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

705 篇 会议
8 篇 期刊文献
4 册 图书

馆藏范围

718 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

340 篇 工学
- 282 篇 计算机科学与技术...
- 200 篇 软件工程
- 114 篇 信息与通信工程
- 57 篇 控制科学与工程
- 52 篇 生物医学工程（可授...
- 46 篇 生物工程
- 40 篇 电气工程
- 31 篇 电子科学与技术（可...
- 24 篇 光学工程
- 24 篇 安全科学与工程
- 23 篇 动力工程及工程热...
- 21 篇 机械工程
- 20 篇 交通运输工程
- 19 篇 网络空间安全
- 15 篇 仪器科学与技术
- 13 篇 建筑学
163 篇 理学
- 101 篇 数学
- 54 篇 生物学
- 41 篇 统计学（可授理学、...
- 34 篇 物理学
- 20 篇 化学
- 18 篇 系统科学
110 篇 管理学
- 70 篇 管理科学与工程(可...
- 55 篇 图书情报与档案管...
- 44 篇 工商管理
58 篇 医学
- 43 篇 基础医学(可授医学...
- 42 篇 临床医学
- 35 篇 药学(可授医学、理...
26 篇 法学
- 23 篇 社会学
17 篇 教育学
- 14 篇 教育学
11 篇 经济学
6 篇 农学
4 篇 文学

主题

35 篇 cognitive radio
22 篇 cognitive system...
15 篇 machine learning
13 篇 computational mo...
12 篇 deep learning
11 篇 feature extracti...
9 篇 big data
9 篇 accuracy
8 篇 internet of thin...
8 篇 decision making
7 篇 electroencephalo...
7 篇 neural networks
7 篇 semantics
7 篇 fuzzy cognitive ...
7 篇 data models
6 篇 object detection
6 篇 edge computing
5 篇 covid-19
5 篇 cognitive comput...
5 篇 data mining

机构

8 篇 college of intel...
6 篇 fraunhofer insti...
6 篇 tianjin key labo...
6 篇 uttaranchal inst...
5 篇 institute of art...
5 篇 anhui provincial...
5 篇 lovely professio...
5 篇 tianjin key labo...
5 篇 college of compu...
4 篇 school of comput...
4 篇 school of comput...
4 篇 centre for inter...
4 篇 college of mecha...
4 篇 collage of engin...
3 篇 symbiosis instit...
3 篇 anhui university...
3 篇 copelabs - cogni...
3 篇 school of comput...
3 篇 university of ch...
3 篇 univ connecticut...

作者

4 篇 zhao haifeng
4 篇 gayathri n.
4 篇 dutt varun
4 篇 haifeng zhao
3 篇 kanna r. kishore
3 篇 lorenz jeanette ...
3 篇 wang tao
3 篇 wenbin zhang
3 篇 jeanette miriam ...
3 篇 godinho antónio
3 篇 mankun zhao
3 篇 wang li
3 篇 yang jinzhu
3 篇 chao dong
3 篇 zhang kai
3 篇 qu yuben
3 篇 anandakumar h.
3 篇 r. kishore kanna
3 篇 anita gehlot
3 篇 bhasin harsh

语言

682 篇 英文
33 篇 其他
10 篇 中文

检索条件"任意字段=2023 International Conference on Cognitive Computing and Complex Data, ICCD 2023"

共 718 条记录，以下是621-630 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：

Analysis of future trend and opportunity in the emerging 5G IoT scenario

Analysis of future trend and opportunity in the emerging 5G ...

引用

Advance computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Ramakrishnan Raman Joel Alanya-Beltran Rajesh Singh Snehal Trivedi Biju G. Pillai M. Kalyan Chakravarthi Symbiosis Institute of Business Management Pune & Symbiosis International (Deemed University) Pune Maharashtra India Universidad Tecnológica del Perú Uttaranchal Institute of Technology Uttaranchal University India Department of Mech Parul University Department of IT & Business Analytics Sri Balaji University Pune (SBUP) School of Electronics Engineering VIT-AP University Amaravathi India

