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

4,140 篇 会议
38 册 图书
6 篇 期刊文献

馆藏范围

4,184 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,738 篇 工学
- 2,466 篇 计算机科学与技术...
- 2,041 篇 软件工程
- 615 篇 生物工程
- 587 篇 信息与通信工程
- 364 篇 生物医学工程（可授...
- 266 篇 控制科学与工程
- 216 篇 电气工程
- 211 篇 光学工程
- 148 篇 安全科学与工程
- 136 篇 机械工程
- 124 篇 电子科学与技术（可...
- 118 篇 化学工程与技术
- 107 篇 交通运输工程
- 91 篇 动力工程及工程热...
1,367 篇 理学
- 673 篇 数学
- 645 篇 生物学
- 331 篇 统计学（可授理学、...
- 307 篇 物理学
- 197 篇 系统科学
- 127 篇 化学
720 篇 管理学
- 393 篇 管理科学与工程(可...
- 388 篇 图书情报与档案管...
- 237 篇 工商管理
342 篇 医学
- 315 篇 临床医学
- 308 篇 基础医学(可授医学...
- 221 篇 药学(可授医学、理...
- 125 篇 公共卫生与预防医...
159 篇 法学
- 138 篇 社会学
157 篇 教育学
- 155 篇 教育学
141 篇 农学
- 140 篇 作物学
89 篇 经济学
9 篇 军事学
5 篇 文学

主题

528 篇 machine learning
245 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
93 篇 accuracy
93 篇 machine learning...
83 篇 forecasting
76 篇 convolutional ne...
70 篇 predictive model...
70 篇 feature extracti...
59 篇 artificial intel...
53 篇 students
51 篇 learning systems
48 篇 decision trees
48 篇 training
47 篇 reinforcement le...
47 篇 computational mo...
47 篇 computer vision
46 篇 internet of thin...
41 篇 neural networks

机构

46 篇 chitkara univers...
15 篇 graphic era hill...
10 篇 college of manag...
9 篇 graphic era deem...
8 篇 computer science...
8 篇 beijing universi...
7 篇 school of comput...
7 篇 school of comput...
7 篇 school of comput...
7 篇 department of in...
6 篇 università di ca...
6 篇 infn sezione di ...
6 篇 north-west unive...
6 篇 computer science...
6 篇 lovely professio...
6 篇 in2p3 lpc campus...
6 篇 kkr and ksr inst...
6 篇 institut univers...
6 篇 national centre ...
6 篇 greater bay area...

作者

18 篇 kukreja vinay
16 篇 mehta shiva
10 篇 william p.
8 篇 sharma vikrant
7 篇 mahamudul hasan
7 篇 shiva mehta
7 篇 hasan mahamudul
6 篇 chen a.
6 篇 benoit d.m.
6 篇 ferrara g.
6 篇 ardid m.
6 篇 calvo d.
6 篇 gagliardini s.
6 篇 eddymaoui a.
6 篇 kulikovskiy v.
6 篇 labalme m.
6 篇 gal t.
6 篇 bozza c.
6 篇 khatun a.
6 篇 kalekin o.

语言

2,638 篇 英文
1,545 篇 其他
112 篇 中文

检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

共 4184 条记录，以下是3311-3320 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：

5th international conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2024

5th International Conference on Innovative Intelligent Indus...

