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

525 篇 会议
29 册 图书
4 篇 期刊文献

馆藏范围

558 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

383 篇 工学
- 353 篇 计算机科学与技术...
- 228 篇 软件工程
- 60 篇 信息与通信工程
- 46 篇 控制科学与工程
- 39 篇 电气工程
- 38 篇 生物工程
- 24 篇 生物医学工程（可授...
- 24 篇 安全科学与工程
- 20 篇 机械工程
- 19 篇 交通运输工程
- 17 篇 动力工程及工程热...
- 15 篇 化学工程与技术
- 14 篇 电子科学与技术（可...
- 12 篇 光学工程
137 篇 理学
- 71 篇 数学
- 43 篇 生物学
- 37 篇 统计学（可授理学、...
- 22 篇 系统科学
- 19 篇 化学
- 18 篇 物理学
108 篇 管理学
- 74 篇 管理科学与工程(可...
- 48 篇 工商管理
- 47 篇 图书情报与档案管...
27 篇 医学
- 26 篇 基础医学(可授医学...
- 26 篇 临床医学
- 17 篇 药学(可授医学、理...
24 篇 法学
- 22 篇 社会学
15 篇 教育学
- 15 篇 教育学
12 篇 经济学
- 12 篇 应用经济学
12 篇 农学
- 12 篇 作物学
1 篇 军事学

主题

36 篇 big data
27 篇 machine learning
20 篇 data mining
20 篇 artificial intel...
19 篇 internet of thin...
18 篇 cloud computing
10 篇 support vector m...
10 篇 deep learning
10 篇 computational in...
10 篇 predictive model...
10 篇 decision making
9 篇 computational mo...
9 篇 real-time system...
9 篇 data models
7 篇 blockchain
7 篇 industries
7 篇 machine learning...
7 篇 data analysis
6 篇 reinforcement le...
6 篇 data privacy

机构

6 篇 university of vi...
6 篇 university of mi...
5 篇 department of ma...
4 篇 electronics and ...
3 篇 tohoku univ ctr ...
3 篇 university of sa...
3 篇 center for data-...
3 篇 department of co...
3 篇 tongji universit...
2 篇 university of ai...
2 篇 school of comput...
2 篇 western universi...
2 篇 chongqing univer...
2 篇 new delhi
2 篇 uttaranchal scho...
2 篇 hindustan instit...
2 篇 university tun h...
2 篇 school of econom...
2 篇 department of el...
2 篇 cairo

作者

4 篇 swagatam das
4 篇 snehanshu saha
4 篇 carlos a. coello...
3 篇 yuda emi
3 篇 emi yuda
3 篇 altintas ilkay
3 篇 florentino fdez-...
3 篇 jagdish c. bansa...
2 篇 yuehui chen
2 篇 haijun zhang
2 篇 deepak gerard
2 篇 tianyong hao
2 篇 rozaida ghazali
2 篇 pan yongqiang
2 篇 neil yen
2 篇 nakamura shigena...
2 篇 m. rajmohan
2 篇 sridhar
2 篇 rajeswari d.
2 篇 miguel p. rocha

语言

445 篇 英文
109 篇 其他
6 篇 中文

检索条件"任意字段=International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2022"

共 558 条记录，以下是81-90 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 advances in Information Communication Technology and computing, AICTC 2024

5th International Conference on Advances in Information Comm...

引用

5th international conference on advances in Information Communication Technology and computing, AICTC 2024

