检索结果-内蒙古大学图书馆

7th ieee International Conference of Computer science and Information Technology, ICOSNIKOM 2023

作者： Hasugian, Paska Marto Mawengkang, Herman Sihombing, Poltak Efendi, Syahril University of Sumatera Utara Faculty of Computer Science and Information Technology Medan Indonesia Faculty of Mathematics and Natural Sciences Department of Mathematics Medan Indonesia

ISBN: (纸本)9798350360752

In the age of big data, high-dimensional and complex data create significant challenges for data visualization. This research analyzes their impact on visualization techniques. Increasing data dimensions make traditional methods struggle to depict complex structures and patterns. This study comprehensively explores challenges arising from high dimensionality and data complexity in visualization. By examining various techniques and their suitability for such data, we aim to reveal the pros and cons of each approach in conveying essential information. Additionally, this research investigates using dimension reduction techniques to tackle the complexities of the data. The effectiveness of these techniques in preserving crucial information while enhancing visualization quality is evaluated. Some of the models examined include Multidimensional Scaling (MDS), which projects data into a lower-dimensional space to maintain distance relationships but does not consider class labels. MDS operates with a distance matrix but is sensitive to data that do not conform to distance metrics and can yield suboptimal projections in high-dimensional space. Principal Component Analysis (PCA) focuses on dimension reduction by maximizing data variance but does not consider class labels. PCA requires high-dimensional data and cannot handle non-linear structures. Linear Discriminant Analysis (LDA) is used for classification by maximizing inter-class distances, minimizing intra-class distances, and requiring class labels. However, LDA works well only under the assumptions of normal distribution and fulfilled class variance differences. Conversely, t-SNE and UMAP reveal data cluster structures. t-SNE is computationally complex and sensitive to parameters, while UMAP performs faster. t-SNE interprets data with topological and network context, suited for data with strong topological structures but requiring deep domain knowledge. Each method has its uses and limitations, depending on analysis goa

关键词： visualization

来源：评论

学校读者我要写书评

暂无评论

Tomo2Mesh: Fast Porosity Mapping and visualization for Synchrotron Tomography 19

Tomo2Mesh: Fast Porosity Mapping and Visualization for Synch...

引用

19th ieee International Conference on e-science, e-science 2023

作者： Tekawade, Aniket Nikitin, Viktor Satapathy, Yashas Liu, Zhengchun Zhang, Xuan Kenesei, Peter Zheng, Weijian De Carlo, Francesco Foster, Ian Kettimuthu, Rajkumar Data Science and Learning Division Argonne National Laboratory United States X-ray Science Division Argonne National Laboratory United States Nuclear Science Division Argonne National Laboratory United States

ISBN: (纸本)9798350322231

Applications of X-ray computed tomography (CT) in porosity characterization of engineering materials often involve an extensive data analysis workflow. This workflow includes CT reconstruction of raw projection data, binarization, labeling, and mesh extraction. Mapping porosity in larger samples presents a significant computational challenge, as it requires processing gigabytes of raw data to extract porosity information, which becomes a critical bottleneck in the analysis. In this study, we present algorithms and an implementation of an end-to-end porosity mapping framework. Our framework processes raw projection data obtained from a synchrotron CT instrument, generating a porosity map and a visualization in the form of a triangular face mesh. To achieve this objective, we introduce a novel subset reconstruction scheme for X-ray CT, combining filtered back-projection and a convolutional neural network. This scheme allows us to reconstruct subsets of a tomography object with arbitrary shapes. Building upon this scheme, we have developed a fast and efficient framework for porosity mapping. Initially, our framework detects potential voids by performing a coarse reconstruction on down-sampled projections. Subsequently, we enhance the shape of these voids by reconstructing selected subsets from the original raw data, providing higher detail. To evaluate the performance of our framework, we measured the processing time from raw data to a triangular face mesh across multiple visualization scenarios. Our experiments were conducted on a single high-performance workstation equipped with a GPU. The results demonstrate that our framework enables the visualization of local porosity within an 8-gigavoxel CT volume (12 gigabytes raw data) in just 1 to 2 minutes. Moreover, for a larger 64-gigavoxel CT volume (100 gigabytes of raw data), the visualization can be generated within 3 to 7 minutes, showcasing the efficiency of our approach. © 2023 ieee.

关键词： Porosity

来源：评论

学校读者我要写书评

暂无评论

Invertible Image Decolorization With CFEH and Reversible data Hiding

引用

ieee TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2024年第12期34卷 12811-12822页

作者： Zhu, Yike Hu, Runwen Xiang, Shijun Jinan Univ Coll Informat Sci & Technol Guangzhou 510632 Peoples R China

In the field of invertible image decolorization, how to reduce artifacts in the smooth grayscale regions and prevent color distortion at the boundaries of the reconstructed color image is a crucial issue. In this paper, we propose an invertible deep learning network with extraction and hiding of color information. Our approach separates the original color image into the luminance and chromaticity planes by using orthogonal transformation, which enhances the independence and completeness of color and luminance information. Then, the color feature extraction module is developed to minimize color information distortion, while the color hiding module is adopted to hide color information invisibly. Compared with existing deep-learning-based methods, the proposed network can preserve more color information while ensuring the quality of grayscale images by processing color and grayscale information separately. Furthermore, we propose a reversible data hiding strategy that enhances the performance of the reconstructed color images. Our method outperforms learned invertible image decolorization methods, as demonstrated through experiments on the VOC2012, Kodak24, and NCD datasets.