引用

5th international conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2024

ISBN: (纸本)9783031807596

the proceedings contain 61 papers. the special focus in this conference is on Innovative Intelligent Industrial Production and Logistics. the topics include: An Out-of-Sample Clustering Ensemble Method for Defect Detection and Classification in Metal Additive Manufacturing;Advanced Process Monitoring and OEE Metrics: Leveraging AASs for Efficiency;obsolescence Forecasting of Intel Processors: A Transformers Approach;machine learning Tool for Yield Maximization in Cream Cheese Production;comparative Evaluation of Irregular Shape Strip-Packing Algorithms;an Inventory Management Support Tool through Indirect Q-Value Estimation: A Combined Optimization and Forecasting Approach;multiscale Clustering to Improve Anomaly Detection in Nuclear Equipments;clustering Analysis for Forecasting Medicine Consumption;a Decision Support System of the Configuration of a Supermarket in a Components Company for the Automotive Industry;a Distributed Framework for Cooperative Scheduling of Production, Transportation, and Maintenance Using Multi-Agent Systems;the Role of Actor’s Creative Self-efficacy in AI Enabled Value Creation;building Realistic Environment from computer Vision Approach Applied to Manufacturing Simulation in the Digital Twin Context;towards a Process-Based Industry 5.0 Maturity Model: A Feasibility Study in Supply Chain;a Multi-objective Genetic Algorithm Approach for Multi-component Products Recovery and Remanufacturing Planning;reinforcement learning for Optimizing Routing in the Production Supply of Matrix Production Systems;an Innovative Fault Detection Robotic Tool for Overhead Cranes in Industries: Magnetic Wheel Modelling and Experimental Validation;current Trends and Future Challenges to Put Circular Manufacturing in Practice;enhancing Human – Robot Collaboration in the Industry 5.0 Framework with Physics-Informed Neural Networks: application to Collision Detection;AI-Driven Smart Air Conditioning System for a Sustainable and Energy-Efficient Industrial Future.

关键词：

来源：评论

学校读者我要写书评

暂无评论

5th international conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2024

5th International Conference on Innovative Intelligent Indus...

引用

5th international conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2024

ISBN: (纸本)9783031807749

关键词：

来源：评论

学校读者我要写书评

暂无评论

9th international conference on Computing and Informatics, ICOCI 2023

9th International Conference on Computing and Informatics, I...

引用

9th international conference on Computing and Informatics, ICOCI 2023

ISBN: (纸本)9789819995882

the proceedings contain 55 papers. the special focus in this conference is on Computing and Informatics. the topics include: Sentiment Analysis of Arabic Dialects: A Review Study;charting Inclusive Digital Society Research Trends: A Bibliometric Analysis of E-Participation through Social Media;systematic Literature Review and Bibliometric Analysis on Addressing the Vanishing Gradient Issue in Deep Neural Networks for Text Data;a Test Dataset of Offensive Malay Language by a Cyberbullying Detection Model on Instagram Using Support Vector machine;tikTok Video Cluster Analysis Based on Trending Topic;a Video Summarization Method for Movie Trailer-Genre Classification Based on Emotion Analysis;e-Nose: Spoiled Food Detection Embedded Device Using machine learning for Food Safety application;an Analysis of Objective Function Modification Approaches in Routing Protocols for Low Power and Lossy Networks: A Fuzzy Logic-Based Perspective;an Empirical Study of Label Size Effect on Classification Model Accuracy Using a Derived Rule from the Holy Quran Verses;large Scale Web Crawling and Distributed Search Engines: Techniques, Challenges, Current Trends, and Future Prospects;anomalies in Mooring (thin) Lines: Causes, Risk Mitigations, and Real Time Consequences of Failure – A Comprehensive Review;data Analytics Modelling System for Short Courses at Seberang Jaya Community College;examining the Software Developers’ Perception in Open-Source Software of Blockchain Project Using Association Rules Mining;support Vector machine for Satellite Images Classification Using Radial Basis Function Kernel Method;a Regression Test Case Prioritization Framework for Software Sustainability;towards a Sustainable Digital Society: Supporting Producer Mobility in Named Data Networking through Immobile Anchor-Based Mechanism.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards Eco-Resilient Networks: CNN-Enabled Anomaly Detection for Green Cybersecurity

Towards Eco-Resilient Networks: CNN-Enabled Anomaly Detectio...