Nowadays, there are many concepts focused on the Iot devices (IoT), such as virtual reality, elevated streaming media, Automated vehicles, intelligent ecosystems, digital healthcare, etc. The requirements for these applications include high throughput, low latency, increased capacity, higher data rates, and enormous bandwidth. The Internet of Things (IoT) is revolutionary because it allows for interoperability between previously incompatible networks, which has led to a dramatic shift in the way people interact with and perceive the (HetNets). The ultimate goal of IoT is to bring plug-and-play technology to market, providing users with versatility, remote access control, and ease of use. The IoT technology is presented in this article from a high-level perspective, including its statistical and architectural trends, application cases, difficulties, and hopes for the future. A thorough and in-depth assessment of the developing 5G-IoT situation is also included in the study. Cellular networks of for the mainstream use of IoT (internet of things, the networks(5G) offers important advancement of technology. This consist of network function transformation (NFV), operating system smart sensor monitoring (SD-WSN), massive-MIMO (M-MIMO), coordinate multiple access processing (CoMP), equipment (D2D) interactions, cellular technologies, several (MIMO), massive-MIMO, and cognitive radios (CRs). This article gives a thorough assessment of these major enabling capabilities. The last section of the article examines difficulties with 5G-IoT deployment caused by high data rates that need edge computing on IoT devices and platforms that are located in the cloud.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ECA-RetinaNet: A Novel Self-Attention RetinaNet for Environmental Microorganism Image Object Detection

ECA-RetinaNet: A Novel Self-Attention RetinaNet for Environm...

引用

IEEE international conference on Big data

作者： Hechen Yang Jinzhu Yang Tao Jiang Xin Zhao Jinghua Zhang Peng Zhao Ao Chen Qianqing Nie Marcin Grzegorzek Chen Li Microscopic Image and Medical Image Analysis Group College of Medicine and Biological Information Engineering Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang Liaoning China School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Chengdu China International Joint Institute of Robotics and Intelligent Systems Chengdu University of Information Technology Chengdu China Institute of Medical Informatics University of Luebeck Luebeck Germany

The detection of environmental microorganisms is always a difficult task, e specially when the multi-scale environment is complex. For tiny objects in microscopic images, current detection methods face the challenge of accurate identification and localization. In contrast, we propose a convolutional neural network (ECA-RetinaNet) for microscopic object detection of which underlying dataset is a high-quality EMDS-7 dataset. The accuracy of ECA-RetinaNet is high, with a high mean Average Precision (mAP) value of 81.42% in the Environmental Microorganisms (EMS) detection task. Its accuracy has been higher than that of the two-stage object detection network.

关键词：

来源：评论

学校读者我要写书评

暂无评论

AD Classification and Detection Using Neuroimaging data

AD Classification and Detection Using Neuroimaging Data

引用

Mobile, Intelligent, and Ubiquitous computing conference (MIUCC), international

作者： Salma Abed Mohamed Mourad Mohamed Mohamed Abdelkreem Mostafa Ashraf Youssef Talaat Walaa H. Elashmawi Misr International University) Computer Science Cairo Egypt

Alzheimer's disease (AD) is the most prevalent type of dementia, a progressive brain illness that typically manifests in old age. Alzheimer's disease will affect 1.2 percent of the world's population by 2046, according to the World Health Organisation. If nothing is done to reduce that figure, the number of fatalities from Alzheimer's and dementia in Egypt will reach 6,975 in 2020. Egypt is rated 148th in the world. Early Alzheimer's diagnosis is critical for informing patients about the severity of their condition and empowering them to take medication and other preventative measures. MRI and PET scans, have been used to aid in diagnosing along with machine learning approaches. Early AD diagnosis was required to accurately distinguish AD cases from standard control (NC) subjects. Naive Bayes (NB), Support Vector Machine (SVM), and k-Nearest Neighbors (KNN) are machine learning algorithms that have been utilized to predict the possibility of Mild cognitive Impairment (MCI) participants getting Alzheimer's, allowing the disease's progression rate to be determined. These strategies, however, were unreliable due to the difficulties of defining the condition as AD or ND, the likelihood of late or seriously demented patients, and a lack of access to large or diverse data sets. A thorough analysis discovered that the proposed workflows might be substantially enhanced by focusing on the constraints of previous studies. The suggested Alzheimer's disease technique categorizes AD patients into one of four stages, using a data set of 1288 MRI images for training and pre-processing procedures such as skull stripping, noise reduction, and motion correction. This method utilizes a convolutional neural network model (CNN) and deep learning architecture in order to enhance accuracy while minimizing the computational resources required to access ROIs (regions of interest). The technology can effectively diagnose patients with minimal work and time while providing much potential.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Gaze Behaviour in Adolescents with Obsessive-Compulsive Disorder During Exposure Within cognitive-Behavioural Therapy 17th

Gaze Behaviour in Adolescents with Obsessive-Compulsive Di...

