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

690 篇 会议
3 篇 期刊文献

馆藏范围

693 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

474 篇 工学
- 417 篇 计算机科学与技术...
- 226 篇 软件工程
- 119 篇 信息与通信工程
- 112 篇 电气工程
- 40 篇 控制科学与工程
- 36 篇 电子科学与技术（可...
- 28 篇 生物工程
- 27 篇 动力工程及工程热...
- 18 篇 安全科学与工程
- 17 篇 光学工程
- 17 篇 生物医学工程（可授...
- 16 篇 交通运输工程
- 15 篇 机械工程
- 15 篇 化学工程与技术
- 13 篇 材料科学与工程（可...
- 11 篇 环境科学与工程（可...
- 11 篇 网络空间安全
- 10 篇 仪器科学与技术
142 篇 理学
- 78 篇 数学
- 33 篇 物理学
- 31 篇 生物学
- 25 篇 统计学（可授理学、...
- 17 篇 系统科学
- 13 篇 化学
104 篇 管理学
- 69 篇 管理科学与工程(可...
- 45 篇 图书情报与档案管...
- 37 篇 工商管理
16 篇 法学
- 11 篇 社会学
16 篇 医学
- 13 篇 基础医学(可授医学...
- 13 篇 临床医学
7 篇 经济学
4 篇 农学
3 篇 教育学
1 篇 军事学

主题

50 篇 cloud computing
32 篇 computational mo...
32 篇 distributed comp...
28 篇 accuracy
23 篇 grid computing
19 篇 computer archite...
18 篇 high performance...
18 篇 distributed comp...
17 篇 concurrent compu...
17 篇 resource managem...
15 篇 training
14 篇 internet of thin...
14 篇 software enginee...
14 篇 costs
14 篇 computer network...
14 篇 distributed data...
13 篇 quantum computin...
13 篇 big data
13 篇 data models
12 篇 real-time system...

机构

5 篇 college of techn...
5 篇 sr university de...
4 篇 school of electr...
4 篇 school of softwa...
3 篇 china electric p...
3 篇 college of compu...
3 篇 irisa rennes
3 篇 zhengzhou univer...
2 篇 state grid econo...
2 篇 department of in...
2 篇 school of geomat...
2 篇 department of cs...
2 篇 information tech...
2 篇 school of comput...
2 篇 school of medica...
2 篇 guangzhou south ...
2 篇 department of ic...
2 篇 univ essex dept ...
2 篇 university of ca...
2 篇 henan univ inst ...

作者

4 篇 zhang tao
3 篇 li kuan-ching
3 篇 li hui
3 篇 yang chao-tung
2 篇 altam mohammed
2 篇 li kedan
2 篇 hemant singh sen...
2 篇 pareek piyush ku...
2 篇 xiangyu liu
2 篇 rahul jagtap
2 篇 xiong ke
2 篇 jia yan
2 篇 zhijun wang
2 篇 mengxin liu
2 篇 zomaya albert y.
2 篇 chen liu
2 篇 lv zhuoheng
2 篇 hongyuan gao
2 篇 liu yun
2 篇 pratheesh r.

语言

661 篇 英文
31 篇 其他
5 篇 中文

检索条件"任意字段=3rd International Conference on Distributed Computing and High Performance Computing, DCHPC 2024"

共 693 条记录，以下是1-10 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：

2024 3rd international conference on distributed computing and high performance computing, dchpc 2024

2024 3rd International Conference on Distributed Computing a...

