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

1,527 篇 会议
15 篇 期刊文献
7 册 图书

馆藏范围

1,549 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

1,206 篇 工学
- 869 篇 计算机科学与技术...
- 632 篇 软件工程
- 335 篇 信息与通信工程
- 204 篇 电气工程
- 159 篇 电子科学与技术（可...
- 151 篇 生物工程
- 145 篇 控制科学与工程
- 100 篇 机械工程
- 98 篇 生物医学工程（可授...
- 88 篇 动力工程及工程热...
- 84 篇 材料科学与工程（可...
- 82 篇 光学工程
- 75 篇 化学工程与技术
- 72 篇 仪器科学与技术
- 45 篇 交通运输工程
- 45 篇 网络空间安全
- 41 篇 安全科学与工程
- 38 篇 环境科学与工程（可...
616 篇 理学
- 336 篇 数学
- 173 篇 物理学
- 157 篇 生物学
- 107 篇 统计学（可授理学、...
- 93 篇 化学
- 59 篇 系统科学
299 篇 管理学
- 176 篇 管理科学与工程(可...
- 138 篇 图书情报与档案管...
- 97 篇 工商管理
69 篇 医学
- 64 篇 基础医学(可授医学...
- 64 篇 临床医学
- 47 篇 药学(可授医学、理...
41 篇 法学
33 篇 经济学
32 篇 农学
24 篇 教育学
4 篇 军事学
1 篇 文学
1 篇 艺术学

主题

46 篇 cloud computing
45 篇 accuracy
39 篇 computational mo...
32 篇 deep learning
27 篇 support vector m...
26 篇 convolutional ne...
24 篇 computer archite...
22 篇 optimization
21 篇 computer science
21 篇 high performance...
19 篇 real-time system...
19 篇 machine learning
18 篇 object detection
18 篇 resource managem...
18 篇 predictive model...
18 篇 feature extracti...
18 篇 energy efficienc...
16 篇 internet of thin...
16 篇 grid computing
16 篇 servers

机构

20 篇 maharishi school...
14 篇 centre of interd...
12 篇 chitkara univers...
7 篇 school of comput...
7 篇 department of co...
7 篇 department of co...
7 篇 vivekananda glob...
6 篇 school of comput...
6 篇 the islamic univ...
5 篇 university of sc...
5 篇 college of elect...
5 篇 department of co...
5 篇 department of el...
5 篇 school of inform...
5 篇 state key labora...
5 篇 school of softwa...
4 篇 department of el...
4 篇 computer science...
4 篇 college of techn...
4 篇 shri vaishnav in...

作者

7 篇 chauhan rahul
6 篇 zhang tao
6 篇 liu fang
6 篇 yang chao-tung
5 篇 wang lei
5 篇 chao-tung yang
5 篇 rahul chauhan
5 篇 chen peng
4 篇 zhang lei
4 篇 wang jing
4 篇 bhowmik biswajit
4 篇 banerjee deepak
4 篇 biswajit bhowmik
4 篇 liu jie
4 篇 kukreja vinay
4 篇 li shuai
4 篇 gai keke
4 篇 liu shuanfan
4 篇 wang anrong
4 篇 li kuan-ching

语言

1,475 篇 英文
71 篇 其他
8 篇 中文

检索条件"任意字段=3rd International Conference on High Performance Computing in Science and Engineering, HPCSE 2017"

共 1549 条记录，以下是21-30 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：

An Adaptive Task Scheduling Approach for Cloud computing Using Deep Reinforcement Learning 3

An Adaptive Task Scheduling Approach for Cloud Computing Usi...

引用

3rd international conference on Distributed computing and high performance computing, DCHPC 2024

作者： Amini, Pedram Kalbasi, Amir Amirkabir University of Technology Department of Computer Engineering Tehran Iran

ISBN: (纸本)9798350381580

Today, many important internet services are provided on cloud computing platforms. The ever-increasing expansion of services and user requirements has necessitated the optimal use of resources. Therefore, several algorithms for optimal resource usage have been proposed to increase cloud performance and provide more satisfactory services to internet users. Typically, each algorithm is suitable for a specific environment, and their performance is affected by changes of the execution environment. Meanwhile, the assignment of tasks to resources in cloud computing is a difficult problem that NP-Complete. This paper proposes a novel deep reinforcement learning-based approach for task scheduling in cloud computing environments, aiming to minimize the makespan, which is the total time required to complete all tasks. The proposed approach utilizes a deep Q-learning algorithm to learn the near-optimal task allocation strategies based on the current state of the system. The task scheduling performance of the proposed approach is compared with the Min-Min, Min-Max, FCFS and GA algorithms based on three criteria: makespan, algorithm execution time, and computational complexity. Simulation results demonstrate that the proposed approach results in excellent makespan, while demonstrating very small algorithm execution time. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Dynamic Checkpointing: Fault Tolerance in high-performance computing 3

Dynamic Checkpointing: Fault Tolerance in High-Performance C...

