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

2,407 篇 会议
1,329 篇 期刊文献
37 册 图书

馆藏范围

3,773 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,299 篇 工学
- 1,633 篇 计算机科学与技术...
- 1,341 篇 软件工程
- 622 篇 信息与通信工程
- 365 篇 控制科学与工程
- 300 篇 生物工程
- 288 篇 电气工程
- 229 篇 生物医学工程（可授...
- 220 篇 电子科学与技术（可...
- 180 篇 光学工程
- 160 篇 机械工程
- 160 篇 网络空间安全
- 136 篇 化学工程与技术
- 129 篇 安全科学与工程
- 115 篇 动力工程及工程热...
- 107 篇 交通运输工程
- 104 篇 核科学与技术
- 102 篇 仪器科学与技术
1,346 篇 理学
- 602 篇 数学
- 473 篇 物理学
- 327 篇 生物学
- 214 篇 统计学（可授理学、...
- 154 篇 化学
- 113 篇 系统科学
691 篇 管理学
- 432 篇 管理科学与工程(可...
- 293 篇 图书情报与档案管...
- 153 篇 工商管理
218 篇 医学
- 161 篇 临床医学
- 160 篇 基础医学(可授医学...
- 111 篇 公共卫生与预防医...
129 篇 法学
- 107 篇 社会学
67 篇 经济学
65 篇 农学
36 篇 教育学
34 篇 文学
20 篇 军事学
5 篇 艺术学
1 篇 哲学

主题

172 篇 accuracy
141 篇 deep learning
105 篇 feature extracti...
100 篇 hadron colliders
98 篇 machine learning
89 篇 computational mo...
88 篇 training
84 篇 convolutional ne...
73 篇 real-time system...
66 篇 support vector m...
63 篇 predictive model...
61 篇 artificial intel...
56 篇 optimization
53 篇 internet of thin...
49 篇 reliability
46 篇 genetic algorith...
46 篇 cloud computing
46 篇 data models
44 篇 semantics
44 篇 security

机构

132 篇 yerevan physics ...
129 篇 national and kap...
129 篇 centro brasileir...
129 篇 istanbul technic...
127 篇 university of sp...
127 篇 indian institute...
126 篇 universidad iber...
125 篇 brunel universit...
124 篇 università di to...
124 篇 academy of scien...
124 篇 charles universi...
124 篇 infn sezione di ...
123 篇 department of ph...
122 篇 zhejiang univers...
122 篇 irfu cea univers...
121 篇 infn sezione di ...
120 篇 university of de...
120 篇 department of ph...
118 篇 imperial college...
118 篇 rwth aachen univ...

作者

125 篇 m. lu
95 篇 g. tonelli
95 篇 d. barney
95 篇 l. valencia palo...
95 篇 t. liu
95 篇 c. hensel
95 篇 a. garcia-bellid...
95 篇 a. steen
95 篇 n. cartiglia
95 篇 d. eliseev
94 篇 a. babaev
94 篇 v. karjavine
93 篇 n. colino
93 篇 f. moortgat
92 篇 b. clerbaux
91 篇 g. sultanov
91 篇 a. mallampalli
91 篇 m. a. ciocci
91 篇 k. lamichhane
91 篇 s. maselli

语言

3,148 篇 英文
584 篇 其他
45 篇 中文
2 篇 日文
1 篇 德文
1 篇 法文

检索条件"机构=Computer Science Engineering and Application"

共 3773 条记录，以下是1041-1050 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：

Investigation into a Medical Diagnostic System for Chronic Kidney Disease: Preparation and Execution

Investigation into a Medical Diagnostic System for Chronic K...

