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

2,092 篇 期刊文献
1,486 篇 会议
36 册 图书

馆藏范围

3,614 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,072 篇 工学
- 1,469 篇 计算机科学与技术...
- 1,203 篇 软件工程
- 429 篇 信息与通信工程
- 350 篇 生物工程
- 302 篇 生物医学工程（可授...
- 262 篇 控制科学与工程
- 238 篇 光学工程
- 221 篇 电气工程
- 138 篇 电子科学与技术（可...
- 137 篇 化学工程与技术
- 99 篇 机械工程
- 85 篇 安全科学与工程
- 77 篇 网络空间安全
- 76 篇 动力工程及工程热...
- 74 篇 仪器科学与技术
1,580 篇 理学
- 651 篇 数学
- 645 篇 物理学
- 416 篇 生物学
- 245 篇 统计学（可授理学、...
- 182 篇 化学
- 110 篇 系统科学
603 篇 管理学
- 319 篇 管理科学与工程(可...
- 308 篇 图书情报与档案管...
- 184 篇 工商管理
316 篇 医学
- 264 篇 临床医学
- 227 篇 基础医学(可授医学...
- 142 篇 药学(可授医学、理...
- 120 篇 公共卫生与预防医...
112 篇 法学
- 91 篇 社会学
76 篇 经济学
- 76 篇 应用经济学
57 篇 农学
49 篇 教育学
8 篇 文学
5 篇 军事学
2 篇 历史学
1 篇 哲学
1 篇 艺术学

主题

130 篇 deep learning
129 篇 accuracy
115 篇 machine learning
78 篇 feature extracti...
75 篇 hadrons
73 篇 training
69 篇 data models
66 篇 artificial intel...
66 篇 convolutional ne...
61 篇 real-time system...
57 篇 semantics
55 篇 computational mo...
53 篇 predictive model...
50 篇 hadron colliders
46 篇 hadronic decays
44 篇 internet of thin...
43 篇 support vector m...
42 篇 optimization
42 篇 visualization
40 篇 data mining

机构

427 篇 department of ph...
410 篇 horia hulubei na...
404 篇 van swinderen in...
401 篇 school of physic...
400 篇 iccub universita...
398 篇 h.h. wills physi...
398 篇 cavendish labora...
381 篇 yandex school of...
381 篇 department of ph...
375 篇 imperial college...
362 篇 university of ch...
355 篇 stfc rutherford ...
353 篇 center for high ...
348 篇 institute of par...
323 篇 henryk niewodnic...
316 篇 nikhef national ...
297 篇 school of physic...
297 篇 physik-institut ...
294 篇 oliver lodge lab...
289 篇 school of physic...

作者

252 篇 barter w.
249 篇 bellee v.
241 篇 beiter a.
224 篇 casse g.
222 篇 bowcock t.j.v.
217 篇 blake t.
216 篇 borsato m.
216 篇 betancourt c.
216 篇 amato s.
215 篇 bediaga i.
215 篇 boettcher t.
210 篇 brundu d.
210 篇 baryshnikov f.
207 篇 braun s.
205 篇 borisyak m.
202 篇 bizzeti a.
195 篇 bencivenni g.
190 篇 back j.j.
189 篇 bay a.
174 篇 bursche a.

语言

3,265 篇 英文
338 篇 其他
13 篇 中文
3 篇 德文
2 篇 法文
2 篇 斯洛文尼亚文
1 篇 日文
1 篇 俄文

检索条件"机构=Faculty for Computer Science and Data Science"

共 3614 条记录，以下是771-780 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：

The Utilization of Google Cloud in the Healthcare Industry

The Utilization of Google Cloud in the Healthcare Industry

引用

Machine Learning and Autonomous Systems (ICMLAS), International Conference on

作者： Rishikesh Kapse Palash Gourshettiwar Dept. of Artificial Intelligence and Data Science Faculty of Engineering and Technology DMIHER (DU) Sawangi(M) Wardha Maharashtra Dept. of Computer Science And Medical Engineering Faculty of Engineering and Technology DMIHER (DU) Sawangi(M) Wardha Maharashtra

