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

6,820 篇 会议
2,354 篇 期刊文献
50 册 图书

馆藏范围

9,224 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,212 篇 工学
- 3,880 篇 计算机科学与技术...
- 3,225 篇 软件工程
- 1,383 篇 信息与通信工程
- 854 篇 控制科学与工程
- 706 篇 电气工程
- 620 篇 生物工程
- 583 篇 电子科学与技术（可...
- 527 篇 生物医学工程（可授...
- 368 篇 光学工程
- 361 篇 网络空间安全
- 346 篇 动力工程及工程热...
- 315 篇 安全科学与工程
- 309 篇 机械工程
- 295 篇 化学工程与技术
- 253 篇 仪器科学与技术
- 233 篇 交通运输工程
2,932 篇 理学
- 1,462 篇 数学
- 838 篇 物理学
- 715 篇 生物学
- 503 篇 统计学（可授理学、...
- 334 篇 系统科学
- 313 篇 化学
1,582 篇 管理学
- 999 篇 管理科学与工程(可...
- 680 篇 图书情报与档案管...
- 481 篇 工商管理
589 篇 医学
- 479 篇 临床医学
- 454 篇 基础医学(可授医学...
- 303 篇 公共卫生与预防医...
- 285 篇 药学(可授医学、理...
285 篇 法学
- 227 篇 社会学
179 篇 经济学
168 篇 农学
78 篇 教育学
43 篇 文学
29 篇 军事学
8 篇 艺术学

主题

410 篇 accuracy
333 篇 deep learning
280 篇 machine learning
268 篇 feature extracti...
247 篇 computational mo...
232 篇 real-time system...
223 篇 internet of thin...
209 篇 predictive model...
205 篇 support vector m...
169 篇 training
160 篇 convolutional ne...
139 篇 security
138 篇 optimization
123 篇 data mining
122 篇 neural networks
110 篇 wireless sensor ...
109 篇 reliability
108 篇 cloud computing
104 篇 application soft...
103 篇 analytical model...

机构

228 篇 department of co...
145 篇 gla university d...
132 篇 lovely professio...
113 篇 department of co...
106 篇 school of comput...
102 篇 department of co...
77 篇 school of comput...
72 篇 gla university d...
70 篇 school of comput...
63 篇 department of co...
62 篇 centre of resear...
57 篇 school of comput...
55 篇 chitkara univers...
51 篇 maharishi school...
46 篇 department of co...
45 篇 chitkara centre ...
44 篇 the islamic univ...
42 篇 lloyd institute ...
41 篇 the islamic univ...
40 篇 department of co...

作者

71 篇 neeraj varshney
63 篇 varshney neeraj
58 篇 rakesh kumar
56 篇 asha v.
48 篇 singh kamred udh...
47 篇 v asha
46 篇 kumar rakesh
42 篇 sharma ashish
42 篇 singh teekam
41 篇 singh ashutosh k...
41 篇 bibhuti bhusan d...
38 篇 sharma dilip kum...
38 篇 kumar ankit
36 篇 sharma himanshu
32 篇 ankit kumar
31 篇 kamred udham sin...
30 篇 patra sudhansu s...
29 篇 himanshu sharma
28 篇 jian-ping li
28 篇 tina babu

语言

8,407 篇 英文
765 篇 其他
63 篇 中文
1 篇 西班牙文
1 篇 法文
1 篇 俄文
1 篇 斯洛文尼亚文

检索条件"机构=Computer Engineering and Applications"

共 9224 条记录，以下是481-490 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：

Exploring Missing Value Handling Techniques for Optimized KNN Heart Disease Prediction

Exploring Missing Value Handling Techniques for Optimized KN...

