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

共 15616 条记录，以下是1621-1630 订阅

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Hardware Implementation of Double Pendulum Pseudo Random Number Generator

Hardware Implementation of Double Pendulum Pseudo Random Num...

引用

ieee International symposium on Embedded Multicore Socs (MCSoC)

作者： T. Hui Teo Maoyang Xiang Hen Rin Leao Keye Qian Jarrod Lim Tom Manuel Opalla Piccio Chua Min Jie Michelle Engineering Product Development Singapore University of Technology and Design Singapore Nano-Electronic Engineering and Design Singapore University of Technology and Design Singapore Chang Gung University Taiwan

ISBN: (数字)9798331530471

ISBN: (纸本)9798331530488

This paper presents a novel pseudo-random number generator (PRNG) implemented on an FPGA for encryption and data security applications. The system leverages environmental data captured by sensors to generate seeds, which are processed using a chaotic double pendulum algorithm. The generated random numbers exhibit strong randomness, demonstrated by a histogram analysis of over one million data points with no discernible pattern. However, the algorithm's complexity posed resource limitations on the FPGA, prompting partial offloading to an Arduino. Despite these challenges, the method provides a robust solution for secure random number generation, with potential improvements to be explored in future work.

关键词： visualization Statistical analysis Multicore processing Prototypes Generators Sensor systems Field programmable gate arrays Random number generation Testing Microphones

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Foot Traffic analysis Using Wi-Fi Sensor During the Tokyo 2020 Olympics and Paralympics 7

Foot Traffic Analysis Using Wi-Fi Sensor During the Tokyo 20...

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7th International Conference on Information Technology, InCIT 2023

作者： Traganmaturapot, Peerada Sonehara, Noboru Hiruma, Nobuharu Cooharojananone, Nagul Jirapongwanich, Jirakit Yodsakuntip, Kanat Atchariyachanvanich, Kanokwan Chulalongkorn University Faculty of Science Department of Mathematics and Computer Science Bangkok Thailand Institute for Policy Studies Tsuda University Tokyo Japan AREAPORTAL Inc Tokyo Japan King Mongkut's Institute of Technology School of Information Technology Ladkrabang Bangkok Thailand

ISBN: (纸本)9798350358698

Various real-world factors, such as time, weather, distance, environment, the COVID-19 pandemic, or even protests, can all impact human decision-making. However, restrictions and unexpected occurrences may also influence people's decisions regarding their path at any given time. These factors can lead to challenges in managing foot traffic at largescale events. In response to these challenges, this paper proposes a data-driven web-based foot traffic management supporting dashboard for large-scale events based on limited pedestrian count data, consisting of sensor name, latitude, longitude, MAC address, Datetime, and RSSI, collected by Wi-Fi sensors around the Sendagaya area during the Tokyo 2020 Olympics and Paralympics. The results confirmed that our proposed web-based dashboard contributes to human behavior understanding and decision-supporting policymaking for foot traffic management, which improves the design of spectator movement between transportation and venues in large-scale events. Furthermore, the dashboard is valuable from various perspectives, including preventing crowd crushing, redesigning areas to increase engagement in the shopping district, and improving traffic management. © 2023 ieee.

关键词： data visualization

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Human Blastocyst Image Generation Using Generative Adversarial Networks

Human Blastocyst Image Generation Using Generative Adversari...

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ieee International symposium on Biomedical Imaging

作者： Evangelos Tikas Lazaros Alexios Iliadis Sotirios Sotiroudis Achilles Boursianis Konstantinos-Iraklis D. Kokkinidis Achilleas Papatheodorou Sotirios K. Goudos ELEDIA@AUTH School of Physics Aristotle University of Thessaloniki Thessaloniki Greece Department of Applied Informatics University of Macedonia Thessaloniki Greece Embryolab Fertility Clinic Thessaloniki Greece Department of Electronics and Communication Engineering Bharath University Chennai India

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Several medical fields such as In Vitro Fertilization (IVF) suffer from limited databases d require augmentations, to be suitable for machine learning (ML) tasks such as classification. We test the use of various Generative Adversarial Network (GAN) architectures to tackle the problem of limited data by generating high-quality samples. We compare two GAN-based data augmentation techniques for a limited medical image database, utilizing synthetic images. A GAN can create synthetic images by learning to model a probability density function that can represent large data like images. Synthetic samples are then evaluated using metrics and visual evaluation with respect to the original "real" samples.

关键词： Measurement Training In vitro fertilization visualization Machine learning Probability density function Generative adversarial networks

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Structurally Consistent MRI Colorization using Cross-Modal Fusion Learning

Structurally Consistent MRI Colorization using Cross-Modal F...