引用

IEEE UP Section Conference on Electrical computer and Electronics (UPCON)

作者： Arvind Sharma Dalwinder Singh School of Computer Application Lovely Professional University Phagwara Punjab India School of Computer Science and Engineering Lovely Professional University Phagwara Punjab india

This abstract provides a concise overview of a study focused on the development and execution of a medical diagnostic system specifically designed for Chronic Kidney Disease (CKD). The primary objective of this study is to contribute to the advancement of early detection and intervention strategies for chronic kidney disease (CKD), a prevalent and potentially incapacitating condition. The inquiry process encompasses several sequential stages, including the initial planning phase and subsequent execution phase. During this stage, comprehensive literature studies are conducted to examine the various approaches used for diagnosing chronic kidney disease (CKD), as well as the risk factors associated with its development and the biomarkers used for its detection. This literature review aids in identifying the deficiencies within the diagnostic system and highlights the potential utility of advanced techniques such as machine learning and data analytics. The development and implementation of the diagnostic system occur during the execution phase. A comprehensive database is established by the consolidation of data from various sources, including patient records, laboratory findings, and diagnostic imaging. State-of-the-art algorithms and machine learning approaches are utilized to conduct comprehensive data analysis, pattern identification, and the construction of prediction models for the diagnosis of Chronic Kidney Disease (CKD). This article provides a comprehensive examination of various healthcare systems pertaining to the management of chronic kidney disease. Additionally, it presents a systematic review of recent research undertaken by multiple scientists during the past five years.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Automated Detection of Abnormalities in Ultrasound Images Using Deep Learning

Automated Detection of Abnormalities in Ultrasound Images Us...

引用

Optimization Computing and Wireless Communication (ICOCWC), International Conference on

作者： Amit Kumar Bhuvana J Vikas Kumar Kharbas College of Engineering Teetthanker Mahaveer University Moradabad Uttar Pradesh India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Department of Computer Science & Application Vivekananda Global University Jaipur India

Deep getting to know has been utilized in scientific imaging studies to explore challenges with diagnosing ailments and detecting anomalies. This examination focused on the automated detection of bizarre tissues in ultrasound pix. Pics must adhere to a homogeneous, properly-described, predictable anatomy for hit-deep getting-to-know applications. It looks at the proposed artificial neural network (ANN) and lengthy quick-time period memory (LSTM) based version referred to as ALunoNet to detect anomalies in ultrasound pictures. The models were skilled on a 10,000 M-mode and B-mode ultrasound pictures dataset. After ten epochs, their checking out accuracy was eighty three.16%. They look at comparing the performance of ALunoNet with other popular CNN and LSTM models. The observed effects demonstrate that ALunoNet performs higher than the same old fashions and that its overall performance is consistent even on datasets with constrained information. It has a look at highlights the capability of deep-gaining knowledge to automatize the detection of strange tissues in ultrasound pics.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ANTIBIOLOG: An Advanced Tool for Combat Antibiotic Resistance With Enhanced Multinomial Logistic Regression 9

ANTIBIOLOG: An Advanced Tool for Combat Antibiotic Resistanc...

引用

9th IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2023

作者： Routray, Sweta Padma Nayak, Amlan Deep Nayak, Debasish Swapnesh Kumar Sahoo, Swayamprabha Swarnkar, Tripti Center for Biotechnology Siksha 'O' Anusandhan Deemed to be University Bhubaneswar751003 India Institute of Technical Education and Research Siksha 'O' Anusandhan Deemed to be University Department of Computer Application Bhubaneswar751030 India Institute of Technical Education and Research Siksha 'O' Anusandhan Deemed to be University Department of Computer Science & Engineering Bhubaneswar751030 India

