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检索条件"任意字段=2019 Conference on Visualization and Data Analysis, VDA 2019"

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Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning 22

Let there be a clock on the beach: Reducing Object Hallucina...

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22nd IEEE/CVF Winter conference on Applications of Computer Vision (WACV)

作者： Biten, Ali Furkan Gomez, Lluis Karatzas, Dimosthenis UAB Comp Vis Ctr Barcelona Spain

ISBN: (纸本)9781665409155

Explaining an image with missing or non-existent objects is known as object bias (hallucination) in image captioning. This behaviour is quite common in the state-of-the-art captioning models which is not desirable by humans. To decrease the object hallucination in captioning, we propose three simple yet efficient training augmentation method for sentences which requires no new training data or increase in the model size. By extensive analysis, we show that the proposed methods can significantly diminish our models' object bias on hallucination metrics. Moreover, we experimentally demonstrate that our methods decrease the dependency on the visual features. All of our code, configuration files and model weights are available online(1).

关键词： Measurement Training visualization Analytical models Computer vision Computational modeling Training data

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Machine Learning Techniques for Covid-19 Pandemic Updates for analysis, visualization, and Prediction System

Machine Learning Techniques for Covid-19 Pandemic Updates fo...

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International conference on Machine Learning and Big data Analytics, ICMLBDA 2022

作者： Radha, D. Ratna Kumari, P. Dhanalakshmi, M. Raghu Engineering College Department of Computer Science and Engineering Andhra Pradesh Visakhapatnam India

ISBN: (纸本)9783031151743

The spread of Covid-19 sickness 2019 (coronavirus) has turned into a worldwide danger, and the World Well-Being Association (WHO) pronounced coronavirus a worldwide pandemic on 28/10/2021. As of Oct 30, 2021, there were 244,897,472 affirmed cases and 4,970,435 passings from coronavirus around the world. The coronavirus pandemic has been incredibly influencing individuals’ lives and the world’s economy. The proposed forecast models have dissected, pictured, and anticipated the coronavirus cases internationally and country-wise. Information is assembled from various information sources—a few bona fide government sites. Time series estimation methods including AI models like straight relapse, backing vector relapse (SVM), polynomial relapse (PR), and Bayesian edge relapse strategies are conveyed to concentrate on the plausible climb in cases and soon. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Coronavirus

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A Web Portal for Real-Time data Quality analysis on the Brazilian Tuberculosis Research Network: A Case Study 23rd

A Web Portal for Real-Time Data Quality Analysis on the Braz...

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23rd International conference on Computational Science, ICCS 2023

作者： Cass Ã O, Victor Andrade, Filipe Costa Lima, Vin Í Cius Thomazini, Giovane Brand Ã O Miyoshi, Newton Shydeo de Andrade Mioto, Ana Clara Kritski, Afr Â Nio Alves, Domingos São Carlos School of Engineering University of São Paulo SP São Carlos Brazil Ribeirão Preto Medical School University of São Paulo SP Ribeirão Preto Brazil School of Medicine Federal University of Rio de Janeiro RJ Rio de Janeiro Brazil

ISBN: (纸本)9783031360237

Research projects with Tuberculosis clinical data generate large volumes of complex data, requiring sophisticated tools to create processing pipelines to extract meaningful insights. However, creating this type of tool is a complex and costly task, especially for researchers who need to gain experience with technology or statistical analysis. In this work, we present a web portal that can connect to any database, providing easy access to statistical analysis of the clinical data in real-time using charts, tables, or any other data visualization technique. The tool is user-friendly and customizable, reaching the project’s needs according to its particularities. The developed portal in this work was used as a use case for the research project developed by the Federal University of Rio de Janeiro (UFRJ) for the validation and cost of performance of the Line Probe Assay 1 and 2 (LPA) as a method of diagnosing resistant Tuberculosis in Brazilian’s reference centers. In the use case, the tool proved to be a valuable resource for researchers, bringing eﬃciency and eﬀectiveness in analyzing results for quick and correct clinical data interpretation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： data assimilation

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Effectively and Efficiently Supporting Visual Big data Analytics over Big Sequential data: An Innovative data Science Approach 22nd

Effectively and Efficiently Supporting Visual Big Data Analy...