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ieee International symposium on Biomedical Imaging

作者： Mayuri Mathur Anav Chaudhary Saurabh Kumar Gupta Ojaswa Sharma Indraprastha Institute of Information Technology Delhi India Purdue University USA All India Institute of Medical Sciences India

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Medical image colorization enhances the interpretability of imaging data by providing clearer anatomical insights. We aim to transfer diverse anatomical colors from Cryosection data to MRI scans while preserving MRI structural details. Our novel architecture achieves structurally consistent color transfer by fusing Cryosection segmentation semantics into the colorization process. This enables stable organ-level colorization in MRI images without requiring precise registration between the input MRI and Cryosection data or segmentation of the MRI itself. Additionally, we introduce a feature compression-and-activation mechanism that captures global organ-level information, suppresses noise, and facilitates accurate and realistic organ-specific colorization of MRI scans. Comparative experiments with state-of-the-art techniques demonstrate significant visual improvements, confirming the effectiveness of our method.

关键词： visualization Image segmentation Three-dimensional displays Image coding Accuracy Image color analysis Magnetic resonance imaging Semantics Colored noise Biomedical imaging

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Dash: A Bimodal data Exploration Tool for Interactive Text and visualizations

Dash: A Bimodal Data Exploration Tool for Interactive Text a...

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International Conference on Visualisation, VIS

作者： Dennis Bromley Vidya Setlur Tableau Research

ISBN: (数字)9798350354850

ISBN: (纸本)9798350354867

Integrating textual content, such as titles, annotations, and captions, with visualizations facilitates comprehension and takeaways during data exploration. Yet current tools often lack mechanisms for integrating meaningful long-form prose with visual data. This paper introduces DASH, a bimodal data exploration tool that supports integrating semantic levels into the interactive process of visualization and text-based analysis. DASH operationalizes a modified version of Lundgard et al.’s semantic hierarchy model that catego-rizes data descriptions into four levels ranging from basic encodings to high-level insights. By leveraging this structured semantic level framework and a large language model’s text generation capabilities, DASH enables the creation of data-driven narratives via drag-and-drop user interaction. Through a preliminary user evaluation, we discuss the utility of DASH’s text and chart integration capabilities when participants perform data exploration with the tool.

关键词： Annotations Visual analytics Semantics data visualization Encoding Distance measurement data models

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Pansharpening of PRISMA Products for Archaeological Prospection

Pansharpening of PRISMA Products for Archaeological Prospect...

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ieee International symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gregory Sech Giulio Poggi Marina Ljubenović Marco Fiorucci Arianna Traviglia Center for Cultural Heritage Technology Istituto Italiano di Tecnologia Venice Italy

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Hyperspectral data recorded from satellite platforms are often ill-suited for geo-archaeological prospection due to low spatial resolution. The established potential of hyperspectral data from airborne sensors in identifying archaeological features has, on the other side, generated increased interest in enhancing hyperspectral data to achieve higher spatial resolution. This improvement is crucial for detecting traces linked to sub-surface geo-archaeological features and can make satellite hyperspectral acquisitions more suitable for archaeological *** research assesses the usability of pansharpened PRISMA satellite products in geo-archaeological prospections. Three pan-sharpening methods (GSA, MTF- GLP and HySure) are compared quantitatively and qualitatively and tested over the archaeological landscape of Aquileia (Italy). The results suggest that the application of pansharpening techniques makes hyperspectral satellite imagery highly suitable, under certain conditions, to the identification of sub-surface archaeological features of small and large size.

关键词： Measurement visualization Satellites Pansharpening Soil Sensor phenomena and characterization Feature extraction

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On a Competition-Reciprocity Network of State-Owned Commercial Banks in Wuhan and Its Statistics analysis 11

On a Competition-Reciprocity Network of State-Owned Commerci...

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11th ieee data Driven Control and Learning Systems Conference, DDCLS 2022

作者： Han, Yao Liu, Jie Liu, Hongling Liu, Guidong Zhou, Hui School of Mathematics and Physics Science Wuhan Textile University Wuhan430073 China Research Centre of Nonlinear Science Wuhan Textile University Wuhan430073 China School of Management Science and Engineering Guangxi University of Finance and Economics Nanning530007 China School of Media and Communication Wuhan Textile University Wuhan430073 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

