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

40,726 篇 会议
2,944 册 图书

馆藏范围

43,669 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

39,908 篇 工学
- 38,450 篇 计算机科学与技术...
- 7,386 篇 软件工程
- 4,031 篇 信息与通信工程
- 3,157 篇 电气工程
- 2,324 篇 控制科学与工程
- 792 篇 生物医学工程（可授...
- 499 篇 生物工程
- 333 篇 机械工程
- 285 篇 交通运输工程
- 179 篇 电子科学与技术（可...
- 165 篇 土木工程
- 164 篇 光学工程
- 163 篇 化学工程与技术
3,496 篇 管理学
- 1,942 篇 管理科学与工程(可...
- 1,236 篇 图书情报与档案管...
- 925 篇 工商管理
3,217 篇 理学
- 1,946 篇 数学
- 886 篇 生物学
- 519 篇 统计学（可授理学、...
- 368 篇 物理学
- 220 篇 系统科学
- 158 篇 化学
1,498 篇 医学
- 967 篇 临床医学
- 693 篇 基础医学(可授医学...
- 235 篇 特种医学
1,484 篇 教育学
- 1,402 篇 教育学
531 篇 文学
- 352 篇 外国语言文学
- 178 篇 新闻传播学
437 篇 经济学
- 317 篇 理论经济学
402 篇 法学
- 366 篇 社会学
177 篇 艺术学
95 篇 历史学
79 篇 农学
11 篇 军事学

主题

1,854 篇 artificial intel...
1,169 篇 machine learning
872 篇 deep learning
777 篇 computer communi...
668 篇 information syst...
558 篇 computer applica...
328 篇 computer systems...
309 篇 cloud computing
297 篇 clustering
295 篇 security
289 篇 internet of thin...
270 篇 software enginee...
269 篇 classification
235 篇 information syst...
229 篇 computer imaging...
224 篇 data mining
218 篇 software enginee...
207 篇 data mining and ...
207 篇 ontology
180 篇 computers and ed...

机构

80 篇 univ chinese aca...
76 篇 univ dist franci...
69 篇 chinese acad sci...
67 篇 shanghai univ sc...
48 篇 tsinghua univers...
43 篇 natl res univ hi...
39 篇 huazhong univers...
35 篇 harbin inst tech...
33 篇 tsinghua univ de...
30 篇 shanghai jiao to...
29 篇 pontificia univ ...
29 篇 harbin universit...
27 篇 polytechnic inst...
27 篇 chinese acad sci...
26 篇 lomonosov moscow...
25 篇 chongqing univ s...
25 篇 beijing univ pos...
24 篇 university of cr...
24 篇 hunan univ coll ...
23 篇 univ nacl colomb...

作者

58 篇 kim tai-hoon
53 篇 lima jose
43 篇 o'connor rory v.
37 篇 wang lei
34 篇 liu yang
33 篇 zhang lin
31 篇 kim seoksoo
30 篇 wang jing
28 篇 sabu m. thampi
28 篇 crawford broderi...
26 篇 zhang lei
25 篇 li yang
25 篇 li li
24 篇 wang jian
21 篇 zhang min
20 篇 hassanien aboul ...
19 篇 li peng
19 篇 serra roberto
18 篇 li xin
18 篇 wang hui

语言

43,504 篇 英文
965 篇 中文
1 篇 丹麦文

检索条件"丛书名=Communications in Computer and Information Science"

共 43670 条记录，以下是1061-1070 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：

Intelligent Seasonal Air Quality Prediction with Machine Learning Models: Enhancing Performance Through Polynomial Regression and Bayesian Optimization 4th

Intelligent Seasonal Air Quality Prediction with Machine Lea...

引用

4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Padaliya, Sneh Saxena, Swati De, Aloknath GSFC Univ Vadodara Gujarat India CTO CVP Retd TechCraftercps Adjunct Prof IISc Banglore Bangalore Karnataka India

ISBN: (纸本)9783031837920;9783031837937

Accurate seasonal air quality prediction is crucial for effective environmental management and public health. This study introduces a novel approach that integrates Polynomial Regression with Bayesian Optimization for forecasting air quality indices (AQI). Traditional ensemble models such as Gradient Boosting, Random Forest, XGBoost, LightGBM and CatBoost, while effective, often face challenges like overfitting, high computational demands and complex hyperparameter tuning. Our approach addresses these issues by using Polynomial Regression to capture non-linear relationships and Bayesian Optimization to streamline hyperparameter tuning, enhancing model efficiency and interpretability. The proposed model outperforms conventional methods based on Mean Squared Error (MSE). Seasonal pollutant analysis also highlights unique patterns in air quality changes, providing deeper insights for better environmental decision-making. Future research will focus on integrating advanced techniques and more variables to further refine and broaden the model's applicability.

