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

509 篇 会议
29 篇 期刊文献
2 册 图书

馆藏范围

540 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

352 篇 工学
- 283 篇 计算机科学与技术...
- 141 篇 软件工程
- 40 篇 电气工程
- 27 篇 信息与通信工程
- 14 篇 力学（可授工学、理...
- 14 篇 建筑学
- 13 篇 仪器科学与技术
- 13 篇 土木工程
- 12 篇 电子科学与技术（可...
- 12 篇 控制科学与工程
- 11 篇 化学工程与技术
- 9 篇 生物医学工程（可授...
- 9 篇 生物工程
- 8 篇 机械工程
- 7 篇 光学工程
- 7 篇 动力工程及工程热...
- 6 篇 环境科学与工程（可...
90 篇 理学
- 49 篇 数学
- 21 篇 物理学
- 18 篇 统计学（可授理学、...
- 16 篇 生物学
- 6 篇 化学
- 6 篇 海洋科学
- 6 篇 系统科学
54 篇 管理学
- 35 篇 图书情报与档案管...
- 26 篇 管理科学与工程(可...
- 17 篇 工商管理
27 篇 医学
- 19 篇 临床医学
- 12 篇 基础医学(可授医学...
12 篇 教育学
- 9 篇 教育学
5 篇 法学
4 篇 文学
2 篇 农学
1 篇 经济学

主题

83 篇 visualization
71 篇 data visualizati...
39 篇 data mining
24 篇 data analysis
23 篇 big data
15 篇 visual analytics
15 篇 algorithm design...
15 篇 image color anal...
15 篇 training
12 篇 three-dimensiona...
11 篇 performance anal...
11 篇 feature extracti...
11 篇 software
11 篇 data models
10 篇 tools
10 篇 human-centered c...
10 篇 computational mo...
9 篇 computer archite...
9 篇 dimensionality r...
9 篇 analytical model...

机构

4 篇 northern illinoi...
4 篇 argonne natl lab...
4 篇 northern illinoi...
4 篇 argonne national...
3 篇 deutsches klimar...
3 篇 lawrence berkele...
3 篇 nvidia
3 篇 univ illinois il...
3 篇 ohio state univ ...
3 篇 leipzig universi...
2 篇 academy of scien...
2 篇 uva
2 篇 penn state univ ...
2 篇 univ konstanz co...
2 篇 utah state univ ...
2 篇 twitter 1355 mar...
2 篇 beijing forestry...
2 篇 aalto univ sch s...
2 篇 university of ca...
2 篇 univ waikato cyb...

作者

5 篇 papka michael e.
5 篇 insley joseph a.
4 篇 michael e. papka
4 篇 silvio rizzi
4 篇 mateevitsi victo...
4 篇 agrawal gagan
4 篇 victor a. mateev...
4 篇 rizzi silvio
3 篇 joseph a. insley
3 篇 jefferson amstut...
3 篇 yang juncheng
3 篇 rashmi k. v
3 篇 yue yao
3 篇 amstutz jefferso...
3 篇 burch michael
2 篇 andres sewell
2 篇 castro miguel ra...
2 篇 park cheol woo
2 篇 lessley brenton
2 篇 li jin

语言

528 篇 英文
6 篇 其他
4 篇 葡萄牙文
2 篇 中文
1 篇 意大利文

检索条件"任意字段=14th Symposium on Large Data Analysis and Visualization"

共 540 条记录，以下是71-80 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：

data analysis of Distributed Application Platform Based on the R which Apply to Digital Library 14

Data Analysis of Distributed Application Platform Based on t...

引用

International symposium Distributed Computing and Applications Business Engineering and Science

作者： Wu, Ningbo Yang, Fan Guizhou Univ Finance & Econ Coll Informat Guiyang Peoples R China Guizhou Univ Finance & Econ Guiyang Peoples R China

ISBN: (纸本)9781467365932

Digital Library large data resource lack of analysis and use, in order to mining the value of big data resources, proposed platformization analysis and processing mode. By integrate R and Hadoop to construct distributed data analysis platform, many big data analytical can be decomposed into "large" and "small" data processing section, overcome before scheme puzzle on analytical of large dataset, improve the performance of data analysis, platform able to handle data analysis tasks.

