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

1,381 篇 会议
93 册 图书
20 篇 期刊文献

馆藏范围

1,494 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,206 篇 工学
- 987 篇 计算机科学与技术...
- 809 篇 软件工程
- 268 篇 信息与通信工程
- 146 篇 生物工程
- 125 篇 生物医学工程（可授...
- 119 篇 控制科学与工程
- 82 篇 电气工程
- 71 篇 光学工程
- 70 篇 机械工程
- 67 篇 电子科学与技术（可...
- 49 篇 安全科学与工程
- 48 篇 化学工程与技术
- 44 篇 仪器科学与技术
- 40 篇 土木工程
536 篇 理学
- 286 篇 数学
- 166 篇 生物学
- 122 篇 物理学
- 108 篇 统计学（可授理学、...
- 65 篇 系统科学
- 44 篇 化学
343 篇 管理学
- 181 篇 管理科学与工程(可...
- 181 篇 图书情报与档案管...
- 117 篇 工商管理
113 篇 医学
- 110 篇 临床医学
- 103 篇 基础医学(可授医学...
- 64 篇 药学(可授医学、理...
- 45 篇 公共卫生与预防医...
71 篇 法学
- 61 篇 社会学
60 篇 教育学
- 60 篇 教育学
52 篇 农学
- 49 篇 作物学
33 篇 经济学
4 篇 军事学
2 篇 文学
1 篇 艺术学

主题

40 篇 artificial intel...
28 篇 computer communi...
23 篇 machine learning
22 篇 information syst...
22 篇 students
20 篇 internet of thin...
18 篇 computer vision
16 篇 support vector m...
16 篇 convolutional ne...
15 篇 computational in...
15 篇 semantics
14 篇 deep learning
13 篇 information stor...
12 篇 feature extracti...
12 篇 accuracy
12 篇 technological in...
11 篇 human computer i...
11 篇 wireless sensor ...
11 篇 visualization
11 篇 decision trees

机构

6 篇 department of co...
5 篇 beijing research...
5 篇 school of comput...
5 篇 department of co...
5 篇 department of co...
5 篇 department of co...
5 篇 institute of com...
5 篇 school of comput...
4 篇 university of sc...
4 篇 key laboratory o...
4 篇 gits udaipur
4 篇 jinan university
4 篇 lovely professio...
4 篇 insight sfi rese...
4 篇 department of co...
4 篇 mlr institute of...
4 篇 purdue universit...
4 篇 school of comput...
4 篇 jaypee universit...
4 篇 department of co...

作者

7 篇 sun fuchun
7 篇 harris frederick...
6 篇 bein doina
6 篇 vani v.
6 篇 karthik n.
5 篇 tyagi vipin
5 篇 constantine step...
5 篇 yang yujian
5 篇 margherita anton...
4 篇 rajalakshmi s.
4 篇 de-shuang huang
4 篇 jose joemon m.
4 篇 sharma ajay kuma...
4 篇 ootsu kanemitsu
4 篇 rathore narendra...
4 篇 patel mayank
4 篇 xiaorui zhang
4 篇 yokota takashi
4 篇 baba takanobu
4 篇 elisa bertino

语言

1,447 篇 英文
35 篇 其他
29 篇 中文

检索条件"任意字段=7th IASTED International Conference on Advances in Computer Science and Technology"

共 1494 条记录，以下是241-250 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：

Dost-Mental Health Assistant Chatbot 5

Dost-Mental Health Assistant Chatbot

引用

5th IEEE international conference on advances in science and technology, ICAST 2022

作者： Nayar, Atulya M. Attar, Zulfa Kachwala, Shabbir Biswas, Tanaya Wagh, Sharmila K. Savitribai Phule Pune University Computer Engineering Pune India

ISBN: (纸本)9781665492638

Mental health is a topic that is still new and must be introduced to everyone with tremendous care and caution and slowly made mainstream, so people don't view it as taboo and get appropriate treatment from professionals. Until then, chatbots will play an integral part in mental health assistance, for citizens who can't afford expensive treatments. the main aim of this paper is to introduce a mental health assistant, Dost, a chatbot built on Rasa framework and deployed on Telegram. the aim is to understand the user's problems and proceed to suggest ways to improve the user's condition through daily, casual conversations. Chatbots will play an integral role in the future of healthcare, to make mental health facilities accessible to everyone, from students to senior citizens and offer 24/7 assistance in the absence of doctors. © 2022 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Distributed Self-fault Outlier Detection in Wireless Sensor Network Based on Machine Learning 6th

Distributed Self-fault Outlier Detection in Wireless Sensor ...

