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

1,576 篇 会议
1 篇 期刊文献

馆藏范围

1,577 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

899 篇 工学
- 774 篇 计算机科学与技术...
- 533 篇 软件工程
- 253 篇 信息与通信工程
- 194 篇 控制科学与工程
- 130 篇 电气工程
- 84 篇 网络空间安全
- 78 篇 生物医学工程（可授...
- 75 篇 安全科学与工程
- 64 篇 交通运输工程
- 62 篇 生物工程
- 55 篇 电子科学与技术（可...
- 45 篇 动力工程及工程热...
- 43 篇 仪器科学与技术
- 42 篇 光学工程
- 42 篇 石油与天然气工程
306 篇 理学
- 164 篇 数学
- 83 篇 生物学
- 73 篇 统计学（可授理学、...
- 61 篇 物理学
- 37 篇 系统科学
- 33 篇 化学
267 篇 管理学
- 203 篇 管理科学与工程(可...
- 106 篇 图书情报与档案管...
- 84 篇 工商管理
- 34 篇 公共管理
114 篇 医学
- 80 篇 临床医学
- 77 篇 公共卫生与预防医...
- 64 篇 基础医学(可授医学...
51 篇 法学
- 48 篇 社会学
39 篇 经济学
- 39 篇 应用经济学
18 篇 文学
15 篇 教育学
11 篇 农学
2 篇 军事学
1 篇 艺术学

主题

193 篇 data models
157 篇 accuracy
153 篇 computational mo...
92 篇 training
86 篇 feature extracti...
86 篇 machine learning
77 篇 predictive model...
69 篇 data mining
68 篇 deep learning
63 篇 real-time system...
57 篇 big data
49 篇 adaptation model...
45 篇 security
44 篇 robustness
41 篇 decision making
40 篇 convolutional ne...
39 篇 cloud computing
36 篇 analytical model...
35 篇 neural networks
34 篇 optimization

机构

14 篇 lovely professio...
7 篇 shandong provinc...
7 篇 key laboratory o...
6 篇 college of mecha...
6 篇 institute of aer...
5 篇 lloyd institute ...
5 篇 college of intel...
5 篇 university of ch...
5 篇 national univers...
5 篇 department of co...
5 篇 shandong fundame...
5 篇 national univers...
5 篇 institute of aer...
4 篇 karnataka bangal...
4 篇 shanghai jiao to...
4 篇 school of comput...
4 篇 chitkara univers...
4 篇 new horizon coll...
4 篇 srm institute of...
4 篇 school of softwa...

作者

7 篇 nijhawan ginni
5 篇 jeanette miriam ...
5 篇 lu xiaobo
5 篇 singh navdeep
4 篇 nicola franco
4 篇 choudhry mani de...
4 篇 akhil karnam
4 篇 zhang rui
4 篇 yu zhang
4 篇 akshya j.
4 篇 lihui wang
4 篇 qu yuben
4 篇 wang lihui
4 篇 li lei
4 篇 dong chao
4 篇 dutt varun
4 篇 puri chetan
3 篇 yuangan wang
3 篇 junqi luo
3 篇 zhang lei

语言

1,273 篇 英文
303 篇 其他
4 篇 中文

检索条件"任意字段=2024 IEEE International Conference on Cognitive Computing and Complex Data"

共 1577 条记录，以下是931-940 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：

PiAGI: The Concept, Mechanism and Framework

PiAGI: The Concept, Mechanism and Framework

引用

Digital Twins and Parallel Intelligence (DTPI), ieee international conference on

作者： Qiang Li Zhuoya Ju Lili Fan Xin Liu Wenhua Liu Feiyue Wang Scientific and Technological Innovation Center Beijing China The School of Automation Beijing Institute of Technology Beijing China School of Big Data & Cyber Security China University of Petroleum Qingdao China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

As social production and living spaces gradually expand from the physical and information domains to the cognitive and social domains, this article addresses the new changes brought about by these expansions. Starting from the new impact of era of intelligent connectivity on social cognitive management, it analyzes the urgent need to enhance social cognitive management capabilities centered on cognitive decision-making, identifying the core key as Adversarial Generated Intelligence (AGI). It delves into the conceptual characteristics, operating mechanisms, and winning strategies of AGI, identifies the new challenges it faces, and proposes a Parallel Intelligence empowering AGI (PiAGI) system architecture through the empowerment of parallel intelligence. This provides theoretical support for improving social cognitive management capabilities centered on cognitive decision-making.