关键词： Air Quality Monitoring Air Quality Prediction Ensemble Methods Intelligent Computing Machine Learning

来源：评论

学校读者我要写书评

暂无评论

Towards Augmenting Human-Centred Design: Generative AI Tools for Interaction Research and Design 1

引用

8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Gross, Tom Univ Bamberg Human Comp Interact Grp D-96045 Bamberg Germany

ISBN: (数字)9783031826337

ISBN: (纸本)9783031826320;9783031826337

Generative AI tools are hailed as a motor for revolutionising our work and life. Recently, tools based on large language and foundation models, such as ChatGPT, have also become a hot topic in interaction research and interaction design. This paper contributes a discussion of whether and how Generative AI tools can be used to augment interaction research and interaction design throughout the whole process of Human-Centred Design for Interactive Systems as defined by the International Organization for Standardization. The paper compiles an extended, up-to-date version of the process model covering highly relevant additions of methods bridging the gap between interaction research and interaction design in each of the processes. It then suggests Generative AI tools to support those methods. Finally, it discusses vital aspects of interaction research and interaction design concerning the current design practice, the respective design situation, and the design circumstances at large.

关键词： Human-Centred design Generative AI Process modelsm Methods Interaction research Interaction design

来源：评论

学校读者我要写书评

暂无评论

Multiscale Clustering to Improve Anomaly Detection in Nuclear Equipments 5th

Multiscale Clustering to Improve Anomaly Detection in Nuclea...

引用

5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Saley, Amaratou Mahamadou Moyaux, Thierry Sekhari, Aicha Bouleux, Guillaume Cheutet, Vincent Danielou, Jean-Baptiste INEO Nucl Lyon France Univ Jean Monnet St Etienne Univ Claude Bernard Lyon 1 Univ Lumiere Lyon 2 INSA LyonDISPUR4570 F-69621 Villeurbanne France

ISBN: (纸本)9783031807596;9783031807602

In the nuclear industry, the relentless pursuit of operational excellence and reliability is paramount, especially considering the critical importance of safety and efficiency. This sector, a key component of global energy supply, is constantly driven to innovate and optimize its equipments. Early fault detection plays a central role in this endeavor, as it not only helps to prevent potential incidents, but also maximizes production. Traditional anomaly detection methods, primarily based on clustering algorithms, often overlook minor yet warning faults. Addressing this, our paper introduces a multiscale clustering approach, advancing beyond classical methods. This methods achieves a satisfactory classification of anomalies and culminates in a silhouette score of 90%. Additionally, it facilitates the computation of a preventive maintenance indicator.

关键词： Predictive maintenance Anomaly detection Clustering methods Time series Nuclear industry

来源：评论

学校读者我要写书评

暂无评论

Managing Classified information by a Third-Party Contractor: A Computational Cybersecurity Analysis 8th

Managing Classified Information by a Third-Party Contractor:...

引用

8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Keijzer, Sebastiaan Lochtenbergh, Daan Marsman, Thom Voorhoeve, Sam Zwarts, Natalia Bouma, Debby Treur, Jan Roelofsma, Peter H. M. P. Hague Univ Appl Sci Ctr Expertise Cybersecur Risk Management & Cybersecur Grp The Hague Netherlands Vrije Univ Amsterdam Dept Comp Sci Social Grp Amsterdam Netherlands

ISBN: (纸本)9783031838446;9783031838453

In this paper, a computational analysis is contributed of the process of a third-party contractor being contracted by a governmental body to store classified documentation. The several steps to complete this process are modeled in a network-oriented manner including contractualization and deployment of suppressing risk measures to mitigate the risks and limit the damages potentially caused by the compromise of these documents. What-If analysis has been performed for the simulation experimental setup.

关键词： Third party Cybersecurity Computational

来源：评论

学校读者我要写书评

暂无评论

An Interactive Intelligent System of Creating a Class Schedule 2nd

An Interactive Intelligent System of Creating a Class Schedu...

引用

2nd International Conference on information Technologies and Their Applications

作者： Ismibayli, Reshad Rzayeva, Sona Univ Architecture & Construct Baku Azerbaijan Inst Control Syst Baku Azerbaijan

ISBN: (纸本)9783031734168;9783031734175

The article describes the process of creating a class schedule in educational institutions with a classical education system. The requirements and restrictions for the class schedule are given. A model for interactive scheduling of classes in an educational institution is proposed. Interactive scheduling, which is based on the "traffic light" principle, frees the user from the control of all hard restrictions and warns about violations of soft restrictions, which ensures that there are no conflict situations in the schedule. All this is done in interaction with the user, who is an active participant in this process. The user sees how the schedule is being compiled and can intervene in this process at any stage. The developed system ensures the creation of an acceptable schedule and its optimization according to the priorities of user-selected criteria. The intellectual capabilities of the program built into the system control the admissibility of the duration of classes, the start and end times of classes, dividing groups into subgroups, combining groups into streams, and taking into account the division of classes into upper/lower weeks.

