenues to expand these limits. However, complex control flows inherent to computation notably impair performance on GPUs. Furthermore, the significant disparity in computational load across different branches leads to load imbalance, challenging the large-scale simulations. In this work, we introduce PASCI, a heterogeneous parallel computing framework designed to quickly and efficiently parallelize the computation of dynamical correlation energy based on determinants. The features of the PASCI framework include (1) a divergence-avoiding GPU algorithm, (2) a three-level load-mapping strategy to ensure load balance across processors, GPU warps, and GPU threads, (3) performance models for memory footprint and computation, and (4) seamless integration with existing quantum chemistry software. Experimental results using an NVIDIA A100 GPU demonstrate that our new GPU algorithm achieves an average 6.6x (up to 13.8x) peak performance increase and 2-4 orders of magnitude speedup in practical usage compared to its original GPU implementation. Moreover, PASCI exhibits excellent scalability, highlighting its potential as a powerful high-performance computing tool in complex quantum chemistry research.

关键词： Quantum Chemistry Computation Load Balancing distributed Heterogeneous Systems GPU Warp Divergence

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning offloading for Computation Cost Minimization of Wireless Powered Mobile Edge computing 24

Deep Reinforcement Learning offloading for Computation Cost ...

引用

2024 international Academic conference on Edge computing, parallel and distributed computing, ECPDC 2024

作者： Yu, Hang Yang, Jun School of Information Engineering Ningxia University Ningxia Yingchuan750021 China

ISBN: (纸本)9798400718168

The development of the Internet of Things has increased the demand for real-time communication and computing in user equipments (UEs), which is a challenge for the limited battery capacity and computing power of UEs. Mobile edge computing (MEC) is a solution for UEs to achieve low delay and low energy consumption by offloading compution-intensive tasks to edge servers. The combination of wireless power transfer (WPT) and MEC further extends the battery lifetime of UEs. Conventional offloading methods are inadequate in adapting to environmental variations and achieving the long-term performance of the wireless powered MEC system with random task requirements and wireless channel states of the UEs. We introduce a deep reinforcement learning framework that takes into account the wireless powered MEC system's long-term average computing cost. We utilize the deep deterministic policy gradient approach to effectively acquire knowledge on optimal task schedule and runtime of the edge server. Additionally, we optimize energy transmission power, offloading time, offloading ratio, and local computation time simultaneously to assess the performance of actions. To enhance exploration of actions, we introduce the differential evolution algorithm which expands and variegate the action generated by the policy network while also accelerating convergence. The simulation outcomes indicate that our proposed scheme outperforms four benchmark strategies in terms of reduced computing costs and accelerated convergence rate. © 2024 ACM.

关键词： Computation offloading

来源：评论

学校读者我要写书评

暂无评论

Strengthening Healthcare Cybersecurity by Optimizing Adversarial Attack Defences in Deep Learning Models using GPU and parallel Processing Technologies 7

Strengthening Healthcare Cybersecurity by Optimizing Adversa...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Venugopal, Hridya Christo, Mary Subaja Kattankulathur Campus SRM Institute of Science and Technology Department of Networking and Communications Tamilnadu Chengalpattu603203 India

ISBN: (纸本)9798350372816

In healthcare, safeguarding patient data integrity is paramount, necessitating robust deep learning models. This research focuses on bolstering the cyber security defenses of these models, particularly against adversarial attacks, through the application of the Localized Adversarial Feature Attack (LAFEAT) technique. Leveraging Graphics Processing Units (GPU) and the TensorFlow framework, the study explores algorithmic enhancements like the Fast Gradient Sign Method (FGSM) and Model-Agnostic Meta-Learning (MAML). These techniques perturb input data gradients or adapt model parameters, enhancing resilience against adversarial perturbations. Additionally, Particle Swarm Optimization (PSO), a metaheuristic optimization technique, is examined to fortify defense mechanisms further. parallel processing techniques, utilizing parallel GPU or distributed clusters, are implemented to expedite the optimization process, reducing computational burdens and enhancing scalability. Despite advancements, gaps remain in understanding how these models can be optimized for real-world healthcare applications, particularly in terms of balancing computational efficiency and robustness. The research demonstrates tangible benefits, with a significant 10% increase in success rates against adversarial attacks compared to baseline methods. Moreover, parallel processing implementation results in a 30% reduction in optimization time, improving the efficiency of cyber security defenses for deep learning models in healthcare. These numerical enhancements underscore the research's value in fortifying healthcare systems against adversarial threats, ensuring the security and integrity of patient data while addressing existing gaps in the optimization of adversarial defenses in healthcare applications. The strengths of this research lie in its robust adversarial attack optimization techniques, integration of parallel processing for efficiency, and application to critical healthcare tasks. Comprehensive

关键词： Graphics processing unit

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 << < 55 56 57 58 59 60 61 62 63 64 > >>

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：