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
1,316 篇 期刊文献
37 册 图书

馆藏范围

3,760 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,305 篇 工学
- 1,636 篇 计算机科学与技术...
- 1,341 篇 软件工程
- 623 篇 信息与通信工程
- 366 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
- 161 篇 机械工程
- 160 篇 网络空间安全
- 135 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...
- 111 篇 核科学与技术
- 107 篇 交通运输工程
- 102 篇 仪器科学与技术
1,344 篇 理学
- 602 篇 数学
- 472 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
- 431 篇 管理科学与工程(可...
- 294 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...
131 篇 法学
- 109 篇 社会学
66 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...
55 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...
125 篇 irfu cea univers...
124 篇 università di to...
124 篇 academy of scien...
124 篇 charles universi...
124 篇 infn sezione di ...
123 篇 department of ph...
123 篇 zhejiang 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

3,136 篇 英文
584 篇 其他
44 篇 中文
2 篇 日文
1 篇 德文
1 篇 法文

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

共 3760 条记录，以下是201-210 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：

Stage Wise Classification and prediction of Alzheimer disease using Hybrid Appraoch 4

Stage Wise Classification and prediction of Alzheimer diseas...

引用

4th International Conference on Intelligent Technologies, CONIT 2024

作者： Prabagaran, A. Dwivedi, Vinay Neelam Rani, Jyoti Angelin Blessy, J. Padmanabhan, P. Gupshup Technology India Pvt Ltd Bengaluru India Galgotias University School of Computer Science and Engineering Uttar Pradesh Greater Noida India Noida Institute of Engineering & Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Galgotias Univeristy School of Computing Science and Engineering Dept of Computer Application India Greater Noida Institute of Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350349900

Alzheimer's, the most prevalent cause of dementia, leads to a continuous decline in cognitive functions, social skills, and behavior, affecting individuals' independent functioning. As per survey 2010 in India around 3.7 million affected by dementia, and this data is expected to twofold by 2030. The associated cost of care is projected to triple, necessitating ongoing support. This issue is a significant societal concern that warrants careful consideration. Prediction and classification of Alzheimer's disease (AD) are crucial for identifying and addressing it at earlier stages. The disease is typically classified into three stages: early-stage dementia, middle-stage, and late-stage. However, several challenges exist, including limited awareness, diagnostic difficulties, insufficient technologies and treatments, unpredictable progression across stages, and a lack of comprehensive stage-by-stage predictions. This work proposes a hybrid model for predicting, classifying, and stage-wise classifying Alzheimer's disease. The hybrid model aims to address the challenges associated with the disease, utilizing different features for prediction and classification. The hybrid model used a Random forest, convolutional neural network (CNN), kernel density algorithm (KDA) with hyperparameter tuning for accurate prediction and classification. The proposed hybrid method used Random forest used for basic classification, CNN and kernel density for stage wise classification. The proposed hybrid method achieved an impressive 95.6% accuracy in stage wise classification and prediction of AD. © 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

Genetic Algorithm-Based Data Allocation in Multi Media Using Cloud Computing 3

Genetic Algorithm-Based Data Allocation in Multi Media Using...

引用

3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Yadav, Surendra Kaur, Manpreet Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

The recent growth of Internet-of-Things (IoT) applications using cloud computing has been amazing. One of the advancements is heterogeneous cloud computing, which has made it possible to use the cloud for a range of infrastructure solutions, including multimedia big data. The optimizations of on-premise heterogeneous memory have been the subject of several past studies. However, the performance and financial limits brought on by hardware distributions and manipulative techniques are placing restrictions on the heterogeneous cloud memory. It is an NP-hard combinatorial issue to distribute data jobs across dispersed memory with different capacities. In order to provide high performance cloud-based heterogeneous memory service offerings, this study focuses on this problem and suggests a unique solution called Cost-Aware Heterogeneous Cloud Memory Model. It allocates data to the cloud-based memory via genetic programming. In our suggested method, we take into account a number of important elements that have a significant influence on how well Communication expenses, data transfer operating costs, energy performance, and time constraints all play a role in how cloud memories operate. Finally, we put our suggested paradigm to the test via experimental assessments. The trial findings have demonstrated the viability and scalability of our technique as a cost-conscious cloud-based solution. © 2023 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

A Multi-Objective Decision Assistance System for Selecting Security Controls Based On Simulation 3

A Multi-Objective Decision Assistance System for Selecting S...