引用

6th international conference on Computational Intelligence in Pattern Recognition, CIPR 2024

作者： Padhi, Ruchika Mudulli, Debendra Gouda, Bhabani Sankar C. V. Raman Global University Odisha Bhubaneswar India School of Computer Science NIST Institute of Science and Technology Odisha Brahmapur India

ISBN: (纸本)9789819780891

Due to a wide range of essential applications, resource limitations, and intermittent irregular responses from cluster sensor nodes, different cluster sensor node faults and failures of distributed wireless sensor networks have occurred in recent years. Due to limited calculation capabilities, limited storage space, resource constraints, and a poor wireless communication environment, relatively few studies have been done on distributed fault diagnosis and fault tolerance in wireless sensor networks, making these networks vulnerable to impending security issues and abnormal detection. this chapter presents a thorough investigation into data quality, with a focus on the features of sensor node information with respect to time and space similarity, as well as recent advances in the study of outlier analysis. In this study, we employ classification to identify outliers by predicting the values of faulty sensor nodes using information gathered from their fault-free neighbors. the proposed method, DSFOD, uses the KNN algorithm to diagnose the proximity of a distance and achieves promising results of greater than 0.99. To accomplish the goal of data outlier detection in WSN, the data are analyzed and detected using the DSFOD method. the simulation’s findings demonstrate the network’s efficiency and superior performance at that specific time. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

Challenges and Issues in Team Gamer Loyalty for Massively Multiplayer Online Game 4th

Challenges and Issues in Team Gamer Loyalty for Massively Mu...

引用

4th international conference on advances in Computational science and Engineering, ICACSE 2023

作者： Xue, G. Lili, N.A. Noris, M.N. Azrul Hazri, J. Faculty of Computer Science and Information Technology Universiti Putra Malaysia UPM Selangor Darul Ehsan Serdang43400 Malaysia

ISBN: (纸本)9789819729760

As the number of players in Massively Multiplayer Online Games (MMOG) increases, the complexity of game missions requires players to work in teams to accomplish game objectives. If players lack expertise in collaboration, they may have difficulty integrating into the game team, which may further erode their loyalty to the MMOG. However, little is known about how game cooperation affects players’ loyalty to MMOG, suggesting that there is a dearth of research in this area. As a result of this mismatch, game developers are unable to allocate resources in ways that increase gamer loyalty. We propose a new framework for the study of team gamer loyalty. the results show that game team norm identification, team participation experience, and cooperative knowledge all contribute to team gamer loyalty. the study suggests that cooperative knowledge among players not only directly increases gamer loyalty, but also amplifies the effects of team participation experience and game team norms on loyalty, which is valuable information for game developers. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

Enhancing ASD Cognitive Assessment with P300 Classification using EMD-based qEEG Wavelet Features

Enhancing ASD Cognitive Assessment with P300 Classification ...

引用

international conference on computer Applications In Electrical Engineering-Recent advances (CERA)

作者： Madhuparna Das Manjunatha Mahadevappa School of Medical Science and Technology Indian Institute of Technology Kharagpur

Individuals with Autism Spectrum Disorder (ASD) often face challenges in effective communication due to deficiencies in their joint attention skills. Brain-computer Interface (BCI) systems based on the P300 Electroencephalogram (EEG) signal has shown promising results in neuro-rehabilitation training for individuals with Autism spectrum disorder(ASD), helping them overcome these communication barriers. However, detecting the P300 signal in ASD is particularly difficult due to its noisy nature, lower amplitude, and higher latency compared to other individuals. In this paper, we propose a novel application of the Empirical mode decomposition (EMD) using the Hilbert Huang transform to identify the P300 signal in a BCI system involving ASD subjects. Further, the optimized mode was selected and utilized and the qEEG fused time-frequency domain wavelet features were extracted for each selected mode of each individual channel. To address the class imbalance issue in the dataset, To handle imbalanced data, we applied SMOTE for data augmentation, and for optimized feature selection, we used PCA. We conducted a comparative classification analysis using five popular machine-learning classifiers. Among the classifiers, Random Forest outperformed the others, achieving 93% accuracy. these results demonstrate the effectiveness of our approach in enhancing P300 signal identification for joint attention-based cognitive task classification for individuals with ASD, surpassing state-of-the-art methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimizing Resource Allocation in Agriculture through IoT and AI

Optimizing Resource Allocation in Agriculture through IoT an...