ISBN: (纸本)9798350319651

Pseudomonas aeruginosa, a multidrug-resistant organism with clinical significance, complicates the treatment of critically ill patients. Since traditional susceptibility testing takes at least 24 hours, timely identification and treatment are crucial in the face of rising Antimicrobial Resistance (AMR). In this study, we present the development of ANTIBIOLOG, a cutting-edge Machine Learning (ML) model. This model predicts P. aeruginosa antibiotic susceptibility based on patient demographics and antibiotic susceptibility testing results, using a dataset of 49 patient samples from IMS & SUM Hospital. Multinomial logistic regression was selected for dealing with multiple classes and providing probabilistic interpretations. The performance of the model is evaluated using various metrics such as accuracy, precision, recall, specificity, F1 score, and MCC. Through a user-friendly web interface, it simplifies resistance prediction and guides empirical antibiotic treatment. Unlike generic tools, it focuses on P. aeruginosa and provides accurate therapy selection. ANTIBIOLOG predicted antibiotic susceptibility with a promising 77.77% accuracy. This ML-based tool enables healthcare professionals to combat multidrug-resistant P. aeruginosa infections and address AMR issues. © 2023 IEEE.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

A Bayesian Optimization Framework for Adaptive Node Deployment in Wireless Sensor Networks

A Bayesian Optimization Framework for Adaptive Node Deployme...

引用

International Conference on Communication Systems and Network Technologies (CSNT)

作者： Rahul Priyadarshi Jayant Kumar Rout Anish Kumar Vishwakarma Nikhil Dhengre Rakesh Ranjan Amit Verma Faculty of Engineering and Technology ITER SOA Bhubaneswar India School of Computer Application KIIT Bhubaneswar India School of Computer Science UPES Dehradun Uttarakhand India Department of ECE IIIT Nagpur Maharashtra India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Wireless Sensor Networks (WSNs) require efficient node deployment strategies to optimize network longevity, energy consumption, and coverage. This paper introduces a novel approach for strategic node deployment in WSNs using Bayesian Optimization (BO). A BO-based framework that iteratively modifies node positions to maximize network performance metrics, such as energy efficiency and coverage ratio, while minimizing execution time is proposed. Through extensive simulations across diverse deployment scenarios, the proposed method is evaluated and demonstrates superior performance compared to both traditional and machine learning (ML)-based techniques. The results indicate significant improvements in coverage and energy efficiency, alongside competitive execution times. These findings highlight the potential of BO to enhance WSN deployment strategies, offering a scalable and adaptive solution for real-world applications. Future research will focus on integrating BO with other optimization techniques and extending the approach to dynamic environments and varied network configurations.

关键词： Learning systems Wireless sensor networks Energy consumption Adaptive systems Machine learning Energy efficiency Real-time systems Bayes methods Reliability Optimization

来源：评论

学校读者我要写书评

暂无评论

Conventional Neural Network for Maths Handwritten Digit Categorization

Conventional Neural Network for Maths Handwritten Digit Cate...

引用

International Conference on Contemporary Computing and Informatics (IC3I)

作者： Shivya Garg Navya Kuchhal Jigyasa Barmola Vandana Rawat Neelam Singh Department of Computer Application Graphic Era Deemed to be University Dehradun India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India

Handwritten digit recognition plays a crucial role in various sectors such as document processing, automatic form identification, and postal automation. This task involves accurately identifying and classifying handwritten digits into their respective numerical values. This presentation provides a summary of current developments in machine learning techniques for handwritten digit recognition. The primary objective of this research is to develop an advanced system for recognizing handwritten digits by harnessing state-of-the-art machine learning techniques. To train and test the suggested system, a sizable dataset of handwritten digits is used. We are utilizing the MNIST dataset here. To improve the quality of the input pictures and guarantee uniform feature representation, preprocessing techniques like image enhancement and normalization are used. Experimental results indicate that the CNN model surpasses all other investigated techniques in accuracy, boasting an impressive accuracy rate of over 98%. The capacity of the CNN model to automatically deduce pertinent characteristics from the input pictures, catching both local and global patterns, is credited with its better performance. Additionally, the model can successfully handle spatial relationships in the digit pictures because to CNNs' usage of convolutional layers. A number of practical applications, such as computerized form processing, digital document analysis, and intelligent character recognition, are possible with the suggested handwritten digit recognition system. The CNN model's high accuracy enables accurate digit categorization, enhancing efficiency and accuracy across a variety of applications. Future research can concentrate on investigating ensemble approaches, data augmentation methods, and fine-tuning techniques to improve the handwritten digit recognition system's performance even further.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Intelligent Framework for Task Placement and Resource Allocation for IoT in the Fog-Cloud Scenario

Intelligent Framework for Task Placement and Resource Alloca...