引用

17th EAI international conference on Pervasive computing Technologies for Healthcare, PervasiveHealth 2023

作者： Thierfelder, Annika Severitt, Björn Klein, Carolin S. Alt, Annika K. Hollmann, Karsten Bulling, Andreas Ilg, Winfried Hertie Institute for Clinical Brain Research Section for Computational Sensomotorics University Hospital Tübingen Tübingen Germany Department of Computer Science Human-Computer Interaction University of Tübingen Tübingen Germany Department of Child and Adolescent Psychiatry Psychosomatics and Psychotherapy University Hospital Tübingen Tübingen Germany Institute for Visualisation and Interactive Systems University Stuttgart Stuttgart Germany

ISBN: (纸本)9783031597169

Digital health interventions that involve monitoring patient behaviour increasingly benefit from improvements in sensor technology. Eye tracking in particular can provide useful information for psychotherapy but an effective method to extract this information is currently missing. We propose a method to analyse natural gaze behaviour during exposure exercises for obsessive-compulsive disorder (OCD). At the core of our method is a neural network to detect fixations based on gaze patch similarities. Detected fixations are clustered into exposure-relevant, therapist, and other locations and corresponding eye movement metrics are correlated with subjective stress reported during exposure. We evaluate our method on gaze and stress data recorded during video-based psychotherapy of four adolescents with OCD. We found that fixation duration onto exposure-relevant locations consistently increases with the perceived stress level as opposed to fixations onto other locations. Fixation behaviour towards the therapist varied largely between patients. Taken together, our results not only demonstrate the effectiveness of our method for analysing natural gaze behaviour during exposure sessions. The fixation analysis shows that patients allocate more attention towards exposure-related objects under higher stress levels, suggesting higher mental load. As such, providing feedback on fixation behaviour holds significant promise to support therapists in monitoring intensity of exposure exercises. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Location

来源：评论

学校读者我要写书评

暂无评论

Interpreting Deep Learning Models for Multi-modal Neuroimaging

Interpreting Deep Learning Models for Multi-modal Neuroimagi...

引用

international Winter Workshop on Brain-Computer Interface (BCI)

作者： K.-R. Müller S.M. Hofmann Machine Learning Group TU Berlin Marchstr. 23 Berlin Germany Dept. of Artificial Intelligence Korea University Seoul Korea Max Planck Institute for Informatics Saarbrücken Germany Max Planck Institute for Human Cognitive and Brain Sciences Stephanstr. 1a Leipzig Germany

Accurately analyzing both structural and functional brain data from multimodal neuroimaging is a challenge for deep learning methods. Recent progress in explainable AI (XAI) has helped to gain insight into structural relationships across brain regions and complex dynamics of cognitive states, both in healthy and diseased. In this brief note, we will touch upon selected recent directions of our research where machine learning techniques help to analyze brain measurements from EEG, fNIRS, sMRI and fMRI. We owe these steps that we are summarizing mainly to activities of members of the BBCI team and their collaborators. Clearly, unavoidably and intentionally this abstract will have a high overlap to prior own contributions as it reports about and discusses these novel ideas and directions.

关键词： Neuroimaging Deep learning Functional magnetic resonance imaging Brain modeling Electroencephalography Brain-computer interfaces Functional near-infrared spectroscopy

来源：评论

学校读者我要写书评

暂无评论

2nd international conference on Business data Analytics, ICBDA 2023

2nd International Conference on Business Data Analytics, ICB...