引用

3rd international conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Bhowmik, Biswajit Verma, Tushar Dineshbhai, Navdeep Dadhania Reddy, Manideep Raya Vsrs Girish, K.K. National Institute of Technology Karnataka Maharshi Sushrut Cas Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Maharshi Kanad Qc Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Ishwarchandra Vidyasagar Ait Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India

ISBN: (纸本)9798331528201

Parallel computing has become a cornerstone of modern computational systems, enabling the rapid processing of complex tasks by utilizing multiple processors simultaneously. However, the efficiency and reliability of these systems can be significantly compromised by inherent challenges such as hardware failures, communication delays, and uneven workload distribution. These issues not only slow down computations but also threaten the dependability of applications reliant on parallel processing. To address these challenges, researchers have developed strategies like dynamic checkpointing and load balancing, which are crucial for enhancing fault tolerance and optimizing performance. Dynamic checkpointing periodically saves the computational state, allowing for recovery from failures without significant data loss, while load balancing ensures that tasks are evenly distributed across processors, preventing bottlenecks and underutilization of resources. By integrating these mechanisms, this paper proposes a robust framework that improves the reliability and efficiency of parallel systems, particularly in high-performance computing environments where the ability to handle large-scale data processing with minimal downtime is critical. © 2024 IEEE.

关键词： Parallel processing systems

来源：评论

学校读者我要写书评

暂无评论

Small Intestine Cancer Prediction using Deep Learning: A Comparative Study of CNNs and RNNs 3

Small Intestine Cancer Prediction using Deep Learning: A Com...

引用

3rd international conference on Distributed computing and high performance computing, DCHPC 2024

作者： Sherin Beevi, L. Joe Prathap, P.M. Reddy, Pulimi Hanith Sai Kumar Priya, Gomasani Bhanu Sai R.M.D. Engineering College Department of Computer Science and Engineering Kavaraipettai India R.M.D. Engineering College Department of Computer Science and Engineering India

ISBN: (纸本)9798350381580

Small bowel cancer is one of the rare tumors that often stays untreated until it has spread to a more advanced stage. Cancer is the leading cause of death in the globe. Early detection is critical for successful treatment, and machine learning algorithms have showed promise in detecting cancer at its early stages. In this article, we offer a deep learning-based technique to predicting small intestinal cancer that employs Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). We used a dataset of clinical characteristics and biomarkers from small intestinal cancer patients to train and evaluate our models. Our findings reveal that the proposed models were highly accurate in predicting small intestinal cancer, with the CNN-based model slightly outperforming the RNN-based model. We also compared our approach to other cutting-edge methodologies, and discovered that the proposed models surpassed them in terms of accuracy. Our study indicates the potential of deep learning-based approaches for predicting small intestine cancer and provides information on the relative efficacy of CNNs and RNNs. Our findings can help design more accurate and efficient cancer prediction models for small intestinal cancer. © 2024 IEEE.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing the performance of Photonic Crystal AND Gates with Machine Learning Optimization 3

Enhancing the Performance of Photonic Crystal AND Gates with...

引用

3rd international conference on Distributed computing and high performance computing, DCHPC 2024

作者： Parandin, Fariborz Mohammadi, Alireza Islamic Azad University Kermanshah Branch Department of Electrical Engineering Kermanshah Iran Islamic Azad University Kermanshah Branch Department of Computer Engineering Kermanshah Iran

