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

941 篇 会议
262 篇 期刊文献
14 册 图书

馆藏范围

1,217 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

639 篇 工学
- 494 篇 计算机科学与技术...
- 429 篇 软件工程
- 155 篇 信息与通信工程
- 107 篇 控制科学与工程
- 101 篇 生物工程
- 87 篇 生物医学工程（可授...
- 67 篇 光学工程
- 64 篇 电气工程
- 47 篇 电子科学与技术（可...
- 42 篇 动力工程及工程热...
- 40 篇 安全科学与工程
- 38 篇 交通运输工程
- 37 篇 网络空间安全
- 36 篇 机械工程
- 35 篇 化学工程与技术
358 篇 理学
- 161 篇 数学
- 110 篇 生物学
- 86 篇 物理学
- 73 篇 统计学（可授理学、...
- 31 篇 地球物理学
- 30 篇 化学
231 篇 管理学
- 141 篇 管理科学与工程(可...
- 104 篇 图书情报与档案管...
- 91 篇 工商管理
93 篇 医学
- 72 篇 临床医学
- 68 篇 基础医学(可授医学...
- 49 篇 公共卫生与预防医...
- 40 篇 药学(可授医学、理...
40 篇 经济学
- 40 篇 应用经济学
39 篇 法学
- 34 篇 社会学
22 篇 农学
10 篇 教育学
5 篇 文学
4 篇 军事学
1 篇 哲学

主题

118 篇 accuracy
61 篇 real-time system...
56 篇 computational mo...
50 篇 deep learning
49 篇 predictive model...
48 篇 machine learning
44 篇 training
41 篇 feature extracti...
38 篇 machine learning...
38 篇 convolutional ne...
33 篇 artificial intel...
32 篇 technological in...
31 篇 data models
25 篇 analytical model...
25 篇 adaptation model...
24 篇 prediction algor...
21 篇 reliability
20 篇 internet of thin...
20 篇 security
19 篇 adversarial mach...

机构

36 篇 lovely professio...
17 篇 institute of aer...
17 篇 institute of aer...
15 篇 lloyd institute ...
11 篇 computer science...
10 篇 dept. of compute...
10 篇 smart data & kno...
9 篇 st. martin's eng...
8 篇 knowledge park i...
7 篇 dept. of compute...
6 篇 college of healt...
6 篇 national univers...
6 篇 kalinga universi...
6 篇 data science and...
6 篇 dept. of informa...
6 篇 dept. of knowled...
6 篇 lloyd institute ...
5 篇 university of th...
5 篇 artificial intel...
5 篇 graphic era hill...

作者

12 篇 dengel andreas
12 篇 schröder markus
12 篇 jilek christian
11 篇 ashwini kodipall...
10 篇 kodipalli ashwin...
9 篇 nasraoui olfa
8 篇 watabe hirokazu
8 篇 tsuchiya seiji
8 篇 yuyun
7 篇 yoshimura eriko
7 篇 rao trupthi
6 篇 shoeibi afshin
6 篇 venu nookala
6 篇 praveen
6 篇 deepak upadhyay
6 篇 nookala venu
6 篇 alizadehsani roo...
6 篇 trupthi rao
5 篇 pradnya saval
5 篇 upadhyay abhay

语言

1,142 篇 英文
68 篇 其他
6 篇 朝鲜文
4 篇 日文

检索条件"机构=Dept. of Data Science and Knowledge Engineering"

共 1217 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：

A method for generating association words from several other words in an Association System

A method for generating association words from several other...