关键词： Class Schedule Requirements and Restrictions to the Schedule Interactive Mode "Traffic Light" Principle Acceptable Schedule

来源：评论

学校读者我要写书评

暂无评论

Cancer Classification in Breast Imaging via Enhanced CNN Deep Learning Architecture 4th

Cancer Classification in Breast Imaging via Enhanced CNN Dee...

引用

4th International Conference on Intelligent Systems and Pattern Recognition-ISPR

作者： AlKhater, Rozah Al-maadeed, Somaya Qatar Univ Doha Qatar

ISBN: (纸本)9783031821554;9783031821561

A major factor in determining the future probability of breast cancer is the early and precise identification of breast abnormalities, which includes differentiating between malignancy, normal tissues, and suspected cancer. The mortality rate can be reduced if the condition is detected early. It takes a lot of time for doctors and radiologists to examine histopathological images for breast cancer manually. The use of deep learning algorithms for medical imaging issues has garnered much interest due to its rapid progress. This paper introduces a novel customized 20-layered Convolutional Neural Network (CNN) architecture to avoid manual analysis and streamline the classification process. The customized proposed CNN is compared with the ResNet50 model, in which the initial layers are freezed, and the last layers are modified and fine-tuned to achieve the optimized model. Among the two models, the highest training and testing accuracy of 99.03% and 92.90%, respectively, is achieved by the proposed CNN model. The proposed model outperforms the benchmarked models on the same dataset.

关键词： CNN ResNet transfer learning deep learning AI medical imaging

来源：评论

学校读者我要写书评

暂无评论

Optimally Traversing Explainability in Bayesian Networks via the Graphical Lasso 5th

Optimally Traversing Explainability in Bayesian Networks via...

引用

5th Southern African Conference for Artificial Intelligence Research

作者： Derks, Iena Petronella de Waal, Alta Smith, Jarod Loots, Theodor Stander, Jean-Pierre Univ Pretoria Dept Stat Pretoria South Africa Bayer Motorenwerke AG Munich Germany

ISBN: (纸本)9783031782541;9783031782558

Abductive inference plays a critical role in solving problems involving uncertain information and multiple competing hypotheses. In the Bayesian network framework, abductive inference involves generating the configuration of target variables that best explains the observed evidence. Furthermore, research has shown that these configurations should be precise and concise. However, the search space for potential explanations can be vast, particularly in more complex networks, requiring efficient search algorithms to traverse this space and find optimal configurations. This aligns with the challenges in explainable artificial intelligence, where researchers aim to provide relevant and meaningful explanations in a computationally efficient manner. Previous work has focused on developing several search algorithms, such as forward, backward, tabu, and reverse jump MCMC algorithms. Algorithms like the forward search algorithm still involve exhaustive searching as it does not prune the neighbourhood of potential solutions. To address this, we propose incorporating a statistical neighbourhood selection method, such as the graphical Lasso (Least Absolute Shrinkage and Selection Operator), with the forward search algorithm to prune the search space. The graphical Lasso's penalty term encourages sparsity, helping to prune less relevant variables, thereby improving computational efficiency. By reducing the set of instantiations, the forward-gLasso algorithm provides explanations focusing on the most relevant dependencies. We evaluate the performance and computational efficiency of the forward-gLasso algorithm on a set of benchmark Bayesian networks and compare it to the forward search algorithm.

关键词： Explainable artificial intelligence Bayesian networks most relevant explanation graphical Lasso

来源：评论

学校读者我要写书评

暂无评论

MEGKT: Multi-edge Features Enhancement for Graph-Based Knowledge Tracing 7th

MEGKT: Multi-edge Features Enhancement for Graph-Based Knowl...

引用

8th Asia Pacific Web and Web-Age information Management Joint International Conference on Web and Big Data

作者： Zhang, Lei Zhao, Linlin Zhang, Zhenguo Yanbian Univ Dept Comp Sci & Technol 977 Gongyuan Rd Yanji 133002 Peoples R China