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

This essay's primary focus is on Google Cloud's use in healthcare and how it affects data management, teamwork, and cost-effectiveness. With a focus on Google Cloud, which improves the processing, storing, and accessibility of medical data, the study examines the trends, advantages, and persistent challenges that come with the increasing usage of cloud computing technology. These consist of remote patient monitoring, “artificial intelligence,” and “machine learning” applications in diagnostics, diagnostics, and personalized medicine. data privacy, security issues, and concerns with the HIPAA incident are among the problems that are discussed along with all the significant elements that could facilitate the cloud migration of healthcare.

关键词： Industries Cloud computing data privacy Technological innovation Medical services Machine learning Teamwork Security Predictive analytics Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

Enhancing Business Intelligence Through A Semi-Distributed Blockchain Framework for Predictive Analytics On Sales Growth 2

Enhancing Business Intelligence Through A Semi-Distributed B...

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Mullaikodi, C. Jagannathan, Sharath Kumar Jayanthi, N. Singh, Rakhi Tomar, Yesha Jaison, B. J. N. N Institute of Engineering Department of Ece Tamilnadu Tiruvallur India Data Science Institute Saint Peter's University NJ United States Chennai India Sgt University Faculty of Commerce and Management Haryana Gurugrm India School of Management Doon University Uttarakhand Dehradun India Rmk Engineering College Department of Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350371055

The cutting-edge technologies in the ever-evolving sector of data analytics has been accelerated by the requirement for efficient and secure techniques of acquiring business intelligence. This approach provides a solution to the existing issues. In order to address the issues of data integrity, security, and transparency that are associated with the existing methodologies, there is a need for a paradigm shift that will lead to a solution that is more resilient. The traditional centralised data analytics solutions have their limitations when it comes to guaranteeing the accuracy and dependability of forecasts, and this is the most important aspect of the situation. A semi-distributed blockchain paradigm is proposed as a solution to the problems that are associated with centralised systems. This paradigm spreads the computing burden while maintaining a certain degree of decentralisation in order to enhance security. The approach that is currently being considered is the construction and deployment of a blockchain network that is semi-distributed and contains data analytics techniques. Smart contracts simplify the processes of data transmission and validation among participants, hence ensuring transparency and confidence in the predictive analytics model. These findings reveal an improvement in the system efficiency, data quality, and accuracy of forecasting. © 2024 IEEE.

关键词： Business Intelligence Predictive Analytics Sales Growth Semi-Distributed Blockchain Smart Contracts

来源：评论

学校读者我要写书评

暂无评论

A Novel Convolutional-Transformer Neural Network Architecture for Diagnosis of Pneumothorax

A Novel Convolutional-Transformer Neural Network Architectur...

引用

International CSI computer Conference, CSICC

作者： Amir Sanati Mansoureh A. Dashtestani Habib Rostami Saeed Talatian Azad Computer Engineering Department Faculty of Intelligent System Engineering and Data Science Persian Gulf University Bushehr Iran

Pneumothorax is a life-threatening and urgent chest disease than can be detected using Chest X-Ray (CXR) image. CXR images are low resolution and diagnosis of pneumothorax based on them is error prone. Deep learning-based computer aided diagnosis systems can improve diagnosis performance of pneumothorax. Convolutional Neural Networks (CNNs) are default networks in deep learning-based medical image process. However, CNNs fail to capture long range features. On the other side, Transformer are proposed to exploit long range feature, but they cannot capture local features. In this paper, we propose a general method with a convolution and a transformer module which can classify CXR images to diagnose pneumothorax by extracting local features, global features and global features attended by local ones using a novel architecture. Results show that the proposed method outperforms base architectures and the other previous works.

关键词： Image resolution Convolution Neural networks computer architecture Feature extraction Transformers Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Multi-modal Fusion and 1D-CNN Based Elderly Fall Risk Prediction during Treadmill Walking

Multi-modal Fusion and 1D-CNN Based Elderly Fall Risk Predic...