引用

2012 International Conference on Artificial Intelligence, ICAI 2012

作者： Imono, Misako Yoshimura, Eriko Tsuchiya, Seiji Watabe, Hirokazu Dept. of Knowledge Engineering and Computer Sciences Graduate School of Engineering Doshisha University Kyo-Tanabe Kyoto Japan Dept. of Intelligent Information Engineering and Sciences Faculty of Science and Engineering Doshisha University Kyo-Tanabe Kyoto Japan

ISBN: (纸本)1601322178

Humans communicate with others using natural language. Because many expressions in natural language can convey the same message, humans interpret these expressions flexibly based on their knowledge of words and association skills. An Association System was constructed on a computer by applying Concept Bases and the degree ofassociation. This paper proposes a method for generating an association word from several other words with the Association System to show that it can achieve humanlike associative abilities on a computer. The proposed method generated a natural human association with 61.0% accuracy and 77.0% recall.

关键词： Association mechanism Concept base Degree of association

来源：评论

学校读者我要写书评

暂无评论

Development of an AI based Priority Formation Mechanism in Criminal Law 3

Development of an AI based Priority Formation Mechanism in C...

引用

3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Sharma, Kashish Amburle, Ankita Shelake, Vijay Chauhan, Ashvini Ashok Dept. of Computer Engineering Fr. Conceicao Rodrigues College of Engineering Mumbai India Dept. of Artificial Intelligence and Data Science Fr. Conceicao Rodrigues College of Engineering Mumbai India

ISBN: (纸本)9798331532420

Nowadays, there is a necessity to tackle a number of pending crime cases across different parts of the world through effective scheduling and management. AI and ML can be used in handling unfinalized criminal cases in India can be one of the possible ways of improving the functioning of the criminal justice system in this country. The approach to this project is to create an AI system that will filter through the open cases and then rank them according to complexity, time-sensitivity, prior performances, and location. Since priority in a case is explained through the use of a supervised learning based on selected set, then law enforcement as well as legal personnel are able to shift most of their attention to other significant cases. Despite feature engineering and data preprocessing being in the construction of the system from the data collected from the various sources such as court records. This means that there is than models such as;Random Forest, Apriori and Rule-Based in an effort to establish the most suitable model. Perhaps the application of this AI based mechanism to form priorities could aid India in better organization of resources and with the assistance of backlog decrease – the justice system in India. But as the right touch to measure artificial use is considered, themes of privacy, bias, and fairness must also be addressed appropriately. © 2024 IEEE.

关键词： Crime

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning-Enhanced IoT Wearable Device for Monitoring and Providing Feedback on Stuttering 3

A Machine Learning-Enhanced IoT Wearable Device for Monitori...

引用

3rd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2024

作者： Suttarwala, Hussain Kumar, Ritesh Deorankar, Madhavi L. Daulat Sarpate, Dikshendra Shingade, Pallavi Kumar Sharma, Surender More, Vrushali Patkar, Uday Chandrakant Sharma, Deepak K. American Express Senior Software Engineer PhoenixAZ85054 United States Dr. Akhilesh Das Gupta Institute of Professional Studies Dept. of AI and Data Science Delhi New Delhi110053 India Marathwada Mitramandal College of Engineering Dept. of Electronics and Telecommunications Maharashtra Pune411052 India Zeal College of Engineering and Research Dept. of AI and Data Science MaharashtraNarhe Pune411041 India D Y Patil College of Engineering Dept. of AI and Data Science Akurdi Pune411041 India Poornima University Dept. of Electrical Engineering Jaipur India Genba Sopanrao Moze College of Engineering Dept. of AI and Data Science Balewadi Maharashtra Pune411045 India Bharati Vidyapeeth's College of Engineering Department of Computer Engineering Lavale Pune412115 India Savitribai Phule Pune University Dept. of AI and Data Science Maharashtra Pune India