引用

Advancement in Electronics & Communication Engineering (AECE), international conference on

作者： Arman Kalra Kanwarpartap Singh Gill Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798350364729

ISBN: (纸本)9798350364736

Cybersecurity is a major concern across various industries today. It is directly related to global goals such as enhancing infrastructure and industrial innovation (SDG 9) and fostering peace, justice, and strong institutions (SDG 16). Traditional problem-detection methods are becoming less effective as cyber threats evolve and increase in frequency, necessitating new approaches. this article introduces a novel technique for detecting abnormal patterns in network traffic using Convolutional Neural Networks (CNNs). the model is trained and tested on the CICIDS2017 dataset, which includes a wide range of both normal and suspicious network activities. Our CNN-based approach achieved a remarkable accuracy of 93.64%, outperforming conventional techniques. this method not only enhances cybersecurity but also contributes to SDG 9 by promoting resilient infrastructure. Additionally, it aids in building robust institutions by swiftly detecting and mitigating cyber threats, aligning with SDG 16. the performance of the model, including metrics like accuracy, recall, F1 score, and confusion matrices, has been thoroughly analyzed. these results underscore the importance of leveraging advanced machine learning techniques, especially deep learning, in cybersecurity solutions. Creating secure and sustainable digital environments depends heavily on integrating such innovations. Our model’s ability to accurately detect network anomalies demonstrates the potential of CNNs to revolutionize cybersecurity practices. this study advocates for the continued application of deep learning methods to address the growing challenges in cybersecurity, contributing to the achievement of key sustainable development goals while ensuring the stability and security of digital systems.

关键词： Deep learning Training Technological innovation Accuracy Telecommunication traffic Convolutional neural networks computer security Sustainable development Anomaly detection Resilience

来源：评论

学校读者我要写书评

暂无评论

An Approach to Detect Air Quality using machine learning and Data Analysis Tools

An Approach to Detect Air Quality using Machine Learning and...

引用

international conference on Computing and Networking Technology (ICCNT)

作者： Anirban Roy Mehnaz Rashid Mim Department of Computer Science & Engineering Daffodil International University Dhaka Bangladesh

After the headway of the computerized structure, Information science hopes to be a fundamental part here. Information science stores and investigates information of various sorts of banks, foundations, workplaces and others. the framework answers in this manner subject to learning. Precise learning gives the exact outcome in any case its produce blended forecast. Along these lines, this learning is the most significant part for computerized framework. Information science is basically expectation based. machine can imagine result without help from some other individuals rely on the given dataset. Generally, that predicted outcome is more accurate, once in a while not. the certified guess is obligated to learning accuracy. thusly, Information science is distributed four frameworks reliant upon learning, for example, Ostensible, Ordinal, Discrete, Ceaseless. Directed systems are reliant upon marked information. Also, unstructured dataset is utilized in unaided realizing, where model information is given as of now doesn't yield. In this work we attempted to anticipate lessen air contamination in various nations with python programming language, Google studio and RFM run application. For that we gathered a dataset from public outflows answered to the Show on Lengthy reach Transboundary Air Contamination (LRTAP Show). Air poison discharges — EEA datasets. A gigantic extent of individuals kicks the bucket purposes behind vascular disease at of air contamination. Early discovery of air contamination might help the patient defeat the infection. this might be an approach to forestalling this sickness. the Information science method is essentially usable systems in this manner. In this paper the result is the gamble variables of air toxins which is in table 4 and the aftereffect of RMSE in XG Lift calculation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Expression of Concern for: machine learning techniques for identifying Cyberbullying on digital networks

Expression of Concern for: Machine Learning techniques for i...

引用

Innovative Trends in Information Technology (ICITIIT), international conference on

作者： N. Gayathri Prawin R Ranjith kumar A Manikandan R Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore Tamilnadu India

ISBN: (数字)9781665494144

ISBN: (纸本)9781665494151

With the proliferation of virtual entertainment platforms around the world, particularly among young people, digital taunting and enmity have become real and annoying problems that networks must address. threats can use these levels to attack and weaken others in their networks. To combat digital tormenting, various strategies and tactics have been used or proposed, including early detection and alarms that both detect and protect victims from such attacks. machine learning techniques with Artificial Intelligence Framework are being widely used to identify specific linguistic patterns that danger uses to hunt for their victims. the Feeling Analysis (FA) of virtual entertainment content is one of the expanding fields of research in AI. FA makes it possible to gradually identify online harassment and continuously recognize cyberbullying. this study recommends a SA model to identify cyberbullying messages in Facebook web-based entertainment. SVM and MAXENT classifier, controlled AI arrangement tools, are employed in this model. When a higher n-grams language model is applied to such texts in correlation with analogous prior research, the findings of the investigations carried out using this model showed encouraging results. Similar patterns in the results showed that these classifiers preferred execution measures over other classifiers on such remarks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deep learning Forecast of Cognitive Workload Using fNIRS Data

Deep Learning Forecast of Cognitive Workload Using fNIRS Dat...