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22nd International conference on Computational Science and its Applications (ICCSA)

作者： Cuzzocrea, Alfredo Sisara, Majid Abbasi Leung, Carson K. Wen, Yan Jiang, Fan Univ Calabria iDEA Lab Arcavacata Di Rende Italy Univ Lorraine LORIA Nancy France Univ Trieste Dept Engn Trieste Italy Univ Manitoba Dept Comp Sci Winnipeg MB Canada Univ Northern British Columbia Dept Comp Sci Prince George BC Canada

ISBN: (纸本)9783031104503;9783031104497

In the current era of big data, huge volumes of valuable data have been generated and collected at a rapid velocity from a wide variety of rich data sources. In recent years, the willingness of many government, researchers, and organizations are led by the initiates of open data to share their data and make them publicly accessible. Healthcare, disease, and epidemiological data, such as privacy-preserving statistics on patients who suffered from epidemic diseases such as Coronavirus disease 2019 (COVID-19), are examples of open big data. Analyzing these open big data can be for social good. For instance, people get a better understanding of the disease by analyzing and mining the disease statistics, which may inspire them to take part in preventing, detecting, controlling and combating the disease. Having a pictorial representation further enhances the understanding of the data and corresponding results for analysis and mining because a picture is worth a thousand words. Hence, in this paper, we present a visual data science solution for the visualization and visual analytics of big sequential data. The visualization and visual analytics of sequences of real-life COVID-19 epidemiological data illustrate the ideas. Through our solution, we enable users to visualize the COVID-19 epidemiological data over time. It also allows people to visually analyze the data and discover relationships among popular features associated with the COVID-19 cases. The effectiveness of our visual data science solution in enhancing user experience in the visualization and visual analytics of big sequential data are demonstrated by evaluation of these real-life sequential COVID-19 epidemiological data.

关键词： Information visualization Big data Sequences data science Visual data science data mining data analytics Visual analytics COVID-19

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Temporal Dynamics of Consumer Engagement in E-Commerce

Temporal Dynamics of Consumer Engagement in E-Commerce

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Computing for Sustainability and Intelligent Future (COMP-SIF), International conference on

作者： Gomathi Thiyagarajan Swathi. Y Department of Computer Applications CMR Institute of Technology Bengaluru India Department of Computer Science and Engineering Gopalan College of Engineering and Management Bengaluru India

ISBN: (数字)9798331538538

ISBN: (纸本)9798331538545

This paper explores into an indepth analysis of consumer behavior on an e-commerce platform, extending the study period to include November 2019 through February 2020. Looking at user interactions that come under the categories of views, carts, purchases, and removals from cart along with process discovery visualizations will help identify complex patterns of engagement, measure the impact of interface changes and quantify marketing intervention's successes. This research uses sophisticated data analytics through process mining to provide recommendations for improving the e-commerce journey through increased user satisfaction and better conversion rates.

关键词： Process mining data analysis Consumer behavior data visualization Electronic commerce Sustainable development

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Visualisation Tool to Support Fraud Detection 25

Visualisation Tool to Support Fraud Detection

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25th International conference Information Visualisation (IV) - AI and Visual Analytics and data Science

作者： Silva, Pedro Macas, Catarina Polisciuc, Evgheni Machado, Penousal Univ Coimbra Dept Informat Engn CISUC Coimbra Portugal

ISBN: (纸本)9781665438278

Automatic fraud detection and prevention are challenging problems that have attracted the attention of many researchers in academia and industry. Over the last few years, many improvements have been achieved, especially in predictive models based on Machine Learning. However, a considerable amount of these models only provide a prediction score and a short explanation which may not be enough to make informed decisions. This paper presents a visualization tool that aims to assist fraud analysts in making informed decisions and increase their effectiveness in the detection of fraud. To this end, we designed three visualisation models that apply state of the art techniques to support the analysis of fraudulent transactions. To demonstrate the analytic capabilities and benefits of the proposed tool, we discussed a real use case scenario and conducted user testing with real fraud analysts. Through the feedback from both studies, we were able to conclude that the tool is an asset to facilitate the detection of suspicious events as well to improve the analysis times of the fraud analysts' work process.

关键词： Information visualization data Analytics Fraud

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Decision-support system for the management of truck stays at seaports 27

Decision-support system for the management of truck stays at...

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27th International conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Martín-Lorenzo, Alba Expósito-Márquez, Airam López-Plata, Israel Expósito-Izquierdo, Christopher Castilla-Rodríguez, Iván Universidad de Las Palmas de Gran Canaria Calle Juan de Quesada 30 Las Palmas de Gran Canaria35001 Spain Universidad de La Laguna Camino San Francisco de Paula 19 San Cristóbal de La Laguna38200 Spain

This work presents a decision-support system for predictive analysis of truck arrivals, dwell times and possible congestion situations in seaport, through a methodology that encompasses machine learning algorithms, data visualization tools and discrete-event simulation models. This decision-support system makes it possible to have a detailed planning of the arrival and transit times of trucks in the port to predict land congestion events;and to know in advance the needs in relation to services or stopovers, and how long each truck will be in the port facilities. The system also allows for the planning and sizing of waiting areas according to expected arrivals and dwell times of trucks in port, at the same time that it optimizes port value spaces, and reduces unnecessary journeys and associated emissions, by evaluating the relationship between the sea side and the demand in land accesses. This will eventually help to improve coexistence and port-city integration between urban and heavy traffic. The system has been validated in the Port of Santander (Spain) with satisfactory results in terms of operational improvement. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： data visualization machine learning Seaport simulation model

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Key Technology Application Research for Intelligent Operation and Maintenance of Urban Bridge-Tunnel Clusters Traffic Based on BIM

Key Technology Application Research for Intelligent Operatio...