ISBN: (纸本)9798350381580

Recent advances in photonic crystals have opened up new possibilities for developing high-speed, low-power optical devices. One promising application is using photonic crystals to realize AND gates, fundamental building blocks in digital logic circuitry. This paper presents a machine learning-based approach to optimizing the performance of AND gates. We utilize the Extra Trees Regressor model to train on a dataset of simulation results and predict the output power for different input and parameter configurations. Our results show that the model can accurately predict the output power with an RMSE (Root Mean Square Error) of 0.18. We then use the model to identify optimal parameter settings for the radius of the rods and the lattice constant. We find that the optimal parameters are R= 0.05 um and x=0.12 um. The paper further scrutinizes the optimization process for optical gate outputs, leveraging predictions from the Extra Trees Regressor for conditional calculations. It meticulously examines the impact of parameters such as rod radius and lattice constant on gate functionality, emphasizing their role in achieving desired output states. Simulation results elucidate the efficacy of optimized parameters in realizing the behavior of an AND gate within the photonic crystal framework. © 2024 IEEE.

关键词： Lattice constants

来源：评论

学校读者我要写书评

暂无评论

high-performance computing for Accurate Weather Forecast: Leveraging Advanced Algorithms and HPC Systems for Improved Predictions 3

High-Performance Computing for Accurate Weather Forecast: Le...

引用

3rd international conference for Advancement in Technology, ICONAT 2024

作者： Mariappan, Umasree Balakrishnan, D. Karunya, T.Blessing Ponraj, Anitha Abhishekh, P. Devi, R. Karishma P.S.R. Engineering College Department of Information Technology Tamil Nadu Sivakasi626140 India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamil Nadu Krishnankoil626126 India Kalasalingam Academy of Research and Education Department of Information Technology Tamil Nadu Krishnankoil626126 India Academy of Research and Education Department of Electronics and Communication Engineering Kalasalingam Tamil Nadu Krishnankoil626126 India

ISBN: (纸本)9798350354171

high-performance computing (HPC) has revolutionized the field of weather forecasting by enabling the use of advanced algorithms and powerful computing systems to predict weather patterns with greater accuracy. Weather sensors and satellites collect vast amounts of data on temperature, pressure, humidity, wind speed, and precipitation, which are then processed and analyzed in near real-time to generate accurate forecasts. This article highlights the role of HPC in improving weather forecasting by leveraging Scalable Probabilistic Approximation (SPA) and HPC systems. Weather modelling is used to improve our understanding of how processes work in land, oceans, and the atmosphere. It also helps predict weather between days and seasons, as well as weather projection for the future. By leveraging these technologies and techniques, HPC is revolutionizing weather pattern prediction, enabling more accurate and timely forecasts that can help protect lives and livelihoods. high-performance computing and advanced algorithms are crucial for improving the accuracy of weather forecasting. By leveraging these technologies, researchers can better predict weather patterns, which has significant implications for various industries and applications. © 2024 IEEE.

关键词： Wind forecasting

来源：评论

学校读者我要写书评

暂无评论

Hybrid CNN-SSM Network for Efficient and Perceptually Enhanced Super-Resolution 3

Hybrid CNN-SSM Network for Efficient and Perceptually Enhanc...

引用

3rd international conference on Cloud computing, Big Data Application and Software engineering, CBASE 2024

作者： Zheng, Yiyang School of Computer Science and Technology Xidian University Xi'an China

ISBN: (纸本)9798331506582

This paper introduces HybSR, a novel image super- resolution method that leverages the strengths of both Convolutional Neural Networks (CNNs) and State Space Models (SSMs) within a hybrid architecture. CNNs effectively capture local image details, while SSMs offer linear scalability and excel at modeling long-range dependencies. By combining these two paradigms, HybSR achieves a compelling balance between efficiency and performance. Trained with a hybrid loss function encompassing pixel-wise and perceptual components, the model ensures both accurate reconstruction and high visual fidelity. Furthermore, knowledge distillation from a larger teacher network to a smaller student network enhances the model's efficiency. Ex- tensive evaluations on benchmark datasets demonstrate HybSR's superior performance in terms of reconstruction quality, model size, and computational efficiency compared to existing efficient super-resolution methods. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Cloud-Enabled Bio-Inspired Optimization: A Scalable Solution for Complex Real-World Problems 3

Cloud-Enabled Bio-Inspired Optimization: A Scalable Solution...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Shreya Sakthi, U.R. Sruthi, S. Shruti, S.G. Rajganesh, N. Department of Computer Science and Engineering Sri Venkateswara College of Engineering Sriperumbudur India