ISBN: (纸本)9798350361391

This study introduces an innovative IoT-enabled wearable device tailored for monitoring and providing feedback on stuttering, leveraging advanced machine learning algorithms to enhance precision and real-time responsiveness. The device integrates an array of hardware and software elements, including sensors, microcontrollers, and communication protocols, to accurately capture speech patterns and movements. Utilizing machine learning techniques such as Support Vector Machines (SVM) and Convolutional Neural Networks (CNN), the device performs real-time analysis to identify stuttering instances. Detailed discussions cover the criteria for selecting machine learning models, the training and testing procedures, and the metrics used for performance evaluation. The prototype underwent extensive testing and validation, showcasing high accuracy, sensitivity, and specificity in differentiating stuttered from fluent speech. User feedback emphasized the ergonomic design, user-friendly interface, and real-time feedback features, highlighting its potential to significantly enhance stuttering therapy outcomes. Comparative analysis with existing solutions revealed the device's superior performance, indicating strong potential for clinical application. The study discusses the implications for stuttering therapy, acknowledges the limitations, outlines future research directions, and underscores the device's contributions to personalized and effective stuttering interventions. This research advances the field of assistive technologies in speech therapy and demonstrates the promise of IoT-based wearable devices integrated with machine learning for improving the quality of life for individuals with stuttering disorders. © 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

DeepCensored: Deep-Learning Based Probabilistic Forecasting Framework for Censored data 23

DeepCensored: Deep-Learning Based Probabilistic Forecasting ...

引用

23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Tian, Jiahao Porter, Michael D. School of Data Science University of Virginia CharlottesvilleVA United States School of Data Science University of Virginia Dept. of Systems and Information Engineering CharlottesvilleVA United States

ISBN: (纸本)9798350374889

Accurate time series forecasting is critical in various fields, including resource allocation and crime prevention. While traditional approaches often focus on continuous data, count data forecasting, especially with partially observed (censored) data, remains challenging. This paper introduces DeepCensored, a novel deep learning-based framework that combines the Expectation-Maximization (EM) algorithm with deep neural networks to deliver robust probabilistic forecasts. DeepCensored naturally handles interval-censored event data, where exact event times are unknown but fall within a specific interval. Through extensive simulations and real-world crime data analysis, our method significantly outperforms traditional forecasting approaches, reducing the Mean Absolute Error (MAE) by 50% and better detection of emerging crime trends. These results highlight DeepCensored's potential to provide actionable insights for law enforcement and public safety by predicting crime intensity and enabling resource-efficient policing strategies. © 2024 IEEE.

关键词： Expectation maximization algorithm

来源：评论

学校读者我要写书评

暂无评论

A Face Pre-Processing Approach to Evade Deepfake Detector 1

A Face Pre-Processing Approach to Evade Deepfake Detector

引用

1st ACM Workshop on Security Implications of Deepfakes and Cheapfakes, WDC 2022, co-located with ACM AsiaCCS 2022

作者： Kim, Taejune Kim, Jeongho Kim, Jeonghyeon Woo, Simon S. Computer Science & Engineering Dept. Sungkyunkwan University Suwon Korea Republic of Dept. of Artificial Intelligence Sungkyunkwan University Suwon Korea Republic of Applied Data Science Dept. Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9781450391788

Recently, various image synthesis technologies have increased the prevalence of impersonation attacks. With the development of such technologies, damages to people such as defamation or fake news have also increased. Deepfakes have already evolved to the point, where people cannot easily distinguish fake from real. This leads to an urgent need for developing detection methods. Currently, in order to detect deepfakes, many deepfake datasets are widely used in deep neural networks. And several methods have been proposed and demonstrated to be effective in detecting deepfakes. In this work, we present pre-processing techniques such as face restoration, edge smoothing, face beautification to mitigate the artifacts of deepfakes and makes them appear more natural to humans, while lowering the deepfake detection performance. Through extensive experiments, our method can significantly lower the performance of the state-of-The-Art deepfake detectors and expose the vulnerability of deployed detectors. © 2022 ACM.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing Dental Diagnosis through Automated Detection of Teeth Diseases in Panoramic Radiographs

Enhancing Dental Diagnosis through Automated Detection of Te...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Rawashdeh, Majdi Bdair, Tariq Salhi, DhaiEddine Al-Yamamah University Software Engineering Dept. Riyadh Saudi Arabia Psut Business Information Technology Dept. Amman Jordan Psut Data Science Dept. Amman Jordan