引用

2024 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2024

作者： Joseph, Jeena Kartheeban, K. Kalasalingam Academy of Research and Education Department of Computer Applications Tamilnadu Krishnankoil India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu Krishnankoil India

ISBN: (数字)9798350376135

ISBN: (纸本)9798350376135

Heart disease prediction stands at the forefront of contemporary medical research, with machine learning models such as K-Nearest Neighbors (KNN) being increasingly employed for this purpose. A critical factor influencing the performance of these models is the presence of missing data, which, if not addressed appropriately, can severely hinder predictive accuracy. This study provides a comparative analysis of different missing value handling techniques and explores the impact of each method in predicting heart disease by applying the KNN model. Several imputation methods were employed in the existing literature and techniques such as mean imputation, median imputation, mode imputation, KNN imputation, list-wise deletion, and replacement with a constant value were scrutinized. The popular Framingham heart disease dataset is selected for the study and the missing values are addressed using the techniques mentioned. Subsequently, the KNN method is used to ascertain the predictive accuracy and this highlights the deviations in the results depending upon the chosen imputation method. Remarkably, the method of replacing missing values with a predefined constant value of zero achieved a more accurate result. The study focuses on the distinct characteristics, performance, suitable data type and limitations of each missing value handing technique and it provides valuable information for practitioners and researchers who aim to maximize the effectiveness of machine learning algorithms in cardiovascular disease prediction. © 2024 IEEE.

关键词： Nearest neighbor search

来源：评论

学校读者我要写书评

暂无评论

Virtual Mouse Using Face Gesture and NLP 2

Virtual Mouse Using Face Gesture and NLP

引用

2nd IEEE North Karnataka Subsection Flagship International Conference, NKCon 2023

作者： Zad, Ajay Jagannatha, S. Kumar, Manish Ajitha, S. Prakash, B.R. M S Ramaiah Institute of Technology Department of Masters of Computer Applications Bangalore India East Point College of Engineering Department of Computer Applications Bangalore India M S Ramaiah Institute of Technology Department of Master of Computer Applications Bangalore India Government First Grade College Department of Computer Science Karnataka Tumkur India

ISBN: (纸本)9798350314045

The mouse plays a very important role in interacting with laptop's and computer system, to perform necessary operations. In this paper, we are proposing a method to carry out mouse operations on the computer system without a physical mouse by utilizing voice commands and face-motion gestures. The system employs an internal webcam to detect facial gestures and an internal microphone to receive voice commands from the user. By employing a virtual mouse based on face gestures and natural language processing (NLP), we can accomplish all the fundamental functionalities of a mouse by issuing voice commands to the computer system. The system accepts these commands and executes corresponding mouse events such as "click,""right-click,""double-click,""scroll-up,""scroll-down,""minimize,"and "close."The mobility of the mouse cursor on the monitor is achieved through face motion gestures, enabling the cursor to move up, down, left, and right, respectively. © 2023 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Towards Resilient Crops: Disease Detection and Pest Control Strategies 4

Towards Resilient Crops: Disease Detection and Pest Control ...

引用

4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Ilakya, T. Lakshmi, B. Jeyanthi, S. Esakkiammal, U. Abinaya, T. Cenate, C. F. Theresa New Prince Shri Bhavani College of Engineering and Technology Master of Computer Applications Chennai India New Prince Shri Bhavani College of Engineering and Technology Department of Computer Applications Chennai India New Prince Shri Bhavani College of Engineering and Technology Department of It Chennai India New Prince Shri Bhavani College of Engineering and Technology Department of Eee Chennai India

ISBN: (纸本)9798331508845

A new strategy for resilient crop management that incorporates state-of-the-art technology to combat the ongoing problem of insect infestations in agricultural crops. The suggested system seeks to identify and remove pests and illnesses from fields by using image processing, Internet of Things (IoT), and Deep Learning (DL). Use of Convolutional Neural Networks (CNN) on photos taken by Internet of Things (IoT) devices such as DHT11 sensors and Arduino boards allows the system to quickly and accurately detect and localize impacted regions in real-time. Optimal crop health is achieved via accurate irrigation management made possible by the use of moisture sensors in the soil as well as water motor control. Additionally, farmers are alerted promptly upon pest discovery by rapid notifications enabled by a GSM module and a buzzer, allowing fast response. In spite of obstacles like dataset variability and modelling compactness, the MATLAB-implemented system shows potential for strengthening pest management techniques and encouraging resilient crops in agriculture, leading to better yields and more sustainable farming 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

NFT Marketplace: What are NFTs, and how does OpenSea succeed in acquiring the most of the NFT Space 1

NFT Marketplace: What are NFTs, and how does OpenSea succeed...