引用

IEEE international conference on Human-machine Systems

作者： Nicolas Grimaldi Yunmei Liu Ryan McKendrick Jaime Ruiz David Kaber Industrial and Systems Engineering University of Florida Gainesville FL USA Industrial Engineering University of Louisville Louisville KY USA Mission Systems Northrop Grumman Falls Church VA USA Computer & Information Science & Engineering University of Florida Gainesville FL USA

ISBN: (数字)9798350315790

ISBN: (纸本)9798350315806

Introduction: In the domain of helicopter piloting, the pilot’s performance is driven by many cognitive processes, demanding substantial cognitive resources. the pilot must maintain situation awareness and perform rapid decision-making. An objective of integrated helicopter technologies is to predict and effectively manage pilot cognitive workload to ensure safety and efficiency throughout flight. Methods: In this study, we collected data on seven participants, including three experienced pilots, using a UH-60V cockpit simulator to perform 46 distinct trials under various flight conditions. fNIRS neuroimaging was used to collect high-resolution neurophysiological data for exploring and forecasting cognitive workload using a collection of deep learning models. Model implementation: three deep learning architectures are detailed in this work: a stacked LSTM model, a CNN-LSTM hybrid, and a transformer model. Results: An evaluation of three Seq2Seq models, each with two distinct forecasting lengths (10s and 30s), revealed LSTM-based architectures as superior performers for 10s forecasting tasks. Discussion: the LSTM-based models’ superior performance suggested potential limitations with the transformer’s self-attention mechanisms for our specific application. Surprisingly, the CNN-LSTM architecture did not surpass the stacked LSTM model’s performance during forecasting tasks. Conclusion: Future research directions include exploring diverse time-series Seq2Seq methods and forecasting cognitive workload as ordinal measures, offering insights into shifting cognitive demands.

关键词： Deep learning Analytical models Predictive models Transformers Data models Real-time systems Safety

来源：评论

学校读者我要写书评

暂无评论

application of machine learning algorithm for prediction of heart disease

Application of machine learning algorithm for prediction of ...

引用

Advances in Computing, Communication Control and Networking (ICAC3N), international conference on

作者： Ankit Kumar Upadhyay Sharzeel Saleem Adarsh Anubhav Shrddha Sagar Department of Computer Science and Engineering Galgotias University Greater Noida India

Healthcare is the one the domain in which every organization is working on it globally. It need to make it better and better via different researches and the innovations in this sector. machine learning is the most used algorithm in every sector and organization. It not merely transforming the field of healthcare but also able to emulate the various human intelligence from the surrounding in order to solve various problems. machine learning in health care sector has shown its various application in it. Disease prediction is one of the applications of it. this study helps to predict heart diseases with the help of its algorithm to determine the risk and treat the patient in the healthcare system. In this paper we have taken out the data from the kaggle and implemented it using the Jupiter notebook tool. the three algorithm we have implemented (naïve bayes, decision tree and random forest) out of which random forest is giving. Hence, with the help of the following algorithms it is possible for us to predict the heart disease with more accuracy. this research will able to predict various disease over its various symptoms more easily and accurately.

关键词： Heart Technological innovation machine learning algorithms Jupiter Human intelligence Medical services Organizations

来源：评论

学校读者我要写书评

暂无评论

Offer and Deal-Quality Prediction using machine learning and Fuzzy approach: A Shark Tank India Case Study 22

Offer and Deal-Quality Prediction using Machine learning and...