引用

Current Development in engineering and Technology (CCET), IEEE International Conference on

作者： Shifa Manihar Ravindra Patel Sanjay Agrawal Computer Science Engineering University Institute of Technology RGPV Bhopal India Computer Application University Institute of Technology RGPV Bhopal India Computer Engineering and Application NITTTR Bhopal India

In order to identify the latency-critical applications, this research develops an intelligent task placement and resource allocation framework (ITPRAF) that makes use of supervised feed forward neural networks. This algorithm runs through two stages. To decide whether to schedule a task for execution in the fog or send it to the cloud in the first part, this machine learning-based system uses the task's attributes as input. To ensure the best resource usage, jobs that are put to fog are reshuffled keeping into account the priority at the fog queue in the second phase. Four mechanisms for resource allocation in fog are presented in this research. Through the simulation results from various iterations, the reaction time, resource consumption, and delay satisfaction rate of each scenario were compared.

关键词： Schedules Machine learning algorithms Simulation Neural networks Delays Resource management Feeds

来源：评论

学校读者我要写书评

暂无评论

Using Ant Colony Optimised Algorithms for Shortest Path Exploration by Robots

Using Ant Colony Optimised Algorithms for Shortest Path Expl...

引用

Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Aashdeep Singh Sakshi Dhawan Jyoti Verma Gurpreet Singh Amanpreet Kaur Dept. of Computer Science & Engineering Punjab Institute of Technology Rajpura (MRSPTU Bathinda) Rajpura Punjab India Dept. of Computer Application Punjab Institute of Technology Rajpura (MRSPTU Bathinda) Rajpura Punjab India Dept. of Computer Science & Engineering Chitkara University Institute of Engineering & Technology Rajpura Punjab India

In the realm of robotics and autonomous systems, efficient path planning is a critical aspect for optimizing resource utilization and achieving mission objectives. This study explores the application of Ant Colony Optimized (ACO) algorithms to enhance the efficiency of robots in navigating and exploring unknown environments. Inspired by the foraging behavior of ants, ACO algorithms are employed to find the shortest paths by leveraging pheromone communication and decentralized decision-making. Ant Colony Optimization is then introduced as a bio-inspired solution to address these challenges. The experimental results demonstrate the capability of the ACO algorithm to efficiently explore complex environments, adapt to changes in the surroundings, and converge to optimal paths. Insights gained from these analyses contribute to the refinement of the ACO algorithm for diverse robotic applications. The findings of this research have practical implications for the development of autonomous robots operating in real-world scenarios, such as search and rescue missions, environmental monitoring, and surveillance. This study provides a valuable foundation for the integration of bio-inspired algorithms in robotics, advancing the state-of-the-art in autonomous exploration and path planning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

AI-Powered Job Market Analysis: Transforming Workforce Trends and Employment Predictions

AI-Powered Job Market Analysis: Transforming Workforce Trend...