引用

1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Thakur, Anil Divya, K. Verma, Sahil Kaur, Maninder Chandigarh University Dept. of Computer Science & Engineering Mohali India Uttaranchal University Dept. of Computer Science & Engineering Dehradun India Guru Gobind Singh College for Women Dept. of Computer Science & Applications Chandigarh India

ISBN: (纸本)9798350373042

Nowadays, the world is becoming smarter, so as the technology, the new era is on the boom, which is blockchain because of its different use cases and benefits. The blockchain is a growing list of records called blocks that are linked together with the use of cryptography. Because all servers on a network are corresponding and a significant concern in the types of network style, its data sources are managed through a peer-to-peer (p2p) network. The servers engage in negotiation and communication through the agreement method. The dispersed network is a network system in which information, software application, and computer system programs are spread out on greater than one node (computer systems). These nodes also depend on each other. It is only a p2p network that gets rid of a solitary factor of failing. It is a decentralized, dispersed, and unalterable journal to show electronic purchases. One of the concepts of blockchain is NFTs. These are digital assets with a unique identity and cannot be replicated. They can be used for a variety of purposes, such as in-game items, digital collectibles, or even to represent real-world assets like cars or houses. They can represent any digital asset or physical goods. NFTs can represent ownership and authenticity of any type of digital asset or physical goods. They can also represent a stake in the game, such as ownership in a casino or a share in a company. © 2024 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Assessing the Effectiveness of Predictive Maintenance for Internet of Things (IoT) Networks Using Reinforcement Learning 3

Assessing the Effectiveness of Predictive Maintenance for In...

引用

3rd International Conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Sharma, Aparna Rastogi, Divya Manwal, Manika Tyagi, Ayushi Sharma, Prashant Kumar Computer Science and Applications Sharda University UP Greater Noida India Computer Science & Engineering Graphic Era Hill University Uttarakhand Dehradun India Computer Science & Engineering Raj Kumar Goel Institute of Technology UP Ghaziabad India Computer Applications Hindustan Institute of Management & Computer Studies UP Mathura India

ISBN: (纸本)9798350342338

Reinforcement getting to know (RL) has emerged as a famous method to predict considerable occasions inside the Net of Things (IoT) networks. RL is a form of artificial intelligence that models conduct from praise and punishment alerts for a given venture or aim. It has been efficaciously used to expect numerous events in dynamic systems and Internet of Things (IoT) networks. Predictive maintenance (PM) aims to stumble on and diagnose screw-ups in IoT structures before they occur. PM aims to expect events and situations in IoT devices to avoid unplanned stoppages or steeply-priced maintenance. Using RL for predictive protection helps with the upkeep of IoT networks by providing a proactive technique. The RL set of rules can study styles from the information accumulated in actual time from the IoT network, after which a prediction algorithm can discover ability screw-ups and endorse preventive preservation tactics. RL can also regulate its mastering process over time based on remarks from the IoT network. The RL approach toward PM provides tremendous benefits over conventional renovation strategies because of its self-getting-to-know and predictive skills. Extensive proof suggests that reinforcement mastering enhances the effectiveness of predictive preservation for IoT networks. RL gives many blessings along with personalized preventive renovation pointers and lowering the value of maintenance, amongst others. As a result, increasingly, groups are adopting reinforcement studying for predictive upkeep to take advantage of its cost financial savings and proactive technique. © 2023 IEEE.

关键词： artificial intelligence dynamic systems IoT predictive maintenance Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Enhancing Data Aggregation Efficiency: Dynamic Energy-Aware Strategies in Wireless Sensor Networks

Enhancing Data Aggregation Efficiency: Dynamic Energy-Aware ...