In recent years, the research on the layout and performance evaluation of urban financial services have been a hot and forward issue in the field of econometric research. With the rapid development of the economy and technology, the strength of domestic large commercial banks have been constantly enhanced, which plays an important role in supporting and guaranteeing the development of the local economy and the improvement of people's living standards. At the same time, the competition among commercial banks is becoming more and more fierce. Trying to find out the geographical distribution characteristics of the existing commercial banks in the core cities can not only help the urban financial function planning and management decision-makers arrange the layout of existing banks to serve the real economy and the public life;but also improve the performance of commercial banks. Based on the complex network analysis and visualization analysis method, by using the geographic information data visualization technology, firstly, this paper analyzes the main factors that affect the distribution of outlets of state-owned commercial banks in Wuhan. Our results show that the distribution of outlets of state-owned commercial banks in Wuhan has a significant positive correlation with the output value of the tertiary industry and the number of permanent residents. It also has a significant negative correlation with the output value of the secondary industry. At the same time, by using the data visualization method, we analyzed the geographical distribution characteristics of Wuhan state-owned commercial banks. Secondly, the network of competition reciprocity relationships among outlets was constructed. Finally, this paper gave a quantitative analysis of the digital characteristics of the competition reciprocity network among the existing state-owned commercial banks in Wuhan. The results of this paper can provide some valuable quantitative references for the scientific decision-ma

关键词： Complex networks

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Network Embedding for Cluster analysis 21

Network Embedding for Cluster Analysis

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21st ieee International symposium on Computational Intelligence and Informatics

作者： Makarov, Ilya Oborevich, Artem HSE Univ Moscow Russia Natl Univ Sci & Technol MISIS Moscow Russia Artificial Intelligence Res Inst Moscow Russia

ISBN: (纸本)9781665426848

Graph visualization is an effective and efficient way to discover complex inter-connections between elements within the nested structure of data. To accomplish this type of representation machine learning algorithms use a technique called graph embedding and node embedding in particular. However, in this paper, we will compare well-known techniques to yet largely under-explored setting of graph embedding named community embedding: embedding individual communities instead of individual nodes. This type of embedding can be especially useful in graph visualization and community detection tasks. Despite the fact that graph embedding and clustering tasks are separate, a good solution to the first one tends to have a correlation with the solution of the second problem and may have a positive impact if knowledge is transferred.

关键词： Geometric deep learning graph embedding node clustering community detection

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data Variability Study of Advanced 3D NAND Memory using Python

Data Variability Study of Advanced 3D NAND Memory using Pyth...

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ieee/SEMI Conference and Workshop on Advanced Semiconductor Manufacturing

作者： Moshe Agam Henok T Mebrahtu Himadri Dey Intel Foundry Development New Mexico

ISBN: (数字)9798350384550

ISBN: (纸本)9798350384567

The methodology for data analysis with large variability based on Python is discussed and demonstrated. As NAND memory transitioned from 2D to 3D, a significant new source of variability emerged due to the stacking of several hundred layers of memory cells on top of each other. This 3D construction demands a novel approach to efficient analysis that allows for a more general overview without sacrificing the details of individual memory cells. The authors explore how to achieve this by identifying sources of variation and systematically parsing and manipulating the data file into smaller files. This methodology enables straightforward visualization of parametric variability in relation to test and process conditions and facilitating the creation of accessible documentation for future reference. The use of Python provides an open-source and user-friendly interface that can be further customized to enhance consistency and reusability.

关键词： Three-dimensional displays data analysis databases Stacking Memory management data visualization Machine learning

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Visual Analytics of Air Pollutant Propagation Path and Pollution Source 23

Visual Analytics of Air Pollutant Propagation Path and Pollu...

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16th International symposium on Visual Information Communication and Interaction, VINCI 2023

作者： Hao, Yan Bi, Chongke Yang, Lu Qiu, Xiaobin Li, Yunlong Yu, Ce College of Intelligence and Computing Tianjin University Jinnan Tianjin China Tianjin University of Technology Xiqing Tianjin China Tianjin Key Laboratory for Oceanic Meteorology Heping Tianjin China National SuperComputer Center in Tianjin Binhaixinqu Tianjin China

ISBN: (纸本)9798400707513

Recently, controlling air pollution has become increasingly significant due to its impact on our health and daily lives. To prevent and control pollution, it is crucial to trace its source. Many researches have been developed for tracing the source of pollution. However, traditional methods using large-scale simulations need a large number of computation resources and time-consuming. In addition, traditional traceability algorithms do not consider topographic factors, which can cause a certain amount of errors. To resolve above problems, an interactive visual analytics system for pollutant traceability is proposed. In our method, instead of three-dimensional field data, only two-dimensional grid data is enough to track pollution sources in real time. Furthermore, our method can further improve precision through considering topographic factors, which are usually ignored by existing methods. Finally, the possible pollution sources are also identified in our method. This is achieved through analysis of changes in pollutant concentration and the distribution of man-made emission sources. In order to verify the effectiveness of this method, we propose a series of application examples to comprehensively analyze the sources of pollutants. © 2023 ACM.

关键词： visualization

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