引用

3rd international conference on distributed computing and high performance computing, dchpc 2024

ISBN: (纸本)9798350381580

The proceedings contain 21 papers. The topics discussed include: enhancing the performance of photonic crystal and gates with machine learning optimization;bitcoin price prediction based on financial data, technical indicators, and news headlines sentiment analysis using CNN and GRU deep learning algorithms;promoting cybersecurity knowledge via gamification: an innovative intervention design;modeling and verification of the causal broadcast algorithm using colored Petri Nets;GPU-based parallel technique for solving n-similarity problem in textual data mining;a novel approach for specification and verification of symmetric distributed algorithms using spin;optimizing geophysical workloads in high-performance computing: leveraging machine learning and transformer models for enhanced parallelism and processor allocation;and rational Jacobi kernel functions: a novel massively parallelizable orthogonal kernel for support vector machines.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Proceedings of IPDRM 2019: 3rd Annual Workshop on Emerging Parallel and distributed Runtime Systems and Middleware - Held in conjunction with SC 2019: The international conference for high performance computing, Networking, Storage and Analysis

Proceedings of IPDRM 2019: 3rd Annual Workshop on Emerging P...

引用

3rd IEEE/ACM Annual Workshop on Emerging Parallel and distributed Runtime Systems and Middleware, IPDRM 2019

ISBN: (纸本)9781728159935

The proceedings contain 6 papers. The topics discussed include: assessing the performance impact of using an active global address space in HPX: a case for AGAS;sequential codelet model of program execution - a super-codelet model based on the hierarchical turing machine;ADVERT: an asynchronous runtime for fine-grained network systems;design and evaluation of shared memory communication benchmarks on emerging architectures using MVAPICH2;characterizing the performance of executing many-tasks on summit;and leveraging network-level parallelism with multiple process-endpoints for MPI broadcast.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detection of DDoS Attacks in Fog computing using Interpretable Quantum-based 2Q Learning Approach 3

Detection of DDoS Attacks in Fog Computing using Interpretab...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Sohan Jayram Reddy, K. Bhargavi, K. Siddaganga Institute of Technology Department of Computer Science and Engineering Karnataka Tumakuru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

It is seen that there is a rapid increase in Internet of Things (IoT) devices, and fog computing has emerged as an efficient and viable solution to reduce latency by performing computations closer to the edge. However, this nature of fog computing makes it vulnerable to distributed Denial of Service (DDoS) attacks, which can disrupt services. DDoS causes major impact over the fog performance which include resource saturation, increased latency, reduced resource availability, decrease in processing capacity of the fog nodes, and many more. There have been various works proposed to detect DDoS attacks in fog computing, but they lack scalability and have high response times. In this paper, a novel Quantum-based-2QLearning (Q2QL) framework is designed to efficiently detect and mitigate DDoS attacks in fog computing. This framework using quantum-enhanced reinforcement learning reduces overestimation bias and improve speed of convergence. Q2QL framework also achieves high detection accuracy and reduces response time. The results show that the proposed framework performs well across critical metrics, including latency, attack detection time, and overall system performance. © 2025 IEEE.

关键词： Fog computing

来源：评论

学校读者我要写书评

暂无评论

Real-Time Monitoring and Response System for Virtual Power Plants Based on distributed computing 24

Real-Time Monitoring and Response System for Virtual Power P...

引用

3rd international conference on Algorithms, Data Mining, and Information Technology, ADMIT 2024

作者： Lin, Hua Sun, Kangnan Zhang, Kai Wu, Heng SPIC ShanDong Energy Marketing CO.LTD Shandong Jinan China Suzhou Qingshi Botong IoT Technology Co. Ltd Jiangsu Suzhou China

ISBN: (纸本)9798400718120

A smart operation and maintenance management system for photovoltaic power plants based on big data technology has emerged. The system adopts a distributed architecture, achieving key functions such as real-time data collection, efficient transmission, distributed storage, and real-time processing of plant equipment. It integrates multiple machine learning algorithms for intelligent analysis and prediction of generation capacity, equipment health status, and fault types, thereby enhancing operational accuracy and efficiency. Moreover, the system provides web and mobile interfaces for real-time monitoring of plant operations. During system development, comprehensive tests were conducted on cluster load capacity and data processing latency, leading to targeted optimizations of system configurations to ensure high-concurrency processing capabilities in production environments. The successful implementation of this system underscores the vast application prospects of big data technology in the renewable energy sector and its significant role in advancing intelligent operation and maintenance of photovoltaic power plants. © 2024 Copyright held by the owner/author(s).