引用

3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Shree, Ritu Sandhu, Komal Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

In this work, we present the results of our continuing investigations into simulation-based risk analysis for information security and multi-objective investment optimization for security controls. We provide a methodological approach that takes into account the organization's features, information architecture, assets that must be safeguarded, unique threat sources encountered, and decision-makers' risk preferences. This framework includes dynamic attack graph generation techniques, ontological modelling of security knowledge, probabilistic reenactment of assaults by objective driven danger specialists, Identification of compelling arrangement of data security controls utilizing meta-heuristics, and intuitive choice help. These components make it possible for cutting-edge techniques to generate attack graphs and infer potential attack routes based on the motivations, goals, skills, and available entry points of attackers, Then, using this inferred information, simulate assaults based on the infrastructure a model of an organisation. The strategy aids decision-makers weigh financial and non-financial factors related to risks, costs, and benefits when assessing possible security control initiatives. In order to assess the strategy through application case studies, we are now constructing a prototype implementation of the framework. © 2023 IEEE.

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

Enhancing Dynamic Abstract Generation for Code Summarization using CODE-OAN Models and DBWTFF Frames 2

Enhancing Dynamic Abstract Generation for Code Summarization...

引用

2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Bhatt, Chandradeep Sharma, Manish Sharma, Sanjay Gupta, Shefali Singh, Teekam Kumar, Mukesh Computer Science and Engineering Graphic Era Hill University Uttarakhand Dehradun248002 India Computer Science & Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun248002 India Sgrr Univeristy Computer Application Department Dehradun India Chitkara University Institute of Engineering and Tech Chitkara University Punjab India

ISBN: (纸本)9798350306415

This research presents a robustness code abstraction generation method based on an attention mechanism. The method involves extracting high-quality code and its corresponding description language material from the programming community, specifically focusing on the text of query specifications and code responses. Redundant code and its description language material are filtered out, and the query specifications are transformed into declarative sentences for code conversion. Finally, a series model based on the attention mechanism is utilized to generate code summaries. The method effectively eliminates redundancy and noise in the code, leading to improved accuracy rates in automatic judgment, artificial evaluation, and testing. The evaluation results demonstrate superior performance compared to existing baseline methods. © 2024 IEEE.

关键词： accuracy rate attention mechanism code abstraction code summarization declarative sentences description language high-quality code redundancy filtering robustness

来源：评论

学校读者我要写书评

暂无评论

ASLPP-RR Routing Based on Improved IDAF-FIT Clustering with Secure Data Aggregation in Wireless Sensor Network 3

ASLPP-RR Routing Based on Improved IDAF-FIT Clustering with ...

引用

3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Garg, Megha Dogra, Yakesh Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

Wireless Sensor Network (WSN) technology has recently emerged as a critical component for monitoring and tracking tasks across a variety of application domains. The most difficult problem now is developing a power-efficient data collection technique. This is due to the fact that each sensor node in the network only has a certain amount of power resources. Clustering is used to improve power efficiency, network connectivity, and delay minimization. Therefore, because of data aggregation and cluster head selection, approaches base on clustering for information collection assume an essential part as far as power-saving and expanding the lifetime of the network. The IDAF- FIT (Fuzzy and Distributed Autonomous Fashion Integration The algorithm (If-then Rules) is suggested for clustering in this suggested approach, and in the interim, the Cluster kind of Head is also chosen. The routing concept is then started in order to transfer the packet from the source to the target node by selecting the best route. ASLPP-RR, Routing is suggested using an adaptive source location privacy preservation method. in this context. Additionally, Using Secure Data Aggregation based on Principle Component Analysis and integrity are preserved (SDA-PCA) technique. Finally, a thorough analysis of the security of sensitive data yields results that are superior to those of the current methods. The total performance of the suggested approach is described as a 20% increase in packet delivery ratio, a 15% decrease in packet dropping ratio, an 18% increase in residual power, a 22% increase in network lifespan, and a 16% decrease in power consumption when compared to existing. © 2023 IEEE.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Approach to Compare Causal Inference Modelling Strategies in the Digital Advertising Industry 2

A Machine Learning Approach to Compare Causal Inference Mode...