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Agrawal, Navin Kumar Priya, Naincy Sinha, Priyanka Singh, Pranita Jain, Arpit Kumar, Munish GLA University Department of Computer Engineering & Applications U.P. Mathura India Muzaffarpur Institute of Technology Department of Computer Science & Engineering Bihar Muzaffarpur India Government Engineering College Khagaria Department of Computer Science & Engineering India Roorkee Institute of Technology Department of Computer Science and Engineering Roorkee India Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering Vaddeswaram AP India

ISBN: (纸本)9798350394412

In today's surplus world, wi-fi sensor networks are essential for many systems. This network encapsulates sensor nodes powered by irreplaceable batteries, preserving a fixed topology for displaying specific locations. Their efficiency makes it crucial for large data packages. Wireless sensor networks continuously analyze physical factors such as temperature, pressure, ambient soft, sunlight and humidity, dominating the process Energy consumption monitoring is a key task in this area. To address this framework, this paper proposes a different approach: a modified controlled, privacy-controlled approach to record collection. The method aims to reduce redundant sensitivity, thus increasing system lifetime by reducing the frequency of data transfer between nodes and large sinks A comparative study with existing methods shows how the proposed method is effective. Performance findings show that the proposed bundling method (MEBPP) provides high packet transmission values while consuming less power and extending network lifetime. © 2024 IEEE.

关键词： Data aggregation

来源：评论

学校读者我要写书评

暂无评论

Colon Cancer Prediction with Transfer Learning and K-Means Clustering 7th

Colon Cancer Prediction with Transfer Learning and K-Means...

引用

7th International Conference on Emerging applications of Information Technology, EAIT 2022

作者： Babu, Tina Nair, Rekha R. Department of Computer Science and Engineering School of Engineering Dayananda Sagar University Karnataka Bengaluru India Department of Computer Applications School of Engineering Dayananda Sagar University Karnataka Bengaluru India

ISBN: (纸本)9789811951909

The automatic diagnosis of colon cancer is important for patients and their prognosis through the analysis of histopathological images. Traditional feature extraction methods extract low-level image features, and prior knowledge is required to choose meaningful features, which may be modified significantly by humans. Hence, unsupervised and supervised deep convolutions neural networks were utilized to analyze histopathological images of colon cancer. To overcome the impact of the unbalanced histopathology images in sub-classes, the balanced sub-classes are turned right and left, up and down, and rotated counter clockwise by 90∘ and 180∘. The proposed experimental findings for supervised histopathological image classification of colon cancer demonstrate that Inception_V3 and Inception ResNet_V2 outperform current algorithms. These findings suggest that the Inception_ResNet_V2 network is superior deep learning architecture for analyzing histopathological images for diagnosis colon cancers. As a result, in order to perform unsupervised image analysis, Inception_ResNet_V2 is utilized to extract features from colon cancer histopathology images. In addition, a new autoencoder network was created to convert the features collected by Inception_ResNet_V2 to a low-dimensional space for image clustering analysis. The test results demonstrate that the proposed autoencoder network outperforms the Inception_ResNet_V2 network in terms of clustering. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Fuzzy Reliability Redundancy Allocation for xj -out-of- mj System Using Fuzzy Rank-Based Multi-objective PSO 9th

Multi-objective Fuzzy Reliability Redundancy Allocation for ...

引用

9th International Symposium on Applied Computing for Software and Smart systems, ACSS 2022

作者： De, Satyajit Roy, Pratik Chowdhury, Anil Bikash Department of Computer Science Maheshtala College WB Maheshtala700141 India Department of Computer Engineering and Applications GLA University UP Mathura281406 India Department of Computer Applications Techno India University WB Kolkata700091 India

ISBN: (纸本)9789811967900

The main goal of this paper is to solve a fuzzy multi-objective reliability redundancy allocation problem (MORRAP) for xj -out-of- mj series-parallel system. We consider that system reliability and system cost are two conflicting objectives. Due to the incompleteness and uncertainty of input information, we formulate the objectives by considering the reliability and cost of each component as a triangular fuzzy number (TFN). Here, the fuzzy multi-objective optimization problem of system reliability and cost is analyzed simultaneously using our proposed fuzzy rank-based multi-objective particle swarm optimization (FRMOPSO) algorithm. Comparing the results of FRMOPSO with standard particle swarm optimization (PSO), we see that better optimum reliability and cost have been achieved in the FRMOPSO technique. To illustrate the effectiveness of our proposed technique, we consider the problem of the over-speed protection system of gas turbines containing two mutually conflicting reliability and cost objectives with entropy and several other constraints. We present graphically the effect of optimum system reliability and cost with respect to the percentage change of different parameters. We also compare the convergence rate of FRMOPSO with PSO. Our proposed algorithm shows better results. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Redundancy

来源：评论

学校读者我要写书评

暂无评论

Factor Graph Neural Network Meets Max-Sum: A Real-Time Route Planning Algorithm for Massive-Scale Trips 23

Factor Graph Neural Network Meets Max-Sum: A Real-Time Route...