关键词： Image color analysis Gray-scale Color Image reconstruction Feature extraction visualization Image coding Invertible image decolorization deep learning orthogonal transformation

来源：评论

学校读者我要写书评

暂无评论

Using Extended Reality Technology in science Education

Using Extended Reality Technology in Science Education

引用

ieee Long Island Systems, Applications and Technology Conference (LISAT)

作者： Cumberbatch, Iman Olatunji, James Robila, Stefan A. Montclair State Univ Sch Comp Montclair NJ 07043 USA

ISBN: (纸本)9798350311167

Across all scientific fields, the amount of data generated continues to grow exponentially, which creates both opportunities and challenges. Increased availability allows for new insights into phenomena and stimulates discovery. While traditional ways of interacting with data have focused mostly on flat displays, Extended Reality (XR) technologies have the potential to transform the way both research and education are done. They provide an immersive and interactive experience that allows participants to visualize and interact with data while also working collaboratively. In this paper, the research and development of immersive educational 3D visualization tools aligned with several science drivers including environmental science and sustainability and life sciences is described. Specifically, the development of two XR applications is discussed with emphasis on the innovative mechanisms introduced using head-mounted display technologies. Preliminary results from the prototype applications indicate that the use of the XR technologies significantly expands the visualization ability by integrating additional data sources and improving the user's experience.

关键词： modeling science education sustainability virtual reality

来源：评论

学校读者我要写书评

暂无评论

Exploring the Reform of Mathematical Finance Course Based on data visualization: Evidence from Nonparametric Causality-in-Quantiles Tests

Exploring the Reform of Mathematical Finance Course Based on...

引用

2023 International Conference on Algorithms, Computing and data Processing, ACDP 2023

作者： Gao, Wang Zhang, Linlin Cao, Qian Hebei University of Economics and Business Research Center for Finance and Enterprise Innovation Shijiazhuang050062 China School of Finance Hebei University of Economics and Business Shijiazhuang China School of Information Technology Hebei University of Economics and Business Shijiazhuang China Institute of Science and Technology Information Beijing Academy of Science and Technology Beijing China

ISBN: (纸本)9798350326680

data visualization is the use of graphical or visual representations to convey complex information, such as financial data. By incorporating data visualization techniques into mathematical finance courses, educators can help students deepen their understanding of financial concepts and theories, and cultivate practical skills that are essential in the finance industry. This paper employs nonparametric causality-in-quantiles tests to verify that visualizing the entire process of mathematical finance can help improve the grades of the course, especially for average students. This can help students prepare for careers in finance and related fields. © 2023 ieee.

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

A Real-Time 3D data visualization System for Underwater Wireless Sensor Networks

A Real-Time 3D Data Visualization System for Underwater Wire...

引用

2023 ieee/CIC International Conference on Communications in China, ICCC 2023

作者： Huangfu, Bingwen Guo, Jiani Song, Shanshan Liu, Jun Cui, Jun-Hong Jilin University College of Computer Science and Technology Changchun China Beihang University School of Electronic and Information Engineering Beijing China University of Electronic Science and Technology of China Ocean Electronic Information Industry Research Institute China

ISBN: (纸本)9798350345384

Observing topology and communication process in real time is critical for dealing with unexpected situations of Underwater Wireless Sensor Networks (UWSNs). However, due to low bandwidth, limited energy, and severe collisions of underwater acoustic communication, UWSNs are unbearable to afford communication overhead of additional packets for visualization. Moreover, each packet only records the transmission information of one single hop, which imposes great challenges to match nodes with transmission results, failing to visualize the whole propagation path of one packet in multi-hop UWSNs. To this end, we propose a 3D data visualization system (TDVS) to visualize UWSNs' topology and communication process in real time without extra communication overhead. TDVS consists of three parts: data collection, data process and UWSNs presentation. data collection method is proposed to collect UWSNs' status by overhearing packets on the broadcast acoustic channel, without additional energy consumption. Then we design a data process algorithm to extract and analyze visualization-related data from discrete and redundant packets, achieving sending and receiving match, success storage, error reproduction, and collision retrieval. UWSNs presentation module visualizes network topology, data propagation path, data content, and node movement with 3D models and animations. We verified stability and accuracy of TDVS in a NS-3 based simulator called Aqua-Sim-Tg and a 20-heterogeneous-node network sea trial in Dalian, China. © 2023 ieee.

