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Interpreting Distortions in Dimensionality Reduction by Superimposing Neighbourhood Graphs

Interpreting Distortions in Dimensionality Reduction by Supe...

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International conference on visualisation, VIS

作者： Benoît Colange Laurent Vuillon Sylvain Lespinats Denys Dutykh INES Univ. Grenoble Alpes Le Bourget du Lac France CNRS Univ. Grenoble Alpes Univ. Savoie Mont Blanc Chambéry France

ISBN: (纸本)9781728149424

To perform visual data exploration, many dimensionality reduction methods have been developed. These tools allow data analysts to represent multidimensional data in a 2D or 3D space, while preserving as much relevant information as possible. Yet, they cannot preserve all structures simultaneously and they induce some unavoidable distortions. Hence, many criteria have been introduced to evaluate a map's overall quality, mostly based on the preservation of neighbourhoods. Such global indicators are currently used to compare several maps, which helps to choose the most appropriate mapping method and its hyperparameters. However, those aggregated indicators tend to hide the local repartition of distortions. Thereby, they need to be supplemented by local evaluation to ensure correct interpretation of *** this paper, we describe a new method, called MING, for "Map Interpretation using Neighbourhood Graphs". It offers a graphical interpretation of pairs of map quality indicators, as well as local evaluation of the distortions. This is done by displaying on the map the nearest neighbours graphs computed in the data space and in the embedding. Shared and unshared edges exhibit reliable and unreliable neighbourhood information conveyed by the mapping. By this mean, analysts may determine whether proximity (or remoteness) of points on the map faithfully represents similarity (or dissimilarity) of original data, within the meaning of a chosen map quality criteria. We apply this approach to two pairs of widespread indicators: precision/recall and trustworthiness/continuity, chosen for their wide use in the community, which will allow an easy handling by users.

关键词： Distortion Reliability Image color analysis data visualization visualization Dimensionality reduction Three-dimensional displays

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A Study on EEG-NIRS Testing of Drug Users' Brain Function under visual Induction 2020

A Study on EEG-NIRS Testing of Drug Users' Brain Function un...

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Proceedings of the 2020 9th International conference on Computing and Pattern Recognition

作者： Banghua Yang Xuelin Gu Ding Xu Chengcheng Fan School of Mechanical and Electrical Engineering and Automation Shanghai University Shanghai China Shanghai Drug Rehabilitation Administration Bureau Shanghai China

ISBN: (纸本)9781450387835

Long-term drug abuse may change the brain function. In this paper, a new experimental paradigm combining EEG and NIRSIT is designed to explore target stimulus pictures-induced changes in electroencephalograms, as well as the changes in blood oxygen under near-infrared spectroscopy in drug users. The experiment divides into three stages. The first stage denotes the resting state. The task in the second stage includes induction by target stimulation pictures and neutral pictures. And in the third stage, the resting state pictures are all neutral pictures. The electroencephalograms and near-infrared data were collected in the three stages. Then an analysis was made of the ERP potential P300 of the electroencephalograms, the changes in hemoglobin concentration under near-infrared spectroscopy, and the channel time series. An analysis was made of the EEG and NIRSIT data on 120 people who were tested in a rehabilitation center according to the paradigm designed for the experiment. An analysis of the electroencephalograms in the second stage of the experiment shows that target stimulus pictures evoked more obvious P300 volatility in electroencephalograms than neutral pictures. Meanwhile, an analysis of the NIRSIT data shows that the concentration of oxyhemoglobin increased and the concentration of deoxyhemoglobin decreased. exploration of drug rehabilitation studies, laying a foundation for further predicting pathological changes in the human brain, as well as targeted rehabilitation.

关键词： analysis of brain function of drug addicts Drug addiction drug detoxification EEG and NIRSIT

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Immersive and collaborative data visualization using virtual reality platforms

Immersive and collaborative data visualization using virtual...

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IEEE International conference on Big data

作者： Ciro Donalek S. G. Djorgovski Alex Cioc Anwell Wang Jerry Zhang Elizabeth Lawler Stacy Yeh Ashish Mahabal Matthew Graham Andrew Drake Scott Davidoff Jeffrey S. Norris Giuseppe Longo California Institute of Technology Pasadena CA USA Jet Propulsion Laboratory Pasadena CA USA University Federico II Napoli Italy

Effective data visualization is a key part of the discovery process in the era of “big data”. It is the bridge between the quantitative content of the data and human intuition, and thus an essential component of the scientific path from data into knowledge and understanding. visualization is also essential in the data mining process, directing the choice of the applicable algorithms, and in helping to identify and remove bad data from the analysis. However, a high complexity or a high dimensionality of modern data sets represents a critical obstacle. How do we visualize interesting structures and patterns that may exist in hyper-dimensional data spaces? A better understanding of how we can perceive and interact with multidimensional information poses some deep questions in the field of cognition technology and human-computer interaction. To this effect, we are exploring the use of immersive virtual reality platforms for scientific data visualization, both as software and inexpensive commodity hardware. These potentially powerful and innovative tools for multi-dimensional data visualization can also provide an easy and natural path to a collaborative data visualization and exploration, where scientists can interact with their data and their colleagues in the same visual space. Immersion provides benefits beyond the traditional “desktop” visualization tools: it leads to a demonstrably better perception of a datascape geometry, more intuitive data understanding, and a better retention of the perceived relationships in the data.