关键词： Decision making Systems architecture Production Digital twins Faces

来源：评论

学校读者我要写书评

暂无评论

Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

引用

Information Technology and computing (ICITCOM), international conference on

作者： Debby Alita Imam Ahmad Rhaishudin Jafar Rumandan Moh Erkamim Widyasmoro Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Islamic Education Management Study Program Institut Agama Islam Negeri Ambon Ambon Indonesia Smart City Information Systems Study Program Universitas Tunas Pembangunan Surakarta Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data.

关键词： Pediatrics Accuracy Computational modeling Prevention and mitigation data models Classification algorithms Decision trees data mining Information technology Diseases

来源：评论

学校读者我要写书评

暂无评论

Network-Based Analysis of Alzheimer's Disease Using ADNI-Derived Synthetic Connectomes

Network-Based Analysis of Alzheimer's Disease Using ADNI-Der...

引用

Pervasive and Intelligent computing (PICom), ieee conference on

作者： Carmela Comito Annalisa Socievole National Research Council of Italy (CNR) Institute for High Performance Computing and Networking Rende Italy

ISBN: (数字)9798331522742

ISBN: (纸本)9798331522759

Alzheimer's disease (AD) is a progressive neurode-generative disorder characterized by cognitive decline and disrupted brain structural and functional connectivity. Assessing these disruptions has become increasingly important in recent years. However, there remains a limited body of research that examines the various stages of AD through the lens of complex network analysis, considering multiple topological scales. The aim of this study is to investigate the alterations in the structural brain networks of AD patients using the principles of complex network theory. We focus on ADNI-derived connectomes that have been generated from both linear and nonlinear brain network models and characterized by a network connectivity information comparable to the one of the original data. The topological parameters of each brain network were computed for both AD patients and the control group, and subsequently, the results were averaged across all networks within a group. Independently from the network model chosen, our findings reveal decline in network centrality (degree and betweenness), modularity of the network modules, clustering coefficient, and global efficiency in AD patients compared to healthy controls. Such results suggest that at predementia stages, brain network parameters may be useful in identifying subjects who will show fast clinical progression.

关键词： Training Computational modeling Biological system modeling complex networks Biomarkers Brain modeling Prediction algorithms data models Alzheimer's disease Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Classification of cognitive Stress with StressGAN-GP

Classification of Cognitive Stress with StressGAN-GP

引用

Communication, computing and Signal Processing (IICCCS), ieee international conference on

作者： Sudhangshu Sarkar Aniruddha Chandra Anilesh Dey Department of Electronics & Communication Engineering National Institute of Technology Durgapur India Department of Electrical Engineering Narula Institute of Technology West Bengal India Principal Nagar College Murshidabad India

ISBN: (数字)9798350390759

ISBN: (纸本)9798350390766

This paper proposes an innovative Deep Learning (DL) architecture for classifying cognitive stress using a novel hybrid model, StressGAN-GP. The increasing prevalence of stress-related disorders in modern society necessitates accurate and efficient methods for stress detection and classification. This study aims to improve the model's generalization to various stress-inducing events by utilizing the capabilities of Generative Adversarial Networks (GANs) to synthesize stress-related patterns from limited labelled data. The suggested StressGAN-GP system blends the Gradient Penalty's interpretability with GANs' prowess in producing realistic stress characteristics. The proposed StressGAN-GP framework combines the strengths of GANs in generating realistic stress features with the interpretability of Gradient Penalty. The GAN component generates synthetic stress patterns, enriching the training dataset, while the GP component provides a probabilistic framework for stress classification, offering insights into model uncertainty. Test findings on an extensive dataset show that StressGAN-GP outperforms conventional classification models in terms of performance. The model accurately distinguishes between stressed and non-stressed individuals bearing an accuracy of 98.78%, showcasing its potential for real-world stress monitoring and intervention applications. This research contributes to advancing the field of affective computing and lays the foundation for more robust and interpretable models in the realm of cognitive stress classification.