引用

2nd international conference on Business data Analytics, ICBDA 2023

ISBN: (纸本)9783031807770

The proceedings contain 28 papers. The special focus in this conference is on Business data Analytics. The topics include: A Novel Approach for Diabetic Prediction Using Attribute Subset Selection, K-Means and Logistic Regression;diabetic Retinopathy Detection Approach Using Convolution Neural Networks;voting Regression Model for the Air Quality Prediction;Quantitative Assessment on Investigation on the Impact of Artificial Intelligence on HR Practices and Organizational Efficiency for Industry 4.0;NIR Spectroscopy for Freshness Detection and Classification of Chicken Eggs;Human Action Recognition in Infrared Domain: A Study on IITR-IAR dataset;Software Requirements Prioritization Using Fuzzy Based TOPSIS Methods;predictive Analytics for Inventory Management in Multi-Vendor E-Commerce;data Analytics Augmented by AI in the Realm of 6G Wireless Communication;big data-Powered Analytics for Fortifying Virtualized Infrastructure Security in the Cloud;orthogonal Polynomials and Their Engineering Applications;Explainable AI for Drone data Analytics in Aerial computing;correlational Analysis of Risk-Taking Propensity in Adolescents;Analytical Insight into Cutting-Edge Image Captioning for Advanced ChatGPT Functionality;an Expert System for Talent Prediction and Enhancement of Non-Talented Cricket Performers;Predicting Early Dropouts in SWAYAM MOOCs Using Machine Learning Techniques: A Comparative Analysis;data Analysis of Social Media’s Impact on Promotion of Organic Products in Uttarakhand;enhancing Academic Performance Prediction Through K-Means Clustering and Comparative Evaluation of Machine Learning Algorithms: A Case Study on Student dataset;cognitive data Underwriting with Automation: A Survey;Multi-Level Thresholding Segmentation of Chest X-ray Images of COVID-19 Patients Using Chaos Game Optimizer and Utilizing Kapur's Entropy;concrete Strength Prediction Using Machine Learning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimal Excitatory and Inhibitory Balance for High Learning Performance in Spiking Neural Networks with Long-Tailed Synaptic Weight Distributions

Optimal Excitatory and Inhibitory Balance for High Learning ...

引用

international Joint conference on Neural Networks (IJCNN)

作者： Ibuki Matsumoto Sou Nobukawa Tomoki Kurikawa Nobuhiko Wagatsuma Yusuke Sakemi Takashi Kanamaru Nina Sviridova Kazuyuki Aihara Graduate School of Information and Computer Science Chiba Institute of Technology Chiba Japan Department of Complex and Intelligent Systems Future University Hakodate Hokkaido Japan Department of Information Science Toho University Chiba Japan Research Center for Mathematical Engineering Chiba Institute of Technology Chiba Japan School of Advanced Engineering Kogakuin University Tokyo Japan Department of Intelligent Systems Tokyo City University Tokyo Japan International Research Center for Neurointelligence The University of Tokyo Tokyo Japan

Excitatory/inhibitory (E/I) balance is significantly associated with cognitive function. Its imbalance impairs cognitive function, particularly in patients with psychiatric disorders. Recent physiological and modeling findings show that excitatory postsynaptic potentials (EPSPs) have a long-tailed distribution and contribute to the generation of spontaneous activity. Moreover, this spontaneous activity and its response to the external stimulus significantly alternate under the different E/I balance. However, the effects of the E/I balance under long-tailed EPSPs at the functional level remain unknown. Hence, to elucidate this relationship, we constructed a reservoir computing (RC) model generating the long-tailed distribution of EPSPs and investigated the effect of the E/I balance on the learning performance of RC in the memory capacity (MC) task, which measures how correctly delayed input signals can be reproduced. The results revealed that an appropriate E/I balance maximized the MC. This high MC was realized by recurrent spike propagation under long-tailed EPSPs. These findings contribute to the understanding of the effect of the E/I balance in physiologically relevant neural networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Characterization Of Physiological Signals Under cognitive Stress

Characterization Of Physiological Signals Under Cognitive St...