引用

Global Conference for Advancement in Technology (GCAT)

作者： Sanjana Purohit Mirza Shuja Sahil Walia Mukesh Kumar Karan Bajaj Vivek Bhardwaj School of Computer Applications JECRC University Jaipur Rajasthan India School of Computer Application Lovely Professional University Phagwara Punjab India Solutions Architect Snowflake Inc. Atlanta Georgia USA Department of Computer Application Chandigarh School of Business Chandigarh Group of Colleges Mohali Punjab India School of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Department of Computer Science and Engineering Manipal University Jaipur Rajasthan India

ISBN: (数字)9798350376685

ISBN: (纸本)9798350376692

This analysis delves into the "AI-Powered Job Market Insights" dataset, offering a comprehensive exploration of how artificial intelligence (AI) and automation are influencing the modern job market. The dataset provides a snapshot of job listings across various industries, highlighting factors such as AI adoption levels, automation risk, and salary ranges. By examining these elements, we aim to uncover key trends and insights into how AI is reshaping employment opportunities and job market dynamics. The primary objective of this analysis is to identify and understand key patterns related to salaries, required skills, remote work, and job market trends influenced by AI. By employing various analytical techniques, we seek to reveal how AI adoption impacts compensation, skill requirements, and job growth, as well as how it correlates with the likelihood of remote work.

关键词： Industries Correlation Automation Employment Companies Market research Remote working Remuneration Artificial intelligence Qualifications

来源：评论

学校读者我要写书评

暂无评论

A Comparative Analysis of Machine Learning Models for Colon Cancer Classification

A Comparative Analysis of Machine Learning Models for Colon ...

引用

Advances in Power, Signal, and Information Technology (APSIT), International Conference in

作者： Rashmi Ranjan Swain Debasish Swapnesh Kumar Nayak Tripti Swarnkar Department of Computer Application Siksha ‘O’ Anusandhan University Bhubaneswar India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan University Bhubaneswar India

One of the trickiest machine learning challenges is the automatic classification of cancer cells. Colon Cancer can strike anyone at any age, but it often strikes older persons. In recent years, several investigations have focused on developing machine learning algorithms that can automatically classify genes of various types of a particular disease, especially colon cancer. The classification of cancer has improved due to improvements in computational methods like machine learning (ML), which required little human interaction and inefficient computers. Since the classification of gene expression data has been extensively studied in conjunction with the advancement of gene technology, a wide variety of techniques, primarily neural network-related, have been applied to the analysis of medical data, which is primarily concerned with the large dimension and very small in quantity. In this work, five different ML techniques were implemented for the classification of colon cancer in different age groups. The implemented ML techniques are Random Forest (RF), Decision Tree (DT), Support vector Machine (SVM), Naive Bayes (NB), and K-Nearest Neighbour (KNN). It is observed that most of the implemented model has an average accuracy of more than 95%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MP-DPCC: A Motion Proxy-Based Dynamic Point Cloud Compression Framework

MP-DPCC: A Motion Proxy-Based Dynamic Point Cloud Compressio...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Jiang, ZhaoYi Han, Dong Song, Cao Nan, FangZhe Yang, Bailin School of Computer Science and Technolgy Zhejiang Gongshang University China School of Statistics and Mathematics Zhejiang Gongshang University China Economic Forecasting and Policy Simulation Laboratory Zhejiang Gongshang University China Collaborative Innovation Center of Statistical Data Engineering Technology & Application Zhejiang Gongshang University China

ISBN: (纸本)9798350368741

The increasing data volume and the demand for real-time transmission highlight the necessity for efficient compression of dynamic point cloud data. Existing methods primarily focus on reducing inter-frame redundancy by calculating per-point motion information, overlooking the computational and storage costs involved. In this paper, we propose a novel motion proxy-based dynamic point cloud compression framework to enhance the efficiency and accuracy of motion information utilization. Specifically, we introduce a feature proxy module to adaptively locate proxy points, which represent the overall motion through the motion of proxy points. Additionally, a motion enhancement module is employed to refine motion details and prevent local information loss caused by dense motion trajectories. Extensive experiments demonstrate the superiority of our approach. Compared with baseline methods, it achieves an average BD-rate improvement of 12.07% (D1) and 11.90% (D2). © 2025 IEEE.

关键词： compression deep learning neural network point cloud

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378页 << < 101 102 103 104 105 106 107 108 109 110 > >>

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：