关键词： Deep learning Accuracy Uncertainty Computational modeling Computer architecture Generative adversarial networks Feature extraction data models Real-time systems Stress

来源：评论

学校读者我要写书评

暂无评论

Graph Network Modeling of Brain Connectivity: An Exploration of Word and Object Recognition Tasks

Graph Network Modeling of Brain Connectivity: An Exploration...

引用

international conference on Signal Processing Proceedings (ICSP)

作者： Wenhao Jiang Lin Ma Haifeng Li Faculty of Computing Harbin Institute of Technology Harbin China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

Understanding the neural mechanisms underlying cognitive processes, such as word and object recognition, is crucial for advancing cognitive neuroscience. This study explores the neural mechanisms underlying word and object recognition using a graph-based approach, BrainGNN, applied to fMRI data. By focusing on the fMRI scans related to these cognitive tasks, we constructed ROI-wise functional connectivity matrices based on the AAL atlas and employed the BrainGNN model for classification. The model effectively distinguished between tasks, achieving an accuracy of 91.67%. Significant differences were observed in brain regions such as the Temporal Pole and Supplementary Motor Area. This research contributes to a deeper understanding of the brain’s functional connectivity and the neural mechanisms that underpin word and object recognition.

关键词： Accuracy cognitive processes cognitive neuroscience Focusing Functional magnetic resonance imaging Signal processing Brain modeling Motors Object recognition Biological neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing Finger Motion Measurement System and data Export Techniques for End-Users’ Operation

Enhancing Finger Motion Measurement System and Data Export T...

引用

ieee international conference on Big data and Cloud computing (BdCloud)

作者： Sinan Chen Atsuko Hayashi Masahide Nakamura Kobe University Nada Kobe Japan Kobe University Suma Kobe Japan RIKEN Center for Advanced Intelligence Project Kobe University Tokyo Japan

ISBN: (数字)9798331510268

ISBN: (纸本)9798331510275

As Japan’s population continues to age, the rise in dementia cases has become a major societal issue. For early diagnosis and rehabilitation of dementia, research has focused on techniques that measure hand-motor skills to evaluate cognitive function. Previous systems faced challenges such as the need for improved hand movement evaluation methods, difficulty in system operation and implementation by end-users, and inadequate methods for data provision and visualization. This paper aims to enhance a web service to assess manual dexterity through tapping tasks. The proposed system has revised the evaluation method for scenarios where multiple tapping actions are performed under the same instruction, enabling more accurate assessments of motor function. Additionally, by employing Docker container technology to simplify system startup and converting recorded data into the more user-friendly XLSX format for use in applications like Excel, the system has improved data handling, making it more accessible for end-users.

关键词： Hands Web services Systems operation data handling data visualization Medical services Manuals Motors Motion measurement Dementia

来源：评论

学校读者我要写书评

暂无评论

Optimizing Quality of Service in Fog computing using Blockchain Integration: Exploring Approaches, Challenges, and Performance Evaluation

Optimizing Quality of Service in Fog Computing using Blockch...

引用

Big data & Machine Learning (ICBDML), ieee international conference on

作者： Rosahn G. Belsare P. B. Ambhore Department of Computer Science & Engineering Government College of Engineering Amravati India

ISBN: (数字)9798350374100

ISBN: (纸本)9798350374117

In today’s computing era, fog computing has emerged as a transformative paradigm, facilitating real-time data processing at the network edge to reduce latency and enhance responsiveness. However, ensuring optimal Quality of Service (QoS) in fog environments, while safeguarding data integrity, presents a tough challenge. This research endeavours to address this critical concern by introducing a comprehensive framework that systematically boosts QoS through the meticulous integration of blockchain technology. Probing into the association of fog computing and blockchain, this study pioneers sophisticated strategies that target the reduction of latency, the amplification of scalability, and the precision management of resources. Through complex process of implementation and systematic evaluation, our proposed strategies manifest demonstrable enhancements across key QoS metrics, prominently including latency and throughput. These enhancements are substantiated through the inclusion of practical case studies that highlight the tangible benefits of our approach in a diverse range of scenarios. This research advances the understanding of the synergistic potential of fog computing and blockchain, while simultaneously empowering practitioners with actionable insights to bind these technologies harmoniously. By combining these innovations, both enhanced QoS and fortified data processing at the network edge become attainable objectives, furthering the evolution of modern computing paradigms.