ISBN: (纸本)9789819761050

The proceedings contain 86 papers. The special focus in this conference is on advances in Information Communication Technology and computing. The topics include: Universal Representation Theory—Rigour II;revolutionizing Smart Cities: A data-driven Traffic Monitoring System for Real-Time Traffic Density Estimation and Visualization;Assessing the Influence of Self-service Technology on WOM: The Role of Customer Satisfaction;Universal Representation Theory—Applications II;enhancing Performance of Machine Learning Models in Healthcare: An Analytical Framework for Assessing and Improving data Quality;evaluating the Enhancement of Cognitive Skills and Acquisition of New Skills in an Environment of Different Video Game Genres;hySeg-Net: A Robust Interactive Hybrid Technique for Image Segmentation and Classification in Hand Gesture Recognition;web Vulnerability Scanner;digitalization of Educational Resources in Pre-tertiary Education in Ghana: Assessing Impact, Challenges, and Opportunities in Enhancing Learning Outcomes;interconnected Through Robotic System in English Foreign Language Education;transferability Cybersocialization as a Digital Civility Through Artificial Intelligence-Based Design Thinking Mindset to Modern Pedagogy;fog computing in Healthcare: Enhancing Recommendations and Real-Time Monitoring;enhancing Bank Consumer Retention: A Comprehensive Analysis of Churn Prediction Using Machine-Learning and Deep Learning Techniques;a Contemporary Model of Kazakh National Pedagogy in the Era of Technology: Theory-Based Design Framework;the Future of Post-harvest Logistics: The Cold Chain Practices with Blockchain, IoT, and FinTech;diagnosing Sexually Transmitted Disease in Females: Leveraging Dimensionality Reduction and Machine Learning;a Systematic Review of Optimal Task Scheduling Methods Using Machine Learning in Cloud computing Environments;intelligent Urban Futures: Exploring AI and Machine Learning Applications in Smart Cities.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detection of Bicep Form Using Myoware and Machine Learning

Detection of Bicep Form Using Myoware and Machine Learning

引用

international conference on advances in data-driven computing and intelligent systems, adcis 2022

作者： Khan, Mohammed Abdul Hafeez Rudraraju, Rohan V. Swarnalatha, R. Department of Computer Science Engineering Birla Institute of Technology and Science Pilani Dubai Campus Dubai International Academic City Dubai United Arab Emirates Department of Electronics and Communication Engineering Birla Institute of Technology and Science Pilani Dubai Campus Dubai International Academic City Dubai United Arab Emirates Department of Electrical and Electronics Engineering Birla Institute of Technology and Science Pilani Dubai Campus Dubai International Academic City Dubai United Arab Emirates

ISBN: (纸本)9789819932498

Many people have been exercising at home since the beginning of the COVID-19 period. Due to this, they haven’t had the supervision of a professional trainer who could correct them, rectify their mistakes, and prevent from harmful injuries. One very common workout that people frequently do is the bicep curl exercise, yet they fail to maintain the right posture without realizing it and end up straining their back muscles and pulling their shoulders too far forward. This is very dangerous as it could result in long-term back pain and tendonitis. Considering this issue, a methodology has been proposed for the people at home to continue their regular exercises without any professional gym trainer and gym environment. This research is oriented toward the correction of bicep form during the bicep curl exercises and preventing injuries. The acquisition fragment is designed with Myoware, an open-source electromyography sensor along with a three-axis accelerometer for capturing the essential segments required for the analysis. Naïve Bayes, logistic regression, K-nearest neighbor, decision tree, and random forest classification models have been used to perform the classification of the data acquired. The analysis of the novel dataset attained has been effective for determining the model with the best results to detect the bicep form. The random forest classifier has yielded the highest individual accuracy of 90.90%. Ultimately, an app prototype has been developed using the MIT app inventor platform. It has been integrated with a Bluetooth module and google firebase for showcasing and collecting data in real time from the sensory modules to the person working out and simultaneously storing them in the database for the deployment of this test set in the machine learning model. With this, the results of the accuracy and performance of a person are then acquired on the app for expressing the nature of their workout session. © 2023, The Author(s), under exclusive license to Springe

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Predicting Models of Per Day Inbound/Outbound Baggage at Terminal 2 of Taoyuan international Airport During 2019-2023 13

Predicting Models of Per Day Inbound/Outbound Baggage at Ter...