引用

international conference of Electronics, Communication and Aerospace technology (ICECA)

作者： Mirzanur Rahman T Chippy V Dankan Gowda KDV Prasad Harpal Singh Sethi P Vishnu Prasanth Department of Information Technology Gauhati University Guwahati Assam India Department of Computer Science and Engineering Mahaguru Institute of Technology kattachira kayamkulam India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka Symbiosis Institute of Business Management Hyderabad Symbiosis International (Deemed University) Pune India Department of Computer Science Information Technology Vaugh Institute of Agricultural Engineering And Technology (VIAET) Prayagraj Uttar Pradesh India Sree sainath Nagar Tirupati India

Irrigation, fertilisation, and crop rotation has gained paramount importance in the agricultural industry. Technological advances motivate farmers to achieve optimum crop yields. Maximising crop yield via the deployment of cutting-edge agricultural technology is the recent research trend. Increased yields can be achieved by considering various parameters including soil temperature, soil pH, and water availability. this research work proposes the an IoT-based Precision Agriculture system called “ACRIS: Agriculture Cultivation Recommender and Smart Irrigation System” to provide helpful suggestions to farmers interested in increasing the crop yields by using the Internet of things technology. the suggested method works well in monitoring the agricultural crops. the proposed system is also capable of determining future irrigation planning requirements. Soil conditions like moisture, temperature, and humidity are used as predictors. these experimental results show that the smart irrigation may increase the crop output while decreasing water usage.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Classification Using LBP-TOPs from 3D MRI Images 5th

Brain Tumor Classification Using LBP-TOPs from 3D MRI Images

引用

5th international conference on advances in Information Communication technology and Computing, AICTC 2024

作者： Naqvi, Najme Zehra Seeja, K.R. Department of Computer Science and Engineering Indira Gandhi Delhi Technical University for Women Delhi India

ISBN: (纸本)9789819761050

MRI images are the most noninvasive technique for tumor detection. 3D MRI images are difficult to process because of their size. 3D MRI images have three orthogonal planes (TOPs): axial plane, coronal plane, and sagittal plane. Each plane carries information about the tumor. In this research work, brain tumor is detected and classified as malignant and benign from the features extracted from these orthogonal planes. Local Binary Pattern (LBP) is used for feature extraction. All modalities of MRI images, i.e., T1, T2, T1ce, and Flair, are used for feature extraction. the experiments are performed on the Brats 2018 dataset with SVM and KNN classifiers. In one experiment, features retrieved are given to train the SVM classifier. In the second experiment, the retrieved features are given to train the KNN classifier. By using different combinations of malignant and benign MRI images with SVM and KNN classifiers, it is found that SVM performs better than KNN classifier. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Fusion of Panchromatic and Low-Resolution Multispectral Images Using Combination of PCA and Morphological Hat Transformation 7th

Fusion of Panchromatic and Low-Resolution Multispectral Imag...

引用

7th international conference on Microelectronics, Electromagnetics and Telecommunication, ICMEET 2022

作者： Banerjee, Rupa Bhateja, Vikrant Mishra, Reetika Lin, Jerry Chun-Wei Travieso-Gonzalez, Carlos M. Faizabad Road UP Lucknow226028 India Department of Electronics Engineering Faculty of Engineering and Technology Veer Bahadur Singh Purvanchal University Shahganj Road Uttar Pradesh Jaunpur India Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applies Sciences Bergen Norway Campus Univeritario de Tafira sn. Telecommunicacion. Pabellon B. D-111 Las Palmas de Gran Canaria35017 Spain

ISBN: (纸本)9789811988646

In past few years, satellite imagery has made significant advances in the sectors of climate, farming, and defense. As seen in the Low-Resolution Multi-Spectral (LRMS) and Panchromatic (PAN) images, satellites acquire data in two domains: spectral resolution and spatial resolution. the goal of remote sensing image fusion is to merge the complimentary information from the PAN and LRMS images. the same has been accomplished in this study using Morphological Hat Transformation and Discrete Wavelet Transformation. Decomposition of LRMS and Pan images into approximation (cA) and detail (cD) coefficients is used in the proposed fusion method. To extract the first principal component, PCA is applied to the cA coefficients of both images, and MHT is applied to both cD coefficients at the same time. the end outcome is a fusion of the results after applying Inverse Wavelet Transformation (IDWT). the performance evaluation of the final-fused image is presented in the later sections. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image fusion

来源：评论

学校读者我要写书评

暂无评论

MUCS@LT-EDI2023: Learning Approaches for Hope Speech Detection in Social Media Text 3

MUCS@LT-EDI2023: Learning Approaches for Hope Speech Detecti...