关键词： data visualization Three-dimensional displays Collaboration visualization Big data Virtual reality Abstracts

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Prediction of Weather Radar Images via a Deep LSTM for Nowcasting

Prediction of Weather Radar Images via a Deep LSTM for Nowca...

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International Joint conference on Neural Networks (IJCNN)

作者： Guang Yao Zongxuan Liu Xufeng Guo Chaoshi Wei Xinfeng Li Zhihao Chen Em-Data AI Research Shanghai China China Eastern Region Air Traffic Management Bureau(ECATMB) Shanghai China

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Weather radar images provide critical information for mesoscale weather nowcasting which plays significant roles in a range of fields including civil aviation and navigation. Differed from traditional radar exploration methods, this paper presents a novel prediction model based on a deep recurrent neural network (DeepRNN). The approach converts the task of nowcasting to a task of image series prediction. We first design a new loss function that pays more attention to the changes of images in the input sequence. In the mean while, an image discriminator is incorporated into the model to improve the visual quality of predicted images. Furthermore, optical flow is explored to preserve the the motion information. The prediction results are evaluated based on widely used statistic scores. The experimental results show that the proposed model leads to significant improvement in tasks of 2 hours forecasting of radar echo.

关键词： Predictive models Radar imaging Task analysis Optical flow Meteorology

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exploration of visual Interaction Method for Metro Station Space Guidance System Based on Computer Aided Design

Exploration of Visual Interaction Method for Metro Station S...

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Evolutionary Algorithms and Soft Computing Techniques (EASCT), International conference on

作者： Yuwan Feng Kun Wu School Architeture & Urban Planning Shenzhen University Shenzhen Guangdong China

In recent years, the domain space interaction of subway stations based on computer-aided design has become a new trend. This article takes urban rail transit as an example to explain the importance of using computer to realize functions such as graphics and images. The system uses B/S structure to process graphic information, and stores the results in the server database for later analysis and feedback of changes in user needs. Through the simulation based on virtual sample technology, the effectiveness of the model and algorithm is verified. The visualization coefficient of the subway station domain space guidance system is between 0.7 and 0.9, the accuracy of landmarks is between 96% and 97%, the ease of use is between 84% and 89%, and the system operability is 80% above. Finally, in the computer environment, the interactive interface of the subway station domain space is designed to provide passengers with a better experience. This move means that the space interaction in the subway station has a higher technical level, and has played an important role in improving user satisfaction and convenience. In the research, it was found that the visual interaction method of the subway station spatial guidance system based on computer-aided design can be improved through the following aspects. These data may include passenger flow, train operation status, and safety information, and can be presented in the form of charts, heat maps, and animations. These research findings aim to continuously improve the spatial guidance system of subway station areas, enhance user experience and efficiency.

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Facilitating and Managing Machine Learning and data analysis Tasks in Big data Environments using Web and Microservice Technologies 19

Facilitating and Managing Machine Learning and Data Analysis...

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Proceedings of the 11th International conference on Management of Digital EcoSystems

作者： Shadi Shahoud Sonja Gunnarsdottir Hatem Khalloof Clemens Duepmeier Veit Hagenmeyer Karlsruhe Institute of Technology IAI Karlsruhe Germany

ISBN: (纸本)9781450362382

Driven by the great advance of machine learning in a wide range of application areas, the need for developing machine learning frameworks effectively as well as easily usable by novices increased dramatically. Furthermore, building machine learning models in the context of big data environments still represents a great challenge. In the present paper, we tackle these challenges by introducing a new generic framework for efficiently facilitating the training, testing, managing, storing, and retrieving of machine learning models in the context of big data. The framework makes use of a powerful big data software stack and a microservice architecture for a fully manageable and highly scalable solution. A highly configurable user interface is introduced giving the user the ability to easily train, test, and manage machine learning models. Moreover, it automatically indexes models and allows flexible exploration of them in the visual interface. The performance of the new framework is evaluated on state-of-the-arts machine learning algorithms: it is shown that storing and retrieving machine learning models as well as a respective acceptable low overhead demonstrate an efficient approach to facilitate machine learning in big data environments.

关键词： Big data Web-based Applications data Analytic Microservice Machine Learning

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Time-constrained dynamic semantic compression for video indexing and interactive searching

Time-constrained dynamic semantic compression for video inde...