引用

international conference on Electrical Engineering, computing Science and Automatic Control (CCE)

作者： Jennifer Ruan-Limas Laura I. Garay-Jiménez Elena F. Ruiz-Ledezma UPIITA Instituto Politécnico Nacional CDMX México SEPI-UPIITA Instituto Politécnico Nacional CDMX México SEPI-ESCOM Instituto Politécnico Nacional CDMX México

A fusion of wearable device sensors and an electroencephalography system was implemented to identify changes under controlled situations related to stress in the student’s population, to assess whether the physiological signals can detect variations in the stress level by a descriptive statistical analysis. The signals used are: movement, blood volume pulse, electrodermal activity, heart rate, temperature and electroencephalography. The analysis was made in volunteers between 18 and 25 years old, who are young adults with at least 10 years of schooling and being apparently healthy. The recording protocol consisted of 3 consecutive stages taken in a single session, which consisted of two math tests (stage 1 and stage 3) with a relaxation period (stage 2) in between. The physiological signal data were segmented per stage and descriptive statistical metrics were calculated per volunteer. For the appropriate proper selection of metrics, they were compared using the Repeated Measures one-way ANOVA method with α = 0.05, using Tukey's multiple comparisons tests. It was found that the heart rate and temperature signals, along with the descriptive statistical metrics, range, and kurtosis, are the best suited for the study to find the differences. Volunteers in stage 3 maintained a state of relaxation equal to or less than that of stage 2.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Remora Optimization Algorithm for Efficient Routing in cognitive Wireless Sensor Network

Multi-Objective Remora Optimization Algorithm for Efficient ...

引用

Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE), international conference on

作者： J Rajaram Srinivas Aluvala Zainab Abed Almoussawi Muntather Almusawi Anitha D CSE Malla Reddy Engineering college for women (Autonomous) Hyderabad India School of Computer Science & Artificial Intelligence SR University Warangal India College of Islamic Science Ahl Al Bayt University Karbala Iraq The Islamic University Najaf Iraq Department of Computational Intelligence School of computing SRM Institute of Science and Technology Kattankulathur India

cognitive Wireless Sensor Networks (CWSNs) are exposed to severe energy constraints, requiring investigation into solutions for extended network lifetimes. Radio Frequency Wireless Energy Harvesting (RFWEH) has proven its ability to efficiently mitigate these limits. However, the dynamic nature of many CWSN applications, influenced by node mobility, causes issues as network topologies changes. A unique Multi-Objective Remora Optimization Algorithm (MROA) is developed to handle the combination of energy harvesting and node mobility. MROA is designed for mobility-aware CWSNs and incorporates energy harvesting effortlessly. To choose cluster heads, the protocol applies an R-factor parameter that incorporates residual node energy, residual node data, and node speed with appropriate weighting. As a result, the MROA framework improves the network's energy performance, which leads to an extended using lifetime. When compared to existing methods namely RMAC-M, R-MAC, and WORP the suggested method performed well in the 500 rounds. It achieved in terms, Alive nodes -3400, Throughput - 170.57 kbps and Delay - 45.00 seconds respectively.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Graph Contrastive Learning with Adaptive Augmentation for Knowledge Concept Recommendation

Graph Contrastive Learning with Adaptive Augmentation for Kn...

引用

international conference on Computer Supported Cooperative Work in Design

作者： Mei Yu Zhaoyuan Ding Jian Yu Wenbin Zhang Ming Yang Mankun Zhao College of Intelligence and Computing Tianjin University Tianjin China Tianjin Key Laboratory of Advanced Networking(TANK Lab) Tianjin China Tianjin Key Laboratory of Cognitive Computing and Application Tianjin China Information and Network Center Tianjin University Tianjin China College of Computing and Software Engineering Kennesaw State University Marietta GA USA

Knowledge concept recommendation is a kind of fine-grained recommendation in massive open online courses (MOOCs) scenario, user interaction data has the characteristics of strong collaborative signals and imbalanced interactions. This leads to a single recommendation and reduced accuracy. Recently, the ability of contrastive learning (CL) in mitigating interaction imbalance in recommender systems has received widespread attention. CL requires the use of augmentation methods to generate different views. Existing augmentation methods (1) augment only at the topology or feature level ignoring semantic or structural information, and (2) undifferentiated augmentation tends to lose the critical information. In this paper, we propose Graph Contrastive Learning with Adaptive Augmentation for Knowledge Concept Recommendation (GCARec). Specifically, (1) topology level adaptive augmentation based on degree centrality captures critical structural information, and then (2) feature level adaptive augmentation based on degree centrality captures critical semantic information. Comprehensive experiments show that our proposed approach can outperform other baselines. Our implementations are available at https://***/DingZhaoyuan/GCARec.

关键词：

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72页 << < 59 60 61 62 63 64 65 66 67 68 > >>

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：