ISBN: (纸本)9798350351255

Edge learning has shown promising solutions to address diseases by exploiting edge computing capabilities. On the other hand, the analysis of dental radiographs is a crucial step in clinical routine practice since the dentist must evaluate tooth-related issues throughout the clinical diagnosis. Further, errors in manual human analysis may lead to false predictions. Fortunately, the automated approach for identifying and categorizing dental issues can help in the early diagnosis of diseases and prevent tooth loss. This paper aims to create a model that may offer a second viewpoint and simplify dental diagnosis for dentists. The proposed method utilizes state-of-the-art deep learning architecture for object detection. It provides panoramic teeth radiograph images to the proposed network to detect four teeth diseases: conservative (fillings and crowns), implant, RCT (root canal treatment), and bridges. After data preprocessing and augmentation, our framework is used to detect the above teeth diseases with high detection quality and accuracy with mAP and F1-score at 0.902 and 0.86, respectively. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Phishing URLs Using Machine Learning Hybrid Stacking Classifier Approach with XGBoost, Random Forest and Extra Trees

Phishing URLs Using Machine Learning Hybrid Stacking Classif...

引用

2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Chitteti, Chengamma Divya Sree, Tanguturi Sai Madhavi, K. Reddy Pooja, Pikkili Jayanth, Sannapaneni Reddy, Middi Harshavardhan Dept. of Data Science Tirupathi India Sree Vidyanikethan Engineering College Dept. of Information Technology Tirupathi India Mohan Babu University Dept. of Ai & Ml Tirupati India

ISBN: (纸本)9798350382693

Within the dynamic field of cybersecurity threats, phishing remains a prevalent and sophisticated tactic employed by malicious actors to deceive consumers. This paper presents a novel approach that leverages the strengths of Random Forest, ExtraTrees, and XGBoost in a machine learning framework to enhance the detection of phishing URLs through a hybrid stacking classifier. The suggested method combines the best features of all three ensemble learning techniques to provide a phishing detection model that is reliable and precise. An ensemble of classifiers is formed by combining XGBoost, which is well-known for its boosting abilities, with the highly randomized ExtraTrees method and the adaptable Random Forest algorithm. By using the various decision limits of each base learner, the hybrid stacking model combines their particular capabilities in the best possible way to provide higher prediction performance. Preprocessing is done on the training dataset to extract pertinent characteristics such as content, URL structure, and contextual data. The efficacy of the suggested method in detecting phishing URLs is assessed by extensive testing on an extensive dataset. The results indicate how well the hybrid stacking classifier performs in comparison to separate classifiers and highlight the possibility for improved phishing detection in practical situations. The study has importance as it presents a novel and efficient machine learning-based approach to counteract the rising danger of phishing assaults, hence propelling the area of cybersecurity forward. © 2024 IEEE.

关键词： Phishing

来源：评论

学校读者我要写书评

暂无评论

Time threshold for classification between 2D-touch and 3D-touch based on user's 3D-touch input 8

Time threshold for classification between 2D-touch and 3D-to...

引用

2018 8th International Workshop on Computer science and engineering, WCSE 2018

作者： Park, JinHyuck Nam, ChoonSung Lee, JangYeol Seo, Young Hoon Shin, DongRyeol Dept. Electric and Electrical Computer Engineering SungKyunKwan University Suwon Korea Republic of Dept. Applied Data Science SungKyunKwan University Suwon Korea Republic of

ISBN: (纸本)9789811178610

As 3D-Touch technology has recently developed, 3D-Touch technology, which was applied only to the touch display of mobile devices, has been introduced to various devices. Although many researches have proposed applying the 3D-Touch technology to various devices, these researches have been confined only to apply 3D-Touch technology without considering 2D-Touch technology. Therefore, there is no clear criterion for distinguishing between 2D-Touch and 3D-Touch. In this paper, we suggest a time threshold for distinguishing between 2D-Touch and 3D-Touch on a display that supports 3D-Touch. © Proceedings of 2018 the 8th International Workshop on Computer science and engineering, WCSE 2018. All rights reserved.