ISBN: (纸本)9798331527549

Bio-inspired optimization algorithms, encompassing swarm intelligence, neural networks, fuzzy logic, and evolutionary algorithms, are powerful tools for addressing complex real-world optimization problems. However, their effectiveness is often constrained by the computational demands of training and execution, which surpass the capabilities of traditional computing platforms—particularly when dealing with massive datasets or intricate optimization challenges. These limitations restrict the practical applicability of such algorithms. This work introduces a framework that leverages cloud computing as a scalable and efficient platform to overcome these computational barriers. By integrating bio-inspired optimization techniques with the elastic and high-performance resources of cloud environments, this research demonstrates significant improvements in both the scope and efficiency of these algorithms. Experimental results validate the proposed approach, showcasing enhanced performance, reduced execution time, and the ability to solve larger and more complex real-world problems, thereby unlocking the full potential of bio-inspired optimization in practical applications. © 2025 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Leveraging HPC with GAN-CNN Integration for Enhanced Tuberculosis Detection using Synthetic Image Generation 3

Leveraging HPC with GAN-CNN Integration for Enhanced Tubercu...

引用

3rd international conference on Automation, computing and Renewable Systems, ICACRS 2024

作者： Manasa, Pokala Veeramalla, Vaishnavi Vanusha, D. Vathana, D. Robinsha, Delsi S. Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamilnadu Chengalpattu603203 India Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamilnadu Chengalpattu603203 India

ISBN: (纸本)9798331532420

Tuberculosis (TB) remains a significant global health challenge, especially in remote areas with limited medical resources. Early and accurate diagnosis is crucial to control its spread. This project harnesses high-performance computing (HPC) to address two key issues: managing unreliable medical data and improving TB diagnosis. Given the imbalance between healthy and TB-affected samples, Generative Adversarial Networks (GANs) are used to generate synthetic images, enriching the dataset and making it more diverse. This helps train Convolutional Neural Networks (CNNs), which are highly effective in medical image analysis. By leveraging HPC, we accelerate the training of CNNs on large, augmented datasets, significantly reducing processing time while maintaining accuracy. This system improves TB detection by combining GAN-enhanced data and CNN models, enabling faster and more reliable diagnosis. © 2024 IEEE.

关键词： X ray apparatus

来源：评论

学校读者我要写书评

暂无评论

Maximizing Throughput and Minimizing Latency: Evolutionary Algorithms for Optimizing Wireless Cellular Networks 3

Maximizing Throughput and Minimizing Latency: Evolutionary A...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Pechetti, Jyoshitha Yadav, Sneha Tarunya, G. Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

In the rapidly evolving world of wireless cellular network, optimizing key parameters like data throughput and latency is of critical importance for ensuring high quality communication services. The proposed presents a novel approach to multi-objective optimization to enhance overall network performance using Genetic Algorithms (GA), Pareto, and Particle Swarm Optimization (PSO). By employing optimization algorithms, a balance is sought in terms of trade-off of other parameters while maximizing data throughput and minimizing latency. Simulation layers indicate the comparative study further solidifies the efficacy of the value of evolutionary algorithms in optimizing wireless networks to satisfy the growing needs of high speed and less latency services in today’s communication landscape. © 2025 IEEE.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Hybrid Data Security Solutions Using Combined Encryption and Steganography in Communication Systems 3

Hybrid Data Security Solutions Using Combined Encryption and...

引用

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

作者： Chamarthy, Shyamakrishna Siddharth Khan, Imran Sengar, Hemant Singh Krishnamurthy, Satish Goel, Om Al-Farouni, Mohammed Columbia University New York BrooklynNY11226 United States Visvesvaraya Technological University India Shri Vaishnav Institute of Technology and Science India Anna University Chennai India ABES Engineering College U.P. Ghaziabad India The Islamic University Najaf Iraq

ISBN: (纸本)9798331528386

Images, audio, and text files can be steganographically encrypted to conceal secret data. Using the classical logistic chaotic system, this study aims to improve the chaotic behaviour for secure voice encryption. Compared to existing chaotic maps in 1D and 2D, the new approach achieves a broader chaotic range, greater predictability, and improved ergodicity. The paper presents a method for encrypting images using the Henon, Baker, and Arnold maps. ISTFT embeds the encrypted image into the high-frequency harmonics of an audio signal. Analyzing and comparing a sample image to the performance metrics of MSE, PSNR, and SSIM showed that this method had high-performance results. © 2024 IEEE.

关键词： Steganography

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155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：