关键词： photovoltaic power plants

来源：评论

学校读者我要写书评

暂无评论

Intelligent Image Captioning with InceptionV3, LSTM, and PySpark Integration 3

Intelligent Image Captioning with InceptionV3, LSTM, and PyS...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Kurian, Thanu Mathew, Jimsha K. Syam Dev, R.S. Anand, P.K. Vignesh, A. Rakshith, B.S. New Horizon College of Engineering Dept of Artificial Intelligence and Machine Learning Bengaluru India

ISBN: (纸本)9798331515911

Image captioning is a challenging task in artificial intelligence that involves generating descriptive captions for images automatically. In this project, we propose a novel approach leveraging advanced technologies such as PySpark, LSTM, and InceptionV3 to develop an effective image captioning system. We harness the power of PySpark, a distributed computing framework, to efficiently process large-scale image datasets and extract high-level features from images using the InceptionV3 convolutional neural network (CNN) model. These features capture the semantic information present in the images and serve as input to the caption generation model. The caption generation model utilizes LSTM neural network as the decoder component. LSTM is well-suited for sequential data processing and is capable of generating coherent and contextually relevant captions based on the extracted image features. The InceptionV3 model acts as the encoder, extracting meaningful visual features from input images, while the LSTM decoder generates captions by decoding these features into natural language descriptions. This multimodal approach enables the model to understand and describe the content of images accurately. Through experimentation and evaluation on diverse image datasets, our proposed system demonstrates promising results in generating accurate and human-like captions for a wide range of images. By integrating PySpark, LSTM, and InceptionV3, our image captioning system achieves state-of-the-art performance, highlighting the effectiveness of leveraging advanced technologies in solving complex AI tasks. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

computing Power Detection Based on Smart Contract 3

Computing Power Detection Based on Smart Contract

引用

3rd international conference on Electrical, Electronics, and Information Engineering, EEIE 2024

作者： Liu, Shaowei Liu, Xue Long, Chengnian School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Jiangsu Automation Research Institute Lianyungang China

ISBN: (纸本)9781510688179

As blockchain technology is widely applied across various fields, the performance requirements of blockchain systems, such as throughput and transaction latency, are increasing. In this context, blockchain systems have gradually evolved to adopt a two-phase consensus protocol that involves election and block generation. By electing a small number of nodes from a large-scale network to form a committee, a more efficient internal consensus protocol can be executed, thereby improving the overall performance of the blockchain system. This paper proposes a node performance detection method based on smart contracts, which sets performance thresholds for committee nodes without compromising the decentralization of public chains. This ensures high performance, low latency, and enhances the reliability of the consensus protocol. © The Authors.

关键词： Blockchain Consensus Election performance Detection Smart Contract

来源：评论

学校读者我要写书评

暂无评论

Model Migration and Joint Communication and computing Resource Allocation in Native AI Wireless Networks 3rd

Model Migration and Joint Communication and Computing Resour...

引用

3rd international conference on Machine Learning, Cloud computing and Intelligent Mining, MLCCIM 2024

作者： He, Zhimin Deng, Juan Li, Yaru Wang, Xiaoyun China Mobile Research Institute Beijing China ZGC Institute of Ubiquitous-X Innovation and Applications Beijing China China Mobile Communications Group Corporation Beijing China

ISBN: (纸本)9789819616930

As artificial intelligence (AI) continues to drive industrial upgrading, the demands for efficient and real-time AI services have escalated. However, meeting these demands poses challenges, particularly within the framework of 5G networks, where the infrastructure for providing AI services lacks real-time collaborative control over the required resources, such as the limited communication, computing and model resources. Anticipating the future of 6G networks, this paper advocates for the design with native AI integration from inception, leveraging wireless network infrastructure for ubiquitous real-time AI services. In this case, we address the issue of limited computing, model resources by proposing a distributed optimal resource utilization model migration algorithm. Additionally, a joint communication and computing resources allocation algorithm, based on a greedy strategy, is introduced to enhance resource utilization and support a higher number of AI inference tasks. Simulation results demonstrate that the performance of the proposed algorithm can approach the exhaustive search scheme at lower computational complexity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Efficient acne classification based on Resnet18 3