引用

2nd International Conference on Ambient Intelligence in Health Care, ICAIHC 2023

作者： Singh, Sanskriti Sanjay Kumar Kumar Sinha, Apoorv Pandey, Trilok Nath Acharya, Biswa Mohan School of Computer Science and Engineering Vellore Institute of Technology Chennai India SOA University ITER Dept. of Computer Application Bhubaneswar India

ISBN: (纸本)9798350344882

Cause and effect relationships are not extensively explored in machine learning but prior to creating a system that understands causal relationships, there needs to be a general ability to grasp and inculcate cause-and-effect statistically. The way of choice for the proposed model is causal inference where the causes are inferred from the data. The study of causality, unlike correlation, falls in the domain of prescriptive analytics, that is, the likelihood of an occurrence given that another occurrence has happened. As a result, the study of causality and predictions based on causal inference are highly important when it comes to the domain of marketing and sales, largely because many practices in the domain of advertising try to fundamentally mimic causal inference such as A/B testing, primarily used in e-commerce and the digital advertising industry. For the purposes of the study, the treatment will be exposure to multiple advertisements and the uplift modelling will be used to direct marketing efforts to the most agreeable customers. Uplift modelling is a causal learning approach that estimates the dataset's individual treatment effect and using the same, calculates the incremental impact of a direct treatment on the individual behavior of the customer, which is why the advertising use-case felt particularly suitable. The usual way causal inference is inculcated in machine learning models is that one attribute is taken as a treatment, that is, the intervention or policy that has been done, while the target label is the desired outcome while accounting for the confounders which are the rest of the attributes. However, for the crux of this study, the proposed model will be taking two treatment attributes so as to see how the causality of two outcomes improves or worsens the impact of a rudimentary machine learning model. At the same time, this comparative study will be in tandem with two other models featuring one causal relationship as well as no causal relations

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

Improving Efficiency and Accuracy in Clinical Diagnostic Decision Making with Deep Learning

Improving Efficiency and Accuracy in Clinical Diagnostic Dec...

引用

2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Kharbas, Vikas Kumar Gobi, N. Kumar, Dinesh Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

Deep learning is a modern form of synthetic intelligence (AI) based on large quantities of statistics and algorithms that allow computer systems to approximate features and solutions, ensuing in more excellent, efficient, and accurate selections. In the scientific field, deep gaining knowledge is increasingly used to help clinicians with diagnostic decision-making, decreasing the value and attempt associated with diagnostic approaches. This paper discusses the potential of deep learning to enhance the performance and accuracy of medical diagnostic selection-making. The paper provides an overview of the cutting-edge nation of the field, with a particular awareness of picture processing and its application to improve accuracy and decrease the price associated with scientific diagnoses. It also provides a few capacity challenges and pitfalls and outlines the issues essential to ensure a hit implementation and successful results. Eventually, it offers a few recommendations for similar studies to increase deep getting to know algorithms further. Deep gaining knowledge has been broadly explored in recent years as a powerful tool for enhancing the accuracy and efficiency of clinical diagnostic decision-making. Deep studying models can investigate patterns in medical datasets, deliberating the traits of affected person information and ailment signs to generate extra specific and reliable diagnoses. By incorporating extra facts such as transcripts from affected person-clinician interactions and medical imaging, those fashions may be trained to assist clinicians in identifying illnesses early and provide well-timed and correct analysis. Moreover, deep learning allows for incorporating case-primarily based reasoning and presents the capacity to combine scientific knowledge in real-time. By having extra sturdy and accurate models, clinicians can reduce the time required to diagnose a condition and make treatment choices. Deep gaining knowledge also lets in for the integration o

关键词： disorder enhance healthcare value

来源：评论

学校读者我要写书评

暂无评论

Prediction of Reliability of Data in Underwater Communication Network Using Fuzzy Logic

Prediction of Reliability of Data in Underwater Communicatio...