引用

proceedings of the 4th international conference on Information Management & machine Intelligence

作者： Atharva Parikh Shreya Jain Parikshit N. Mahalle Gitanjali Rahul Shinde Information Technology Vishwakarma Institute of Information Technology India Department of Artificial Intelligence and Data Science Vishwakarma Institute of Information Technology India Computer Science and Engineering Vishwakarma Institute of Information Technology India

ISBN: (纸本)9781450399937

the Hindi-language television program Shark Tank India, which airs on Sony LIV, has changed the conversation in many Indian homes and raised awareness of entrepreneurship and start-ups. Shark Tank India depicts the background of each start-up and the business owners pitching their wholesome ideas to a panel of Sharks (Investors) who are entrepreneurs in various industries. Sharks then opt to invest in exchange for equity in the company (some percentage of ownership). Two of the major problems faced by startups before coming on the show is an understanding of what role each business factor plays in determining the proposition of offer by the sharks and the quality of deal done with or without negotiation with the sharks. To address this issue, we created a new dataset for Shark Tank India that contains essential features representing information about participating startups. then we used this data to propose two ambient systems. the first one uses machine learning to predict whether investors will make an offer to the pitching team, with the Artificial Neural Network (ANN) model performing best with an F1 score of 87.09%, and the second one uses a fuzzy system consisting of 22 rules to categorize the quality of a deal after an investment is made.

关键词： Artificial Neural Networks

来源：评论

学校读者我要写书评

暂无评论

Single-Molecule Bioelectronic Sensor: Improving Reliability with machine learning Approaches 5

Single-Molecule Bioelectronic Sensor: Improving Reliability ...

引用

5th IEEE international conference on Flexible and Printable Sensors and Systems, FLEPS 2023

作者： Sarcina, L. Scandurra, C. Caputo, M. Catacchio, M. Di Franco, C. Bollella, P. Chironna, M. Torricelli, F. Esposito, I. Osterbacka, R. Scamarcio, G. MacChia, E. Torsi, L. University of Bari Dept. Chemistry Bari Italy University of Bari Dipartimento di Scienze Biomediche e Oncologia Umana Bari Italy University of Brescia Brescia Italy University of Dusseldorf Dusseldorf Germany Abo Akademi Faculty of Science and Engineering Turku Finland University of Bari Dept. of Physics Bari Italy University of Bari Dept. of Pharmaceutical Sciences Bari Italy

ISBN: (纸本)9781665457330

Digitizing biomarkers analysis by quantifying them at the single-molecule level is the new frontier for advancing the science of precision health. the enhancement of the technical capabilities of bioelectronics systems, by giving clinicians the possibility to rely on biomarkers quantifications down to the single-molecule, holds the potential to revolutionize the way healthcare is provided. Such an analytical tool will indeed enable clinicians to associate a biomarker tiniest increase to the progression of a disease, particularly at its early stage.1 Eventually, physicians will be able to identify the very moment in which the illness state begins. Such an occurrence will enormously enhance their ability of curing diseases by supporting better prognosis and permitting the application of precise treatment methods. the single molecule bio-electronic smart system array for clinical testing - SiMBiT - technology has been developed within the blooming field of precision medicine, leveraging on the single molecule with large transistor (SiMoT)2 lab-based technology that can perform single-molecule detection of both proteins and DNA bio-markers.3,4 Specifically, the SiMBiT technology has lately developed the SiMoT lab-based device into a cost-effective portable prototype multiplexing array that integrates, with a modular approach, standard components and interfaces with novel materials and exhibits enhanced sensing capabilities. the SiMBiT prototype has proven its potency in early detection of pancreatic cancer, being capable to discriminate among low-grade and high-grade mucinous cyst's lesions in peripheral biofluids, such as plasma samples. In this perspective, machine learning approaches play a pivotal role in developing classifiers for a fast, reliable multiparametric biosensors output. Supervised model based on multivariate data processing has been undertaken to enable multiplexing, i.e. the simultaneous quantification of three biomarkers, namely MUC1 and CD55 proteins

关键词： Biomarkers

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419页 << < 328 329 330 331 332 333 334 335 336 337 > >>

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：