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Tiecheng Liu J.R. Kender Department of Computer Science Columbia University NY USA

ISBN: (纸本)0769512720

We define and present a new model for semantic video compression and searching, and apply this model to several video genres, with special emphasis on instructional videos. In this model, a semantic distance based on the video genre is computed between adjacent frames in a dynamic video buffer of predetermined size, and redundant "unkey" frames leak from the buffer interior into a data structure "leakage history directed acyclic graph" (LHDAG) which records the relative importance of these frames. What exits the buffer forms a highly compressed video stream consisting of only the most semantically significant video frames, whereas the LHDAG permits efficient semantic exploration of the video interior. This novel hierarchical but context-sensitive data structure LHDAG permits the searching of the video at display rates that are proportional to visual significance, at levels of semantic density selectable by the user. The data structure is simple to create and query, and appears to be more psychologically plausible than more straightforward fixed sampling indexing schemes. We empirically display and mathematically analyze the relationships of the video buffer's leaking rate, buffer size, and exit delay, and demonstrate its performance on several extended videos. The flexibility of the method is indicated by its demonstration on two very different definitions of semantic significance: color similarity, and content ("ink pixel") similarity.

关键词： Video compression Indexing data structures Displays History Streaming media Psychology Sampling methods Performance analysis Delay

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Image retrieval on the Honeycomb Image Browser

Image retrieval on the Honeycomb Image Browser

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IEEE International conference on Image Processing

作者： William Plant Gerald Schaefer School of Engineering and Applied Science Aston University UK Department of Computer Science Loughborough University UK

Efficient and effective approaches of dealing with the vast amount of visual information available nowadays are highly sought after. This is particularly the case for image collections, both personal and commercial. Due to the magnitude of these ever expanding image repositories, annotation of all images images is infeasible, and search in such an image collection therefore becomes inherently difficult. Although content-based image retrieval techniques have shown much potential, such approaches also suffer from various problems making it difficult to adopt them in practice. In this paper, we follow a different approach, namely that of browsing image databases for image retrieval. In our Honeycomb Image Browser, large image databases are visualised on a hexagonal lattice with image thumbnails occupying hexagons. Arranged in a space filling manner, visually similar images are located close together enabling large image datasets to be navigated in a hierarchical manner. Various browsing tools are incorporated to allow for interactive exploration of the database. Experimental results confirm that our approach affords efficient image retrieval.

关键词： Image retrieval Browsers Image color analysis Navigation data visualization visualization

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Motive Design Creation 'Bakau Forest Themes - Muara Gembong' Bekasi to Promote Micro and Small Enterprises Products

Motive Design Creation 'Bakau Forest Themes - Muara Gembong'...

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International conference on Computing, Engineering, and Design (ICCED)

作者： Muhammad Imam Tobroni Hagung Kuntjara Sambada Wijasa Sambudi Hamali Visual Communication Design School of Design (SOD) Bina Nusantara University Jakarta Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665439978

This research aims to design a new batik motif design by taking inspiration from the mangrove forests of Muara Gembong, Bekasi Regency, and designing the application of the design motif/pattern design with the theme of the Muara Gembong mangrove forest to various forms of products. The study was conducted on the mangrove forests of Muara Gembong, Bekasi Regency, West Java Province, Indonesia. This research uses qualitative research methods, with descriptive research type. data were analyzed using descriptive exploratory analysis, consists of three stages: exploration, design, and embodiment. The Muara Gembong mangrove forest theme in the form of leaves, flowers, and roots is the basis for making a typical Bekasi motif. In addition, the application of pattern designs with the theme of the Muara Gembong mangrove forest to various forms of products, such as Paper Bags, Pillows, and T-Shirts.

关键词： Training Printing visualization Java conferences Force Prototypes

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Interactive visualization of high density streaming points with heat-map

Interactive visualization of high density streaming points w...

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International conference on Smart Computing (SMARTCOMP)

作者： Chenhui Li George Baciu Yu Han Department of Computing The Hong Kong Polytechnic University Hong Kong China The College of Mathematics and Computational Science Shenzhen University China

visualization of high density streaming points has become a challenge in information exploration. In this paper, we present a new pipeline for the interactive visualization of large points set. The pipeline is based on the idea that heat-map can overcome the overlapping problem in visualization of high density streaming points. Thus, we firstly define a regular streaming format for large point set which can be updated or changed continually. Based on streaming points, we use kernel density estimation to estimate the point distribution and visualize the density image. Perceptive and interactive features are also considered in our visualization. To our knowledge, our pipeline is the first work that focuses on perceptive visualization of high density streaming points. The main step of our pipeline is accelerated via GPU rendering in order to make scene of real-time interaction in visualization. We demonstrate the visual effectiveness of our pipeline on a geographical dataset of high-density streaming points.

关键词： data visualization Heating Image color analysis Pipelines Streaming media visualization

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