引用

Smart World Congress (SWC), IEEE

作者： Xuan Huang Bo Wu Xiaokang Zhou Shoji Nishimura Faculty of Human Sciences Waseda University Tokorozawa Japan School of Computer Science Tokyo University of Technology Hachioji Japan Faculty of Business Data Science Kansai University Osaka Japan RIKEN Center for AIP Tokyo Japan

ISBN: (数字)9798331520861

ISBN: (纸本)9798331520878

In today’s society, there has been an increase in the number of accidents among the elderly (60 and over) in places such as health clubs, where the main cause of accidents is due to the loss of balance on treadmills. However, traditional solutions are inefficient while consuming human resources and lagging in their inability to predict effectively and prevent upcoming accidents. A user-friendly system that can detect the movement status of the elderly in real-time and predict and alarm the fall risk is needed. Therefore, to protect the safety of the elderly when using the treadmill, in this paper we design a set of elderly exercise experiments at an elderly welfare center in Japan and propose a multi-modal fusion and 1D-CNN based elderly fall risk prediction system to integrate the short-term (e.g., skeletal features and plantar pressures in five minutes) and long-term (e.g., heart rate and sleep quality for three months) data. Finally, we have shown and discussed an application scenario with the simulation of our proposed system. The system will optimize the elderly users’ exercise experience when exercising on a treadmill, reduce the risk of falls, and provide guidance for the design of future fitness equipment for the elderly.

关键词： Legged locomotion Heart rate Wearable Health Monitoring Systems Predictive models Real-time systems Safety Older adults Usability Accidents Sports

来源：评论

学校读者我要写书评

暂无评论

Re-rank Search Engine Results via Machine Learning

Re-rank Search Engine Results via Machine Learning

引用

International Conference on Web Research (ICWR)

作者： Amir Hussein Ataei Monfared Amir Hossein Avizheh Faculty of Mathematical Sciences and Computer Kharazmi University Tehran Iran Department of Data and Computer Science Shahid Beheshti University Tehran Iran

Research on search engines has demonstrated their significant impact on information search and user behavior and highlighted the need for continued investigation of their effectiveness, efficiency, and ethical implications. Moreover, search engine optimization (SEO) has emerged as a crucial aspect of online content creation and marketing, as it involves optimizing websites and online materials to improve their visibility and ranking on search engine results pages, thereby increasing their reach and impact. SEO metrics provide valuable insight into a website’s search engine performance. However, the relative importance of these metrics remains unclear as search engine algorithms and keyword competitiveness can vary widely. Therefore, ongoing research is needed to better understand the relationship between SEO metrics and search engine rankings. Given the challenge of determining the relative importance of SEO metrics using traditional statistical methods, interested in applying machine learning techniques. By training models with custom datasets of three search engine results (Google, Bing, and DuckDuckGo) and their associated SEO metrics, we hope to gain a better understanding of the complex relationships between these variables. The first two pages of each search engine return the most relevant results. In this article, we propose two types of methods to do this. First, classify the page index of web search results. Second, learning ranking methods to rank them. LambdaRank has the best NDCG compared to other methods for Google and DuckDuckGo which are 0.86 and 0.93 respectively. RankNet is the best learning-to-rank method for Bing with 0.85 as the NDCG value. Logistic regression has the highest accuracy compared to other methods in page index classification for Bing and Google, which are 61.29% and 64.71%, respectively. K-nearest neighbor performs best for DuckDuckGo with an accuracy of 66.67%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An FL-based Energy-Efficient Opportunistic Intelligent Node Selection Scheme for Healthcare IoV Applications

An FL-based Energy-Efficient Opportunistic Intelligent Node ...