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2022 International conference on Smart Transportation and City Engineering, STCE 2022

作者： Liu, Dasheng Zhang, Peng Gao, Lijun Liu, Xun Gu, Ying Chongqing Quantong Engineering Construction Management Co. Ltd. Chongqing400015 China China Merchants Chongqing Highway Engineering Testing Center Co. Ltd. Chongqing400067 China Chongqing Zengjiayan Bridge Construction Management Co. Ltd. Chongqing400015 China

ISBN: (纸本)9781510660250

Based on the background of intelligent traffic operation and maintenance of urban bridge-tunnel clusters, this paper studies the key technology application of BIM technology, including digital technology of urban bridges-tunnel facilities, analysis and coding technology of component-level for bridge-tunnel, multi-service synergistic technology such as inspection, monitoring, and maintenance, multiple data fusion technology of static, semi-static, dynamic real-time, as well as key technologies such as data integration and visualization interaction. Taking the urban bridge-tunnel clusters traffic engineering in Chongqing as an application case, the engineering application of the research results is introduced. © 2022 SPIE.

关键词： data visualization

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A New Tool Based on GIS Technology for Massive Public Transport data 11th

A New Tool Based on GIS Technology for Massive Public Transp...

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11th International conference on Model and data Engineering (MEDI) / Workshop on Modeling, Verification and Testing of Dependable Critical Systems (DETECT)

作者： Brisaboa, Nieves R. de Bernardo, Guillermo Gutierrez-Asorey, Pablo Parama, Jose R. Rodeiro, Tirso V. Silva-Coira, Fernando Univ A Coruna Ctr Invest CITIC La Coruna Spain

ISBN: (纸本)9783031231186;9783031231193

In this work, we present the design of a novel geographic information tool for the analysis of public transportation data. The widespread integration of user traveler cards have enabled public transport operators to generate and store large amounts of data related to user movements within the transport network. However, these authorities are seldom equipped to efficiently exploit these data in order to produce a comprehensible analysis of the transport network usage. This is not only due to the sheer amount of data in need of processing, but also because most public transport operators only validate the travel card on boarding, whereas data referring to transfers and alightings are generally unavailable. Thus, the system we propose not only addresses efficient storage and exploitation of big datasets, but also the reconstruction of complete journeys by using a prediction algorithm to deduce the alighting stop for each boarding. Furthermore, we also provide the transport operators with easy-to-use means of visualizing and analyzing the data through a graphical interface.

关键词： Geographic information systems Compact data structures Big data visualization

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EXPHLOT: EXplainable Privacy Assessment for Human LOcation Trajectories 26th

EXPHLOT: EXplainable Privacy Assessment for Human LOcation ...

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26th International conference on Discovery Science, DS 2023

作者： Naretto, Francesca Pellungrini, Roberto Rinzivillo, Salvatore Fadda, Daniele University of Pisa Pisa Italy Scuola Normale Superiore Pisa Italy ISTI CNR Pisa Italy

ISBN: (纸本)9783031452741

Human mobility data play a crucial role in understanding mobility patterns and developing analytical services across various domains such as urban planning, transportation, and public health. However, due to the sensitive nature of this data, accurately identifying privacy risks is essential before deciding to release it to the public. Recent work has proposed the use of machine learning models for predicting privacy risk on raw mobility trajectories and the use of shap for risk explanation. However, applying shap to mobility data results in explanations that are of limited use both for privacy experts and end-users. In this work, we present a novel version of the Expert privacy risk prediction and explanation framework specifically tailored for human mobility data. We leverage state-of-the-art algorithms in time series classification, as Rocket and InceptionTime, to improve risk prediction while reducing computation time. Additionally, we address two key issues with shap explanation on mobility data: first, we devise an entropy-based mask to efficiently compute shap values for privacy risk in mobility data;second, we develop a module for interactive analysis and visualization of shap values over a map, empowering users with an intuitive understanding of shap values and privacy risk. © 2023, The Author(s).

关键词： data visualization

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