Efficient acne classification based on Resnet18

引用

3rd international conference on Algorithms, Network, and Communication Technology, ICANCT 2024

作者： Cheng, Shi Sun, Mingze Huang, Zhongyi Wang, Yushan Fu, Jiaxuan School of Engineering University of Manchester ManchesterM13 9PL United Kingdom School of Computing Science University of Glasgow GlasgowG12 8RZ United Kingdom School of Data Science and Big Data Nanjing Institute of Technology Nanjing210000 China The Affiliated High School Renmin University of China Beijing100083 China International Department Nanjing Jinling High School Nanjing21000 China

ISBN: (数字)9781510688902

ISBN: (纸本)9781510688896

In this study, we investigated the mechanical performance of lightweight composite slabs, specifically focusing on the application of an integrated face recognition and acne classification pipeline. We propose a comprehensive approach that commences with facial detection, proceeds to the acne region localization, and concludes with acne classification utilizing ResNet18 architecture. The aim is to develop a highly accurate and efficient system for acne classification, particularly beneficial for remote patients or those seeking a convenient self-assessment tool. Our dataset, though limited in size and diversity, is iteratively refined and augmented to mitigate data scarcity issues. Through experimental evaluations, we demonstrate that the combination of ResNet18 and Support Vector Machine (SVM) achieves an accuracy rate of 96%, significantly outperforming traditional manual feature extraction methods. Additionally, visualization techniques such as Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE) are employed to gain insights into the data distribution and the effectiveness of automatically extracted features. This study highlights the potential of deep learning for acne detection and underscores the importance of dataset refinement for enhancing model performance. © 2025 SPIE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

XMeta-OS: A Conceptual Framework for Unified Resource Management in distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

引用

3rd international conference on Advances in computing Research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

来源：评论

学校读者我要写书评

暂无评论

Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation 2nd

Quantifying the Impact of Population Shift Across Age and...

引用

2nd international Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and 3rd international Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with the international conference on Medical Image computing and Computer Assisted Interventions, MICCAI 2024

作者： Čevora, Kate Glocker, Ben Bai, Wenjia Department of Computing Imperial College London London United Kingdom Department of Brain Sciences Imperial College London London United Kingdom Data Science Institute Imperial College London London United Kingdom

ISBN: (纸本)9783031727863

Deep learning-based medical image segmentation has seen tremendous progress over the last decade, but there is still relatively little transfer into clinical practice. One of the main barriers is the challenge of domain generalisation, which requires segmentation models to maintain high performance across a wide distribution of image data. This challenge is amplified by the many factors that contribute to the diverse appearance of medical images, such as acquisition conditions and patient characteristics. The impact of shifting patient characteristics such as age and sex on segmentation performance remains relatively under-studied, especially for abdominal organs, despite that this is crucial for ensuring the fairness of the segmentation model. We perform the first study to determine the impact of population shift with respect to age and sex on abdominal CT image segmentation, by leveraging two large public datasets, and introduce a novel metric to quantify the impact. We find that population shift is a challenge similar in magnitude to cross-dataset shift for abdominal organ segmentation, and that the effect is asymmetric and dataset-dependent. We conclude that dataset diversity in terms of known patient characteristics is not necessarily equivalent to dataset diversity in terms of image features. This implies that simple population matching to ensure good generalisation and fairness may be insufficient, and we recommend that fairness research should be directed towards better understanding and quantifying medical image dataset diversity in terms of performance-relevant characteristics such as organ morphology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image segmentation

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70页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：