引用

Joint 13th international conference on Soft computing and intelligent systems and 25th international Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Li, Sui-Ling National Penghu University of Science and Technology Dept. of Shipping and Transportation Management Penghu Taiwan

ISBN: (纸本)9798350373332

This study aims to develop a data-driven predictive model for daily inbound and outbound baggage volumes at Terminal 2 of Taoyuan international Airport. The research spans 2019 to 2023, encompassing data from the COVID-19 pandemic period. The study considers multiple influencing factors by establishing regression models, including daily passenger numbers, COVID-19 impact, seasonal variations, and policy factors. The models demonstrate high accuracy with R2 values exceeding 0.98. Key findings reveal that the average daily outbound baggage (5,388 pieces) significantly exceeds inbound (3,239 pieces), with outbound passenger numbers having a more significant influence on baggage volume (coefficient 1.045) compared to inbound (coefficient 0.918). Sensitivity analysis shows that changes in passenger numbers have the most significant impact on baggage volume, followed by COVID-19, the 2022 effect, and the January effect. Notably, COVID-19 impacted outbound baggage (-4,680 pieces) more than inbound (-2,517 pieces). The study also established high and low thresholds for baggage handling, with 90% and 68% thresholds for outbound baggage at 36,844 and 25,573 pieces, respectively, and 31,123 and 20,812 pieces for inbound. The model developed in this study accurately predicts daily baggage volumes and serves for long-term planning, such as forecasting inbound baggage for January 2024. These findings give airport managers valuable decision-support tools to optimize resource allocation, improve service quality, and prepare for potential disruptions, enhancing operational efficiency and passenger satisfaction. © 2024 IEEE.

关键词： Sensitivity analysis

来源：评论

学校读者我要写书评

暂无评论

Analysis of Online Health-Related Private data using Named Entity Recognition by Deep Correlation Techniques 1

引用

international conference on advances in data-driven computing and intelligent systems, adcis 2022

作者： Geetha, R. Pasupuleti, Rekha Karthika, S. Tamil Nadu E-Governance Agency Tamil Nadu Chennai India Trent University PeterboroughONK9L0G2 Canada Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Tamil Nadu Chennai India

ISBN: (数字)9789819909810

ISBN: (纸本)9789819909803

Online social network analysis has become a valuable source for health research, as it recognizes convictions and behaviors hidden in traditional surveys. Twitter is a highly dynamic social media platform that enables people to interact and is growing as a valuable source of personal health data. The presence of voluminous health data on the Internet will lead to privacy leaks on user-specific private or sensitive information. Therefore, it is necessary to understand and predict the health data disclosed by social media users. The study focused on private content classification on real-time tweets extracted based on 22 health domain keywords. The tweets were categorized by the proposed Private Content Detection (PCD) algorithm constructed based on personal experience and established regulations/standards to identify the presence of sensitive private health data. The disclosed sensitive private health data are generally in the form of real-time entities like disease information, health and physical attributes like height and weight of a person, and so on. Therefore, the sensitive health entities in social media were identified by the novel Principal Sensitive Health Entity Extraction process which applies spearman's correlation coefficient as the feature extraction phase. This research work built Deep Privacy Models with deep neural networks namely CNN, RNN, C-LSTM, CRF, Bi-LSTM, and Bi-LSTM-CRF with correlation features to classify the private and non-private health data. Highly correlated private health entities identified by Spearman Correlation Coefficient factor in tweets were found to be PRODUCT, GPE, PERSON, and TIME. The Bi-LSTM-CRF model outperformed the other two models with an accuracy of 95% on account of the effective utilization of deep feature-based learning. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Bio Algorithms for Resource Optimisation and Analysis of data 1

Bio Algorithms for Resource Optimisation and Analysis of Dat...