引用

3rd Workshop on Language technology for Equality, Diversity and Inclusion, LTEDI 2023

作者： Hegde, Asha Kavya, G. Coelho, Sharal Shashirekha, Hosahalli Lakshmaiah Department of Computer Science Mangalore University Mangalore India

ISBN: (纸本)9789544520847

Hope exerts a substantial influence on human cognition and behavior, yet hope related content remains under explored in the realm of social media data analysis. Investigating this content unveils valuable insights into users’ emotions, aspirations, and anticipations, offering researchers and analysts a richer comprehension of hope’s impact on digital-era individuals’ well-being, choices, and actions. Further, this area is rarely explored even for high-resource languages. To address the identification of hope text in social media platforms, this paper describes the models submitted by the team MUCS to "Hope Speech Detection for Equality, Diversity, and Inclusion (LT-EDI)" shared task organized at Recent advances in Natural Language Processing (RANLP) - 2023. this shared task aims to classify a comment/post in English and code-mixed texts in three languages (Bulgarian, Spanish, and Hindi) into one of the two predefined categories: "Hope" or "Non Hope". Two models: i) Hope BERT - Linear Support Vector Classifier (LinearSVC) model trained by concatenating Bidirectional Encoder Representations from Transformers (BERT) embeddings and Term Frequency-Inverse Document Frequency (TF-IDF) of character n-grams with word boundary (char wb) for English and ii) Hope mBERT - LinearSVC model trained by concatenating Multilingual BERT (mBERT) embeddings and TF-IDF of char wb for Bulgarian, Spanish, and Hindi code-mixed texts, are proposed for the shared task to classify the given text into Hope or Non-Hope categories. the proposed models obtained 1st, 1st, 2nd, and 5th ranks by exhibiting macro F1 scores of 0.61, 0.75, 0.67, and 0.44 for Spanish, Bulgarian, Hindi, and English texts respectively. © 2023 LTEDI 2023 - 3rd Workshop on Language technology for Equality, Diversity and Inclusion, associated with the 14th international conference on Recent advances in Natural Language Processing, RANLP 2023 - Proceedings. All rights reserved.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

SARCOVID: A Framework for Sarcasm Detection in Tweets Using Hybrid Transfer Learning Techniques 27th

SARCOVID: A Framework for Sarcasm Detection in Tweets Using ...

引用

27th international conference on Pattern Recognition, ICPR 2024

作者： Balaji, T.K. Bablani, Annushree Sreeja, S.R. Misra, Hemant Indian Institute of Information Technology Sri City Andhra Pradesh Sri City517646 India Simpl Bengaluru India

ISBN: (纸本)9783031781940

the COVID-19 pandemic sparked a surge in online discussions, making sentiment analysis challenging due to the prevalence of sarcasm on social media. Identifying sarcastic expressions within the context of COVID-19 conversations poses a unique linguistic hurdle. To tackle this challenge, a novel framework called SARCOVID is proposed that leverages hierarchical transfer learning and ensemble techniques to detect sarcasm in the field. through rigorous evaluation on a collected COVID-19 dataset, SARCOVID demonstrates superior performance in identifying sarcastic content with reduced bias compared to traditional methods. the findings reveal a significant presence of sarcasm in online COVID-19 discussions, underscoring the importance of robust sarcasm detection techniques. In a test, the framework outperforms other models with 0.61 accuracy on Sarcasm corpus V2. this approach not only advances sentiment analysis capabilities for evolving online conversations but also provides deeper insights into the nuanced expressions of sentiment on social media. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Meta-Learned Word Embeddings for Few-Shot Sentiment Classification 7th

Meta-Learned Word Embeddings for Few-Shot Sentiment Classifi...

引用

7th international conference on Smart Trends in Computing and Communications, SmartCom 2023

作者： Pandey, Sumit Sharma, Srishti Department of Computer Science School of Engineering and Technology The Northcap University Haryana Gurugram122017 India

ISBN: (纸本)9789819907687

For each new domain, researchers and technologists developing sentiment classification algorithms must gather and curate data. In particular for domains where the features change over time, the work required to annotate these corpora is prohibitive. the idea of training classifiers on a limited set of domains before using them on further domains is explored in this study. One issue is that classifiers frequently perform poorly when the distributions of the training and testing sets of data are different. Another issue is that it is unclear how to choose domains that are suitable for training and testing other domains based on similarities. To train classifiers that generalize and still perform well on test sets that come from various distributions, the authors approach this challenge by making use of numerous, smaller training datasets. the authors suggest using current developments in meta-learning to learn stronger cross-domain embeddings that can generalize for the few-shot learning context to achieve this. this work investigates sentiment classification using few-shot learning. there are a variety of existing approaches to this problem, but recent advances in meta-learning have proven to be quite effective in the few-shot context. For few-shot learning, the authors suggest using MAML (Model Agnostic Meta-Learning) to quickly train better cross-domain embeddings and networks. Our final model performs at a cutting-edge level. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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150页 << < 21 22 23 24 25 26 27 28 29 30 > >>

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：