关键词： component big data distributed data analysis

来源：评论

学校读者我要写书评

暂无评论

DBScan and WrapDBScan methods applying for intellectual variance analysis in employee's moving 14

DBScan and WrapDBScan methods applying for intellectual vari...

引用

14th International symposium on Intelligent Systems

作者： Savenkov, P. A. Ivutin, A. N. Tula State Univ Dept Comp Technol Tula Russia

this article discusses the development of mathematical support and software for detecting anomalous behavior of users based on biometric characteristics of their behavior analysis. One of the challenges in intelligent UBA systems is acquisition of useful information from a large volumes of unstructured, unmatched data. Methods and algorithms of intelligent data processing and machine learning used in UBA/DSS systems help to work on a task of solving problems of data analysis of different directivities. It is proposed an application of machine learning methods in implementation of mobile UBA system. there was formed the list of the most significant factors submitted to the input of the analyzing methods during the study. Two approaches of detecting abnormal user behavior have been proposed. the application of machine learning techniques in intelligent UBA systems will make it possible to predict information risks and insider excfiltration of these organizations in advance. (C) 2021 the Authors. Published by Elsevier B.V.

关键词： DLP UBA big data datascience dachine learning DBSCAN

来源：评论

学校读者我要写书评

暂无评论

A Multi-sensor Process for In-Situ Monitoring of Water Pollution in Rivers or Lakes for High-Resolution Quantitative and Qualitative Water Quality data 19

A Multi-sensor Process for In-Situ Monitoring of Water Pollu...

引用

19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016

作者： Randhawa, Sukanya Sandha, Sandeep S Srivastava, Biplav IBM Research-India Bangalore India IBM Research-Yorktown Heights Yorktown Heights United States

ISBN: (纸本)9781509035939

Sensor based environmental monitoring is beginning to gain traction given the recent advancements in sensor development technology. Sensor platforms offer several advantages in comparison to the traditional monitoring approaches based on discrete sampling methods as they offer the capability of providing high resolution data. Access to high-frequency spatial and temporal information facilitates real-time event detection or then understanding the impact of pollution to the water quality in natural water resources. In this paper, we report a multi-sensor process that we developed for in-situ monitoring of water pollution in rivers/lakes in which we acquire real-time water quality data using (a) a multiparametric sensor probe for quantitative data, (b) a crowd sensor via a mobile app for qualitative data and integrate these data onto a cloud platform i.e Bluemix which enables interactive visualization of data as Heatmap combined with geographical mapping. this type of visualization technique not only facilitates effective handling of high-resolution data but also allows large-scale data-driven inspection to identify affected/polluted zones and detection of pollution violations, thereby making it an important tool for enabling decision-making. data analysis based on clustering techniques is also presented. We compare our techniques to traditional data collection methods. Furthermore, to support our efforts in water quality monitoring, we have also developed several web-based applications that are aimed at incorporating sensing data as well as data from various other sources onto a common online platform. We demonstrate the capabilities of our tools through a case study done on Yamuna river in New Delhi where we monitor the river pollution in real-time. © 2016 IEEE.

关键词： visualization

来源：评论

学校读者我要写书评

暂无评论

Lightweight Language Model for Speech Synthesis: Attempts and analysis 14

Lightweight Language Model for Speech Synthesis: Attempts an...