引用

1st IEEE international conference on advances in Electronics, Communication, computing and intelligent Information systems, ICAECIS 2023

作者： Madhav Natarajan, H. Pravallika, Kristipati Chaitanya, K. Saarthak, Dasara Sri Ananda, M. Pes University Dept. of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350348057

Wireless sensor nodes are an important part of many modern systems, such as environmental monitoring networks, smart homes, and industrial automation. These nodes are typically small, low-power devices that are deployed in large numbers to collect data and perform various tasks. However, the limited energy resources of these nodes can be a major limitation to their performance and lifetime. Optimal sensor placement not only minimizes the consumption of limited energy of battery-driven sensors but also reduces the sensing of redundant information. Hence it is of utmost importance to optimize the energy consumed by a wireless sensor network for better sustainability. In this project, we focus on bio-inspired optimization algorithms concerning the optimal sensor node placement in WSNs for a smart agriculture setup namely the Particle Swarm Optimization Algorithm and LEACH Algorithm and prove that the latter is the better algorithm suited for energy conservation by soil moisture wireless sensor nodes placed in a WSN and the same can be extended to any real-life application. A comparative analysis is performed between the stochastic heuristic algorithm in PSO and the hierarchical protocol of the LEACH algorithm for energy consumed by the wireless sensor nodes. © 2023 IEEE.

关键词： Soil moisture

来源：评论

学校读者我要写书评

暂无评论

Correlation between human core body temperature fluctuation and sleep efficiency using time series analysis 12

Correlation between human core body temperature fluctuation ...

引用

Joint 12th international conference on Soft computing and intelligent systems / 23rd international Symposium on Advanced intelligent systems (SCIS and ISIS)

作者： Sakamoto, Hiroaki Yoshida, Yutaka Yuda, Emi Tohoku Univ Ctr Data Driven Sci & Artificial Intelligence Sendai Miyagi Japan

ISBN: (纸本)9781665499248

Core body temperature has relation to sleep. However, unlike body surface temperature, it is difficult to obtain time series data on core body temperature, and few studies have focused on the variability of core body temperature. In this study, we focused on the measurement of core body temperature using a non-contact infrared sensor, measured continuous time-series data of core body temperature during sleep, and investigated the correlation between indices obtained from core body temperature data and sleep indices obtained from a wristband-type wearable sensor. The results showed a negative correlation between the very low frequency component (VLF) calculated from core body temperature fluctuations and deep sleep (r = -0.69). The results suggest that VLF values of core body temperature may be useful as a new sleep evaluation index.

关键词： core body temperature core body temperature variation sleep index non-contact infrared sensor wearable sensor

来源：评论

学校读者我要写书评

暂无评论

Cloud Based Automated Control System Workshops and Rooms for Controlling Parameters 1

Cloud Based Automated Control System Workshops and Rooms for...

引用

1st international conference on advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kumar, Dinesh Kuntal, Ravinder Singh Deep, Pragya Chamoli, Anup Shekhar Singh, Pinki Mandal, Rishabh SRM Institute of Science & Technology Department of Computer Science and Engineering UP Ghaziabad India Nitte Meenakshi Institute of Technology Department of Mathematics Karnataka Bangalore India IIMT College of Engineering Department of AI & DS Greater Noida India Uttaranchal School of Computing Sciences Uttaranchal University Dehradun248001 India Accurate College of Engineering & Management Department of Computer Science and Engineering Greator Noida India Tula's Institute Department of Computer Science and Engineering UK Dehradun India

ISBN: (纸本)9798331518578

Across all industries, cloud-based automated control systems have completely changed how operational and environmental parameters are tracked and controlled. With cloud-integrated systems for real-time data collection, processing, and control, this concept presents intelligent, remote-controlled workshops and control rooms. To guarantee accurate control of crucial variables like temperature, humidity, pressure, and equipment efficiency, these systems make use of IoT devices, AI techniques, and big data analytics. Through sophisticated data perspectives, the cloud-based strategy enables predictive maintenance, improves flexibility, and lowers operating expenses. Stakeholders may make prompt, data-driven choices from anywhere with remote access to control rooms. These seminars provide practical experience with cloud-controlled settings and function as training and development centres. The system's flexibility to meet a range of industrial demands is further enhanced by its compatibility with external tools and equipment. The design, deployment, and possible uses of cloud-based control systems are covered in this paper, with an emphasis on how they might promote operational excellence, energy efficiency, and smart manufacturing. © 2025 IEEE.