引用

23rd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2024

作者： Li, Yixuan Wang, Wanyuan Xu, Weiyi Deng, Yanchen Wu, Weiwei Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications School of Computer Science and Engineering Southeast University Nanjing China School of Computer Science and Engineering Nanyang Technological University Singapore School of Computer Science and Engineering Southeast University Nanjing China

Global route planning (GRP) is a typical combinatorial optimization problem that has been solved for a variety of industrial purposes, such as traffic flow management, network routing, and conflict prevention. The goal of the GRP is to find a route for each trip query such that all queries have a minimum global travel time. The GRP problem is NP-hard and computationally challenging, even for medium-sized instances. However, in real-world GRP applications, such as Google Maps-based vehicle route guidance systems, there are always massive-scale trips issued simultaneously, and real-time response is required. Existing mathematical programming-based exact methods and heuristics struggle to balance the extremes of optimality and scalability. Considering that many closed-related GRP instances must be solved repeatedly, this paper explores a deep learning approach to learn real-time and efficient solutions for GRP. This paper first proposes a novel route-query factor graph (RQ-FG) to model the GRP problem, where the message-passing damped Max-sum (DMS) algorithm can be exploited to generate high-quality approximate solutions. A hybrid pruning method is proposed to accelerate solving the DMS. We further devise a route-query factor graph neural network (RQ-FGNN) based on the RQ-FG, which has the ability to return solutions in milliseconds. Experiments demonstrate that our method can generate high-quality solutions in massive-scale GRP instances in real-time. © 2024 International Foundation for Autonomous Agents and Multiagent Systems.

关键词： Message passing

来源：评论

学校读者我要写书评

暂无评论

Predicting Future Automobile Ownership Trends in Uzbekistan Using Linear Regression 2nd

Predicting Future Automobile Ownership Trends in Uzbekistan ...

引用

2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Ather, Danish Singh, Malikhan Arora, Kavita Pathak, Sonal Qurashi, Suhail Javed Singh, Anupam Amity University Tashkent Uzbekistan Computer Science and Engineering College of Engineering & Technology Mathura India School of Computer Applications Manav Rachna International Institute of Research and Studies Haryana Faridabad India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India

ISBN: (纸本)9789819735938

The rapid urbanization and economic growth of Uzbekistan over the past decades have engendered significant changes in automobile ownership trends. Understanding these trends is crucial for infrastructure planning, sustainable transportation strategies, and environmental considerations. This Paper seeks to employ Machine Learning (ML) techniques to forecast the number of cars per 100 households in Uzbekistan by 2025, based on historical data from 2010, 2015, and 2020. The dataset, derived from official statistics provided by the State Committee of the Republic of Uzbekistan on Statistics, shows a remarkable increase from 21 cars per 100 households in 2010 to 48 by 2020. Leveraging regression models, we aim to predict the expected growth for 2025. Preliminary analyses hint at a continuing upward trend, impacted potentially by factors such as Population growth, GDP growth, urban migration, and increasing global connectivity. The findings from this research will not only serve as a prediction tool but will also shed light on the socio-economic factors influencing car ownership, providing valuable insights to policymakers and urban planners. While the limited data points present a challenge for complex model utilization, the study underscores the potential of ML in forecasting and the need for more comprehensive data collection in future studies. The predictive insights drawn from this research can significantly aid in shaping transportation policies, mitigating potential environmental impacts, and planning urban infrastructures in Uzbekistan. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Forecasting

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 << < 45 46 47 48 49 50 51 52 53 54 > >>

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：