引用

14th International symposium on Chinese Spoken Language Processing

作者： Wu, Zhuojun Liu, Dong Li, Ming Wuhan Univ Sch Comp Sci Wuhan Peoples R China Duke Kunshan Univ Suzhou Municipal Key Lab Multimodal Intelligent S Data Sci Res Ctr Kunshan Peoples R China

ISBN: (纸本)9798331516833;9798331516826

large-scale autoregressive text-to-speech (TTS) models can generate speech that is nearly indistinguishable from human speech. However, training large language models (LLMs) is challenging due to memory and computational constraints. this paper describes our TTS method for the 2024 Conversational Voice Clone Challenge (CoVoC). Our approach modifies the LauraGPT model to synthesize mixed Chinese and English text by expanding the Chinese pinyin vocabulary and reducing the number of layers in the decoder-only Transformer architecture. Despite using minimal training data, the performance gap between our method and other constrained systems is relatively small in both subjective and some objective evaluations. this paper discusses our attempt to train lightweight LLMs for zero-shot TTS and analyzes the factors contributing to low performance. Our audio samples can be accessed online(1).

关键词： text-to-speech speech recognition human-computer interaction computational paralinguistics

来源：评论

学校读者我要写书评

暂无评论

Visual nonlinear discriminant analysis for classifier design 14

Visual nonlinear discriminant analysis for classifier design

引用

14th European symposium on Artificial Neural Networks, ESANN 2006

作者： Iwata, Tomoharu Saito, Kazumi Ueda, Naonori NTT Corporation NTT Communication Science Laboratories 2-4 Hikaridai Seika-cho Keihanna Science City Kyoto Japan

ISBN: (纸本)2930307064

We present a new method for analyzing classifiers by visualization, which we call visual nonlinear discriminant analysis. Classifiers that output posterior probabilities are visualized by embedding samples and classes so as to approximate posterior probabilities using parametric embedding. the visualization provides a better intuitive understanding of such classifier characteristics as separability and generalization ability than conventional methods. We evaluate our method by visualizing classifiers for an artificial data set. © 2006 *** publication. All rights reserved.

关键词： visualization

来源：评论

学校读者我要写书评

暂无评论

Location-Based Geographical-Spatial data Mining for Detection and visualization of Reported Problems using Image Processing Techniques 14

Location-Based Geographical-Spatial Data Mining for Detectio...

引用

14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Harsoor, Anita Soma, Bhavani P D A College of Engineering Department of Computer Science and Engineering Kalaburagi India

We face many possible problems/issues in our daily lives, such as potholes, garbage filling, uncomfortable parking, broken roads, etc. To report that kind of problem becomes a great hassle. To solve this problem we developed a Geographical-Spatial data Mining System (GDMS), an android mobile application named Civicawareness for retrieving and analyzing textual data with geographical locations and photos as proof. the model has four constituents: data collection, data pre-processing, data analysis, and data visualization. Here, we use the k-means algorithm for clustering and SVM for classification. this system will collect a large number of data that will be used by common people to post the problems they have found. © Grenze Scientific Society, 2023.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

Tactical Rings: A visualization Technique for Analyzing Tactical Patterns in Tennis 14th

Tactical Rings: A Visualization Technique for Analyzing Tact...

引用

14th International symposium on Visual Computing (ISVC)

作者： Pokharel, Shiraj Zhu, Ying Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA Georgia State Univ Creat Media Ind Inst Atlanta GA 30303 USA

ISBN: (纸本)9783030337230;9783030337223

Sports data visualization can be a useful tool for analyzing or presenting sports data. In this paper, we present a new technique to visualize and analyze shot-by-shot tactical patterns in tennis. Previous work in tennis data analysis and visualization focus more on high-level statistics and overviews such as heat-maps but did not handle data analytics at micro-level. Our visualization technique can reveal patterns and imbalances in a tennis match that lead to a deeper understanding of the game. We demonstrate the application and benefits of our visualization technique with case studies.