关键词： Smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

From the Evolution of Public data Ecosystems to the Evolving Horizons of the Forward-Looking intelligent Public data Ecosystem Empowered by Emerging Technologies 23rd

From the Evolution of Public Data Ecosystems to the Evolving...

引用

23rd international conference on Electronic Government (EGOV)

作者： Nikiforova, Anastasija Lnenicka, Martin Milic, Petar Luterek, Mariusz Rodriguez Bolivar, Manuel Pedro Univ Tartu Tartu Estonia Univ Hradec Kralove Hradec Kralove Czech Republic Univ Pristina Kosovska Mitrovica Kosovska Mitrovica Serbia Univ Warsaw Warsaw Poland Univ Granada Granada Spain

ISBN: (纸本)9783031702730;9783031702747

Public data Ecosystems (PDEs) represent complex socio-technical systems crucial for optimizing data use in the public sector and outside it. Recognizing their multifaceted nature, previous research proposed a six-generation Evolutionary Model of Public data Ecosystems (EMPDE). Designed as a result of a systematic literature review on the topic spanning three decades, this model, while theoretically robust, necessitates empirical validation to enhance its practical applicability. This study addresses this gap by validating the theoretical model through a real-life examination in five European countries - Latvia, Serbia, Czech Republic, Spain, and Poland. This empirical validation provides insights into PDEs dynamics and variations of implementations across contexts, particularly focusing on the 6th generation of forward-looking PDE generation named "intelligent Public data Generation" which represents a paradigm shift driven by emerging technologies such as cloud computing, Artificial Intelligence (AI), Natural Language Processing tools, Generative AI, and Large Language Models with potential to contribute to both automation and augmentation of business processes within these ecosystems. By transcending their traditional status as a mere component, evolving into both an actor and a stakeholder simultaneously, these technologies catalyse innovation and progress, enhancing PDE management strategies to align with societal, regulatory, and technical imperatives in the digital era.

关键词： AI Artificial Intelligence Emerging Technologies Evolution Model Generative AI Open Government data Open data Ecosystem Public data Ecosystem Socio-technical systems systems theory

来源：评论

学校读者我要写书评

暂无评论

Generative AI-driven Automation of Business Process ReImagination 6

Generative AI-Driven Automation of Business Process ReImagin...

引用

6th IEEE international conference on Recent advances in intelligent Computational systems, RAICS 2024

作者： Paulose, Renjith Neelanath, Vinod Ust SmartOps Ust Kochi India Ust SmartOps Ust Trivandrum India

ISBN: (纸本)9798350381689

Traditional business process automation primarily concentrates on digitizing processes to achieve specific outcomes. However, it grapples with challenges stemming from manual configurations and inflexible workflows, restricting adaptability and creativity. This paper delves into the transformative potential of Generative Artificial Intelligence (AI) in revolutionizing process automation, addressing the limitations inherent in traditional approaches. In contrast to traditional automation, Generative AI adopts a groundbreaking approach by harnessing data from past automation solutions to identify more effective methods. This goes beyond conventional orchestration, dynamically integrating software components, automatically generating rules from historical automation solutions data, and seamlessly integrating external systems. Generative AI unlocks its potential through the analysis of past workflows, gaining insights into components, decisions, and sequences. This knowledge serves as the foundation for creating new, efficient processes based on user-described natural language, resulting in robust workflows and rules that assimilate lessons from past best practices and adapt as needed. This innovative approach signifies a notable departure from traditional constraints, paving the way for a future where business processes evolve dynamically, aligning with the efficiency demands of the ever-changing digital landscape. © 2024 IEEE.

关键词： business process automation Generative AI intelligent automation Large Language Model

来源：评论

学校读者我要写书评

暂无评论

5th international conference on advances in Information Communication Technology and computing, AICTC 2024

5th International Conference on Advances in Information Comm...

引用

5th international conference on advances in Information Communication Technology and computing, AICTC 2024

ISBN: (纸本)9789819761029

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56页 << < 5 6 7 8 9 10 11 12 13 14 > >>

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：