关键词： Technological innovation Systematics Scalability Quality of service Throughput data processing Consensus protocol

来源：评论

学校读者我要写书评

暂无评论

Reverse engineering the brain input: Network control theory to identify cognitive task-related control nodes

Reverse engineering the brain input: Network control theory ...

引用

Annual international conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： Zhichao Liang Yinuo Zhang Jushen Wu Quanying Liu Department of Biomedical Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The human brain receives complex inputs when performing cognitive tasks, which range from external inputs via the senses to internal inputs from other brain regions. However, the explicit inputs to the brain during a cognitive task remain unclear. Here, we present an input identification framework for reverse engineering the control nodes and the corresponding inputs to the brain. The framework is verified with synthetic data generated by a predefined linear system, indicating it can robustly reconstruct data and recover the inputs. Then we apply the framework to the real motor-task fMRI data from 200 human subjects. Our results show that the model with sparse inputs can reconstruct neural dynamics in motor tasks (EV =0.779) and the identified 28 control nodes largely overlap with the motor system. Underpinned by network control theory, our framework offers a general tool for understanding brain inputs.

关键词： Linear systems Reverse engineering Functional magnetic resonance imaging Motors Brain modeling Control theory Engineering in medicine and biology Synthetic data

来源：评论

学校读者我要写书评

暂无评论

Application of Big data Technology in data Prediction Models Based on Deep Learning Algorithms

Application of Big Data Technology in Data Prediction Models...

引用

Distributed computing and Electrical Circuits and Electronics (ICDCECE), ieee international conference on

作者： Yong He Lijie Ma Foundational Courses Department Wuhan Donghu University Wuhan Hubei China

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

How to solve the problems faced by traditional statistical models such as large scale, variability and high complexity of data? In this regard, this article proposes a GAN algorithm. The article first defines the data prediction problem, defines the problem goal of this article as the prediction of stock prices, and then applies the adversarial generation network to the stock price prediction problem. Research has found that GAN can generate multiple possible stock price sequences, thereby providing multiple possibilities for future trends. Afterwards, the article establishes a prediction model based on big data, and completes the experimental test of the algorithm of this article through the model. The test results show that the data results of this model in the accuracy test are between 89% and 98%. By making full use of large-scale data samples and distributed computing capabilities, the model can better capture the complex associations and patterns in the data.

关键词： Training Computational modeling Distributed databases Predictive models Big data Parallel processing Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Activity Recognition of Delivery Personnel by Integrating LSTM and CNN on Wearable Sensory data

Activity Recognition of Delivery Personnel by Integrating LS...

引用

Social computing and Networking (SocialCom), ieee international conference on

作者： Apei Li Linhui Cheng Xiao Zhang Yuchen Wang College of Computer Science South-Central Minzu University Wuhan China Wuhan Britain-China High School Wuhan China

ISBN: (数字)9798331521097

ISBN: (纸本)9798331521103

Activity recognition for delivery personnel is growing in significance, as it empowers the quantification and evaluation of their performance by learning their operational behavior related to energy expenditure. This paper presents a deep learning model integrating LSTM and CNN, automating feature extraction and refining activity classification. LSTM captures temporal dependencies, while CNN handles spatial sensitivity, enabling the model to identify complex patterns. The model has demonstrated impressive accuracy, reinforcing its position as a tool for enhancing efficiency and well-being in logistics distribution.

关键词： Deep learning Social computing Sensitivity Computational modeling Refining Personnel Human activity recognition Wearable devices Long short term memory Logistics

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158页 << < 90 91 92 93 94 95 96 97 98 99 > >>

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：