关键词： visualization systems Visual analytics Visual data mining and knowledge discovery

来源：评论

学校读者我要写书评

暂无评论

Hierarchical analysis of GSM network performance data 14

Hierarchical analysis of GSM network performance data

引用

14th European symposium on Artificial Neural Networks, ESANN 2006

作者： Multanen, Mikko Raivio, Kimmo Lehtimäki, Pasi Helsinki University of Technology Laboratory of Computer and Information Science HUT P.O. Box 5400 FI-02015 Finland

ISBN: (纸本)2930307064

In this study, a method for hierarchical examination and visualization of GSM data using the Self-Organizing Map (SOM) is described. the data is examined in few phases. At first temporally averaged data is used and then, in each phase some of the data is discarded and the rest is examined in more detail. the SOM is used both in clustering and in visualization. the actual clustering is performed to the nodes of the SOM to lower the computational cost and to help to understand better the properties of the clusters. © 2006 *** publication. All rights reserved.

关键词： Self organizing maps

来源：评论

学校读者我要写书评

暂无评论

Breaking the Curse of Visual data Exploration: Improving Analyses by Building Bridges between data World and Real World 10

Breaking the Curse of Visual Data Exploration: Improving Ana...

引用

14th International Joint Conference on Computer Vision, Imaging and Computer Graphics theory and Applications (VISIGRAPP) / 10th International Conference on Information visualization theory and Applications (IVAPP)

作者： Kraus, Matthias Weiler, Niklas Breitkreutz, thorsten Keim, Daniel A. Stein, Manuel Univ Konstanz Data Anal & Visualizat Constance Germany

ISBN: (纸本)9789897583544

Visual data exploration is a useful means to extract relevant information from large sets of data. the visual analytics pipeline processes data recorded from the real world to extract knowledge from gathered data. Subsequently, the resulting knowledge is associated with the real world and applied to it. However, the considered data for the analysis is usually only a small fraction of the actual real-world data and lacks above all in context information. It can easily happen that crucial context information is disregarded, leading to false conclusions about the real world. therefore, conclusions and reasoning based on the analysis of this data pertain to the world represented by the data, and may not be valid for the real world. the purpose of this paper is to raise awareness of this discrepancy between the data world and the real world which has a high impact on the validity of analysis results in the real world. We propose two strategies which help to identify and remove specific differences between the data world and the real world. the usefulness and applicability of our strategies are demonstrated via several use cases.

关键词： visualization theory Uncertainty Validation Visual Analytics

来源：评论

学校读者我要写书评

暂无评论

A 3D-shockwave volume rendering algorithm based on feature boundary detection 14

A 3D-shockwave volume rendering algorithm based on feature b...

引用

14th IADIS International Conference Computer Graphics, visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and 5th IADIS International Conference Big data Analytics, data Mining and Computational Intelligence 2020, BigDaCI 2020 and 9th IADIS International Conference theory and Practice in Modern Computing 2020, TPMC 2020, Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020

作者： Wang, Huawei He, Liu Ai, Zhiwei Cao, Yi Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing100088 China CAEP Software Center for High Performance Numerical Simulation Beijing100088 China

ISBN: (纸本)9789898704214

the mechanism of shockwave propagation in complex environments plays an important role in the damage and protection assessment. At present, domain experts are realizing shockwave propagation numerical simulations with high scientific confidence on thousands of processing cores, and thus large-scale three-dimensional (3D) data fields containing fine physical features are output. It is desired to effectively reveal complex spatial structures of shockwaves in the data fields so as to facilitate domain experts to make in-depth observation and analysis. In this paper, a volume rendering algorithm based on feature boundary detection is proposed to visualize 3D shockwave data fields. In the algorithm, a two-dimensional (2D) boundary detection technique is generalized to the 3D case and further used to extract feature data containing the wavefronts, and then, the feature data are resampled and composited in the ray-casting manner. the algorithm has been preliminarily applied to 3D shock fields, and the results show that the algorithm can effectively analyze the shockwave features and clearly show the 3D spatial structures of the wavefronts. © Proceedings of the 14th IADIS International Conference Computer Graphics, visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and Proceedings of the 5th IADIS International Conference Big data Analytics, data Mining and Computational Intelligence 2020, BigDaCI 2020 and Proceedings of the 9th IADIS International Conference theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.

关键词： visualization

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54页 << < 4 5 6 7 8 9 10 11 12 13 > >>

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：