引用

International Communication Systems and Networks and Workshops, COMSNETS

作者： Pallati Narsimhulu Rashmi Sahay Symbiosis Institute of Technology Hyderabad Campus Symbiosis International (Deemed University) Pune India Department of Computer Science and Engineering Faculty of Science and Technology (IcfaiTech) The ICFAI Foundation for Higher Education Hyderabad India Department of Data Science and Artificial Intelligence Faculty of Science and Technology (IcfaiTech) The ICFAI Foundation for Higher Education Hyderabad India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

The complexity of managing the energy and operational needs in large-scale Wireless Sensor Networks (WSNs) emphasizes the importance of energy-aware routing. This paper proposes an energy-efficient routing protocol that uses an intelligent node selection scheme to address energy-aware routing in the healthcare Internet of Vehicles (IoV). The protocol identifies the most suitable cluster leader based on dynamic criteria. By building on a ranking system that considers factors like location and remaining energy, the protocol selects the next intelligent node to establish the most energy-efficient route within the Internet of Things (IoT) context. The energy-aware routing scheme is tested across various clustering systems to evaluate its impact on route discovery based on system size and time. Experimental results show that the model reduces energy consumption during broadcast operations. Performance metrics such as Jitter and Packet Loss Ratio (PLR) further illustrate the protocol’s energy optimization. Simulation results across diverse network conditions demonstrate the superiority of adaptive ranking and intelligent forwarder node selection over competing strategies. Overall, the proposed protocol presents a promising solution for achieving energy-efficient routing in IoV, offering insights into optimized strategies and their benefits for IoT applications.

关键词： Wireless sensor networks Simulation Packet loss Medical services Jitter Routing Routing protocols Energy efficiency Vehicle dynamics Optimization

来源：评论

学校读者我要写书评

暂无评论

Exploring Reinforcement Learning in Large-Scale data Processing 3

Exploring Reinforcement Learning in Large-Scale Data Process...

引用

3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Bhambu, Pawan Kumar, Ritesh Sharmila, P. Patil, Vivek D. Khurana, Shivam Vivek, V. Vivekananda Global University Department of Computer Science & Engineering Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Computer Science and Engineering Faculty of Engineering and Technology Karnataka Bangalore India

ISBN: (纸本)9798350319125

Reinforcement mastering (RL) is vital for big-scale fast processing. RL utilizes the availability of large datasets and dealers skilled in this information to remedy a wide variety of obligations, from automated diagnostics and self-reliant using structures to clinical information analysis. Using exploiting the traits of the modern-day significant information era, RL allows efficient and correct decision-making in massive-scale information processing and answers complicated troubles. This paper explores the use of reinforcement learning (RL) in large-scale data processing. RL is a subfield of machine learning that focuses on decision making in dynamic environments. With the increasing demand for processing large amounts of data, traditional techniques such as rule-based systems and batch processing are becoming inadequate. This has led to the emergence of RL as a potential solution due to its ability to learn and adapt to changing environments. Through a comprehensive review of existing literature, this paper discusses the applications of RL in large-scale data processing and its potential benefits. Furthermore, it examines various challenges and their potential solutions in implementing RL for data processing tasks. The paper concludes by highlighting the future research directions in this domain and the potential impact of RL on improving data processing efficiency and accuracy. It similarly examines some of the demanding situations and possibilities related to using RL for huge-scale records processing and the capability programs of RL in the future. © 2023 IEEE.

关键词： applications challenges opportunities potential processing

来源：评论

学校读者我要写书评

暂无评论

Utilizing Dynamic Spectrum Allocation to Optimize Capacity in High-Speed Fiber Optic Communications 3

Utilizing Dynamic Spectrum Allocation to Optimize Capacity i...