引用

2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Yadav, Surendra Gobi, N. Yadav, Rakesh Kumar Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

This paper uses fuzzy logic to propose a reliability prediction set of rules for the underwater communication community. The set of rules uses fixed fuzzy rules to expect communication reliability among nodes in an underwater environment. Those fuzzy rules are derived from a reliability model based on the characteristics of an ordinary underwater conversation system, such as physical and environmental elements. The algorithm is then examined using accurate statistics from an underwater communication test. The effects imply that this approach is promising in predicting the reliability of the community. It has also been discovered that reliability prediction accuracy can be advanced if the bushy guidelines include extra factors, the sign channel's records rate, and the machine's performance parameters. This study offers a practical approach to improving the performance and reliability of underwater communique networks. © 2024 IEEE.

关键词： algorithm communication environmental fuzzy logic

来源：评论

学校读者我要写书评

暂无评论

Studying the Effect of an Online Realm Based on Wearable Technology on Learners' Understanding

Studying the Effect of an Online Realm Based on Wearable Tec...

引用

2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Kirti Ali Khan, Mizan Chandigarh School of Business Department of Master of Computer Application India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350322309

An interactive system called imperative (AR) creates a realistic and genuine educational and learning environment. The latest crop clearly prefers innovation training over conventional teaching methods. Studies on scientific test techniques are still lacking, despite the fact that earlier research on virtual reality has shown some information on how it might enhance learning results in several subjects. Students need experimental information to better understand the phenomenon. The page discusses the steps involved in constructing & implementing a mobile application for a lab experiment that makes use of augmented reality technology. An extra educational resource for high school seniors is this. The prime purpose of this mobile-based augmented reality program for a scientific experiment is to provide thorough information in addition to conventional processes and educational materials. The experiments that will be shown in ElectroAR include a number of them. An professional review is conducted to evaluate input. In the future, user testing of ElectroAR in actual classroom environments will be conducted. © 2023 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection in Medical Images Using Deep Reinforcement Learning 2

Anomaly Detection in Medical Images Using Deep Reinforcement...

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Rastogi, Divya Sharma, Aparna Yadav, R.K. Varshney, Neeraj Saraswat, Laxmi Computer Science and Application Sharda University UP Greater Noida India Electronics & Communication Engineering Raj Kumar Goel Institute of Technology UP Ghaziabad India Gla University Department of Computer Engineering and Applications UP Mathura India Abes Engineering College Department of Computer Science UP Ghaziabad India

ISBN: (纸本)9798350371055

Anomaly detection in clinical pix is vital to identify and diagnose diseases. Deep reinforcement gaining knowledge is a practical gadget-mastering approach implemented for more than a few medical obligations. This technique applies a synthetic intelligence version to research by revealing an iterative procedure to discover a set of top-of-the-line parameters for ultimate selection-making. The cause of this examination is to use deep reinforcement mastering for anomaly detection in medical pix. This approach is used to identify strange areas in clinical pix, including tumors, mental diseases, and other abnormalities. Deep reinforcement mastering is mixed with Convolutional Neural Networks (CNNs) to extract capabilities from the medical pictures and then classify them consistent with their deviation from normal. The detection accuracy is evaluated using a novel assessment metric, referred to as the precision-recollect (PR) curve, which is designed to degree the version's accuracy. The results show that deep reinforcement learning can gain high-performance anomaly detection accuracy compared with conventional methods. © 2024 IEEE.

关键词： Accuracy Anomalous Evaluated Evaluation Measure

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376页 << < 17 18 19 20 21 22 23 24 25 26 > >>

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：