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

Indy Survey Tool: A Framework to Unearth Correlations in Survey data

Indy Survey Tool: A Framework to Unearth Correlations in Sur...

引用

ieee Conference on visualization and Visual Analytics (ieee VIS)

作者： Crnovrsanin, Tarik Di Bartolomeo, Sara Wilson, Connor Dunne, Cody Northeastern Univ Boston MA 02115 USA

ISBN: (纸本)9798350325577

Survey companion websites allow users to explore collected survey information more deeply, as well as update or add entries for papers. These sites can help information stay relevant past the original release date of the survey paper. However, creating and maintaining a website can be laborious and difficult, especially when authors might not be experienced with programming. We introduce Indy Survey Tool to help authors develop companion websites for survey papers across diverse fields of study. The tool's core aim is to identify correlations between categorizations of papers. To accomplish this, the tool offers multiple combined filters and correlation matrix visualizations that enable users to explore the data from diverse perspectives. The tool's visualizations, list of papers, and filters are harmoniously integrated and highly responsive, providing users with feedback based on their selections. Identifying correlations in survey papers is a pivotal aspect of research, as it can enable the recognition of common combinations of categorizations within the papers-as well as highlight any omissions. The versatility of Indy Survey Tool enables researchers to delve into the correlations between categorizations in survey data, an essential aspect of research that can reveal gaps in the literature and highlight promising areas for future exploration. A preprint and supplemental material for the paper can be found at ***/tdhqn.

关键词： Software tool systematic review literature review survey co-occurrence visualization Human-centered computing visualization visualization systems and tools visualization toolkits General and reference Document types-Surveys and overviews

来源：评论

学校读者我要写书评

暂无评论

A data-driven visualization Platform for Sailing Robots

A Data-driven Visualization Platform for Sailing Robots

引用

2023 ieee International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Zhang, Na Lin, Shuyi Sun, Qinbo Qi, Weimin Qian, Huihuan The Chinese University of HongKong School of Science and Engineering Shenzhen China The Chinese University of HongKong Shenzhen Institute of Artificial Intelligent and Robotics for Society Shenzhen China

ISBN: (纸本)9798350327182

This research aims to develop a visualization platform for sailing robots using Unreal Engine 5. This platform can provide valuable insights and analysis by simulating the sailing of real sailboats in a virtual environment. To achieve this, we utilize Blender to model and Unreal Engine 5 to create realistic ocean scenes with simulations of natural wind and waves. The motion state of the OceanVoy460, collected from its sensors, was imported into the blueprint via the data Table plugin in Unreal Engine 5 to control the sailboat. The platform also enables the export of the simulated sailing information for comparison with actual data to test the accuracy of the visualization. In conclusion, we have successfully developed a data-driven visualization platform for sailing robots, utilized real-world data to conduct experiments, and verified the platform's reliability. © 2023 ieee.

关键词： Engines

来源：评论

学校读者我要写书评

暂无评论

Exploring the Design of visualizations of Personal Online data Based on Users' Mental Models 27

Exploring the Design of Visualizations of Personal Online Da...

引用

27th International Conference on Information Visualisation (IV) / 19th International Conference Computer Graphics, Imaging and visualization (CGiV)

作者： Dutz, Marija Starcevic, Natasa Reynolds, Steven Lamarr Kohlhammer, Joern Fraunhofer IGD Darmstadt Germany Tech Univ Darmstadt Darmstadt Germany

ISBN: (纸本)9798350341614

As data becomes more and more pervasive in our daily lives, supporting people in getting visual insights into their data is an important challenge to address. However, as data visualization literacy is still low, a gap between designers' mental model and users is not uncommon. To best pick up users where they are, we propose to include the data mental models of users into the design process. In this paper, we present our investigations in this direction by incorporating user sketches of their idea about their personal data stored at online services as a basis of our designs. We present our design study on personal data visualization interfaces resulting in a set of user sketches for three types of user groups and in three visualization interfaces. Finally, we reflect on our learnings and identify pitfalls to support other researchers in applying similar approaches.

关键词： information visualization privacy design study

来源：评论

学校读者我要写书评

暂无评论

Web based-BigSync: A Grid Analytics Platform including Power System database Management 10

Web based-BigSync: A Grid Analytics Platform including Power...

引用

10th ieee International Conference on Power Systems, ICPS 2023

作者： Thoufeer, K.K. Kumar Jena, Manas Indian Institute of Technology Palakkad Department of Electrical Engineering Palakkad India

ISBN: (纸本)9798350318739

This paper discusses an offline engineering analytical software named BigSync (Big data Analytics for Synchrophasors) developed at the Indian Institute of Technology, Palakkad. The software solution enables the user to perform offline engineering analysis by leveraging various power system measurements that are stored in a relational database (RDBMS). The software package includes applications such as data visualization, statistical analysis, data de-noising and anomaly detection/cyberattack detection. This paper details the applicability of the developed software product in the energy management system (EMS) or control room of a modern power system. © 2023 ieee.

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：