引用

3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Narmadha, T. Sahoo, Laxman Yadav, Dhananjay Sharmila, P. Mahalle, Parikshit N. Parmar, Yuvraj Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350319125

Dynamic spectrum allocation can extensively improve the ability of high-speed fiber optic communications, permitting Fiber-to-the-home (FTTH) and different deployments to be optimized for max performance. This approach makes use of a decentralized approach to allocate spectrum resources on demand, taking into account scalability and efficient aid usage. With the aid of the use of a restrained set of hardware and software, dynamic spectrum allocation can quick and correctly update the communications community to meet changing demands. This generation takes gain of the increasingly more sophisticated optical additives available these days to alter the spectrum in real time rather than relying on static allocation algorithms. This capability reduces the want to frequently reassign spectrum allocations, in addition to the amount of time and sources it requires, permitting the communications network to be managed and controlled extra efficiently and efficiently. Moreover, dynamic spectrum allocation improves the overall performance of current fiber communications structure with the aid of better using current optical components, which may be applied retroactively. © 2023 IEEE.

关键词： Communications Decentralized Dynamic Retroactively Sophisticated

来源：评论

学校读者我要写书评

暂无评论

Intelligent Predictive Model for Hepatitis C

Intelligent Predictive Model for Hepatitis C

引用

Artificial Intelligence (ICAI), International Conference on

作者： Mehreen Shahzadi Faisal Bukhari Numan Shafi Department of Data Science Faculty of Computing & Information Technology University of the Punjab Lahore Pakistan Department of Computer Science University of Engineering and Technology Lahore Pakistan

Hepatitis C is the liver's festering that can lead to severe liver damage, usually caused by the hepatitis C virus. Hepatitis C has different stages. It is tough to cure in it's last stages; at the same time, it is expensive and painful process. The current research, however, is an alternative precaution to this issue. Hepatitis C can be predicted early by using multiple factors. The dataset related to hepatitis C was not publicly available. To overcome this challenge, the healthy and HCV effected samples were collected from different hospitals in Punjab. A questionnaire based survey was taken including different HCV related factor i.e. gender, weight loss, hives/ rashes, swelling, jaundice, drug addiction history, hepatic encephalopa-thy (drowsiness, slurred speech), Ascites (fluid buildup in belly/ abdomen), spider angiomas (Spiderlike blood vessels), shared syringe usage, medical history, and severeness. Different cleaning, scaling, and feature selection techniques were applied to collect the best feature data. After selection, various machine learning algorithms were applied. Random forest, KNN, Decision Tree, SVC, and MLP were used, but MLP yielded optimal results in all classification algorithms. We have gained 95.9 % accuracy when tested on unknown data based on the MLP model. As the predictions' results were satisfactory, it would be helpful for the people and act as a critical awareness.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Hybrid Agile Model, the Synergy of Waterfall Model and Scrum in a Software Project

Hybrid Agile Model, the Synergy of Waterfall Model and Scrum...

引用

Information Technology and Digital Applications (ICITDA), IEEE International Conference on

作者： Norzariyah Yahya Abdul Muizz Abdul Salam Siti Sarah Maidin Normi Sham Awang Abu Bakar Department of Computer Science Kulliyyah of Information and Communication Technology International Islamic University Malaysia Kuala Lumpur Malaysia Faculty of Data Science and Information Technology (FDSIT) INTI International University Malaysia

ISBN: (数字)9798331510732

ISBN: (纸本)9798331510749

Hybrid agile is one of the recent software engineering process model used by a software engineering team in a software development project. A hybrid agile model is used by software engineering team to meet the requirements of a software project. However, what does the hybrid agile model used by a software engineering team look like? A qualitative study was conducted to answer this question, and a series of interviews were chosen as a data collection instrument. The interview participants are practitioners involved in software projects using hybrid agile. The recorded interviews are transcribed and analysed using thematic analysis. The finding shows that the software engineering team uses the Waterfall model in the planning, design, deployment and maintenance phases, while scrum in the development and testing phases. The results have led to the hybrid agile model presented in this study, which leverages the strengths of each model to ensure the completion of a software project. Future iterations of this study will assess a project's software quality, comparing the proposed model with plan-driven and scrum.

关键词： Instruments Software quality Planning Maintenance Scrum (Software development) Interviews Information technology Software development management Software engineering Testing

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362页 << < 74 75 76 77 78 79 80 81 82 83 > >>

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：