关键词： Three dimensional displays

来源：评论

学校读者我要写书评

暂无评论

Forecasting Air Pollution of Urban Chennai Localities using Artificial Intelligence 3

Forecasting Air Pollution of Urban Chennai Localities using ...

引用

3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Faiz, Rayaan Agarwal, Tisha Rajeswari, D. Srm Institute of Science and Technology School of Computing College of Engineering and Technology Dept. of Data Science and Business Systems Chennai603203 India

ISBN: (纸本)9798350375190

India's air quality deteriorated significantly in 2023, ranking third worst globally, highlighting the urgency for effective monitoring and mitigation measures. To comprehend past trends and predict future patterns, historical air pollution data from seven urban areas in Chennai was analyzed using the XGBoost Algorithm. This study aims to gain insights into Chennai's air quality, identify abnormalities, and issue timely warnings to the public and governing authorities. XGBoost was employed to forecast AQI, NO2, PM2.5, NOx, PM10, CO, SO2, NH3, and Ozone levels, outperforming traditional LSTM, Prophet, and ARIMA models. Evaluation using RMSE and MAE scores revealed XGBoost's efficacy, with scores of 20.65 and 14.35, respectively. The research highlights regions like Alandur, Arumbakkam, and Manali with notable concentrations of contaminants, emphasizing the need for immediate action. These findings highlight the significance of utilizing advanced algorithms for accurate air quality forecasting and proactive pollution management. © 2024 IEEE.

关键词： Air quality

来源：评论

学校读者我要写书评

暂无评论

Perceptions Unveiled: Analyzing Public Sentiment on IoT and AI Integration in Revolutionizing Social Interactions 7

Perceptions Unveiled: Analyzing Public Sentiment on IoT and ...

引用

7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Saraswat, Shweta Sharma, Shashi Kulshrestha, Ruchi Verma, Nootan Lamba, Monica Arya College of Engineering Dept. of Artificial Intelligence with Data Science Jaipur India Jecrc University Dept. of Cse Jaipur India Mody University Dept. of Cse Jaipur India Arya College of Engineering Jaipur Dept. of Cse India

ISBN: (纸本)9798350341485

The IoT and AI are transforming social connections and communication. The article investigates how this symbiotic relationship impacts Twitter sentiment. Using the Twitter Sentiment dataset,"this study analyzes how IoT and AI are changing linked experiences. Analyzing Twitter sentiment on this historic merger shows positive and negative sentiments. Social media allows people to express their thoughts and feelings. This evolving digital environment reflects society and reveals technology adoption sentiment. The merging of IoT with AI is a key technological achievement. Tweets provide a real-time snapshot of worldwide dialogues and reactions to understand public opinion on integration. This study examines the complicated sentiment landscape using the "Twitter Sentiment dataset,"which captures IoT and AI sentiments. Social media sentiment analysis has been used to study public reactions to technological advances. Several studies show that sentiment analysis can predict technological adoption, examine attitudes and concerns, uncover issues, influence legislation, and address ethical issues. Research also emphasizes sentiment polarization's enthusiasm-realism balance and how sentiment predicts technical impact. The research used the "Twitter Sentiment dataset,"with over 1.6 million tweets. Lowercase, punctuation, and stopwords were removed from the dataset. After that, NLP algorithms like sentiment analysis examined the text. The training and test sets were split, and TF- IDF vectorization retrieved features. This research tested sentiment analysis machine learning models (Bernoulli Naive Bayes, Linear Support Vector Classification, and Logistic Regression). Later, the best model was stored. The main measure of sentiment analysis model accuracy was accuracy. Logistic regression outperformed with 83% accuracy. The models accurately captured IoT and AI integration tweets, including joy and concerns. Sentiment analysis can disclose society's feelings, making IoT-AI integrat

关键词： Sentiment analysis

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122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：