ISBN: (纸本)9789819600540;9789819600557

Knowledge tracing (KT) captures the mastery status and proficiency level of students by modeling the answer information in their historical answering records, and then predicts their future answering situations. It can help teachers better grasp their learning situation and make more reasonable and targeted teaching plans. The previous methods mainly focus on the temporal changes in the learning process of students, ignoring the spatial relationships between students, exercises, and knowledge concepts. Graph is an effective way to model these relationships and several works have been shown it's feasibility. However, existing graph-based KT methods mainly extract features from the predefined simple graphs, which usually is a single type of information in students' answering records. To better utilize the abundant information hidden in multiple correlations, we propose a new model called Multi-Edge Features Enhancement for Graph-Based Knowledge Tracing (MEGKT). In MEGKT, we first model student historical learning records as two heterogeneous graphs, where there are three types of edges between students and exercises, students and students, exercises and exercises. Then, we explore the implicit information of student answering situations from the constructed heterogeneous graphs by employing Edge Aggregated Graph Attention Network (EGAT), to build different student models. On this basis, we integrate these student models into a stronger teacher model through online knowledge distillation, allowing the teacher model to supervise the learning of the student model to achieve better results and make predictions through the teacher model. To evaluate the performance of the proposed MEGKT, we do experiments on two real education datasets and the results show that our MEGKT has achieved state-of-the-art performance in predicting student answering exercises.

关键词： Knowledge Tracing Heterogeneous Graph Multiple Edge Features Online Knowledge Distillation

来源：评论

学校读者我要写书评

暂无评论

Data to Decisions: A Computational Framework to Identify Skill Requirements from Advertorial Data 4th

Data to Decisions: A Computational Framework to Identify Ski...

引用

4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Singh, Aakash Kanaujia, Anurag Singh, Vivek Kumar Univ Delhi Dept Comp Sci Delhi 110007 India Banaras Hindu Univ Dept Comp Sci Varanasi 221005 Uttar Pradesh India Univ Delhi Delhi Sch Analyt Delhi 110007 India

ISBN: (纸本)9783031837920;9783031837937

Human capital, or skilled labor, stands out among the factors of production due to its ability to continually evolve and adapt to changing conditions and resources. This flexibility makes human capital the most essential factor for achieving sustainable growth in any industry/sector. As new technologies are developed and adopted, the new generations are required to acquire skills in newer technologies in order to be employable. At the same time professionals are required to upskill and reskill themselves to remain relevant in the industry. There is however no straightforward method to identify the skill needs of the industry at a given point of time. Therefore, this paper proposes a data to decision framework that can successfully identify the desired skill set in a given area by analysing the advertorial data collected from popular online job portals and supplied as input to the framework. The proposed framework uses techniques of statistical analysis, data mining and natural language processing for the purpose. The applicability of the framework is demonstrated on CS&IT job advertisement data from India. The analytical results not only provide useful insights about current state of skill needs in CS&IT industry but also provide decision support to prospective job applicants, training agencies, and institutions of higher education & professional training.

关键词： Advertorial Data computer science Data Analytics information Technology Skill Recommendations

来源：评论

学校读者我要写书评

暂无评论

Scaling Evaluation of Non-objective Assessments Using AI-Based Solutions 17th

Scaling Evaluation of Non-objective Assessments Using AI-Bas...

引用

17th India Compute Conference-COMPUTE-Annual

作者： Chaturvedi, Harsha Srinivasa, Gowri Hegde, Akarsh Adiga, Ananya Paul, Anwesha Poornachandra, M. Simha, Tejas R. PES Univ 4gd Ai Bengaluru 560085 India PES Univ Dept Comp Sci & Engn Bengaluru 560085 India PES Univ Dept Elect & Commun Engn Bengaluru 560085 India PES Univ PES Ctr Pattern Recognit Bengaluru 560085 India

ISBN: (纸本)9783031843907;9783031843914

Evaluation of student answer scripts for multiple in-semester and end-semester assessments is beset with the challenges of scale, fairness and timeliness of providing meaningful feedback to students to facilitate their learning. The time-consuming and biased nature of manual evaluation has necessitated the development of automated grading systems. This work presents a solution that incorporates automated and near real-time digital evaluation of students descriptive answer scripts utilizing multi-modal Large Language Models (LLMs) across various university courses. The methodology involves a three-stage sequential process: setting up Retrieval Augmented Generation (RAG), context-aware rubric generation, and context-aware evaluation. We use RAG to provide context to the LLMs to automate the rubric composition for a question and perform an evaluation of answers submitted in hybrid mode (handwritten or digitally keyed in) in near-real time. The incorporation of inputs from one or more course instructors on the LLM-generated rubric vouchsafes meaningful feedback for students to facilitate learning. The results demonstrate the efficacy of our workflow on multiple undergraduate and graduate courses offered to students majoring in several Engineering courses, thus offering a promising solution to the challenge of providing scalable, automated assessments with feedback that facilitates learning.

关键词： automated evaluation Large Language Models (LLMs) Rubric Retrieval Augmented Generation (RAG) Optical Mark Recognition (OMR) Generative Pre-trained Transformer (GPT)

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500页 << < 103 104 105 106 107 108 109 110 111 112 > >>

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：