Information Visualization Techniques Research Articles

Two-dimensional MoS2-based impedimetric electronic tongue for the discrimination of endocrine disrupting chemicals using machine learning

• E-tongue was built for multi-target prediction of endocrine-disrupting chemicals. • XGBoost machine learning model has shown high accuracy. • Feature selection using information visualization technique enhanced the prediction accuracy. In this paper, we report on machine learning to analyze the capacitance spectra obtained with an electronic tongue (e-tongue) and discriminate three endocrine-disrupting chemicals (EDC): bisphenol A, estrone, and 17- β -estradiol, and their mixtures. The e-tongue comprised seven sensing units made with interdigitated gold electrodes coated with layer-by-layer films of poly( o -methoxy aniline), poly(3-thiophene acetic acid), and molybdenum disulfide (MoS 2 ). The Multilayer Perceptron (MLP), Random Forest, and Extreme Gradient Boosting (XGBoost) models were applied for multi-target regression to predict the concentration of individual contaminants and their mixtures. These machine learning models were evaluated according to the root mean square error (RMSE) values. The best performance was achieved with XGBoost for which RMSE ranged from 0.19 to 3.37 for individual contaminants, from 0.12 to 0.25 for the mixtures, and from 0.34 to 3.46 for the entire dataset. The high performance was only possible with a multi-target regression strategy, including a feature selection procedure. In the latter, the data were plotted with the parallel coordinate technique, and the silhouette coefficient was calculated, which is a quantitative measure of the ability to distinguish similar samples in a dataset. The usefulness of the machine learning methods is demonstrated by noting that the data from mixtures of EDCs could not be distinguished using multidimensional projections. Also significant is that this combination of machine learning and information visualization methodology is entirely generic; it may be applied to analyze data from e-tongues and other sensing and biosensing devices in prediction tasks as demanding as in the discrimination of mixtures of EDCs at concentrations below nmol L −1 .

Social Media and Emergency Services: Information Sharing about Cases of Missing Persons in Rural Sweden

The aim of this article is to investigate the nature of information sharing in social media about missing persons by using social media data (mostly Twitter) and conventional media coverage (media archives), adopting a platial perspective to this geographical information. By focusing on the cases of three people gone missing, we report on ways in which civil society establishes relational networks through social media to collectively support local searches and share information in rural Sweden. Geographical information systems and visualization techniques underlie the methodology of this study. Findings show that the geography of information sharing in social media about a missing person is not random, revealing a globally dispersed pattern across the country. Information sharing contains more emotional than informational content, hitting a peak of spread after a person is found deceased. This finding indicates that the value of information shared by social media as a problem-solving resource might have so far been overestimated in the process of finding missing persons. In addition, tweets show indications that voluntary organizations constitute a valuable resource in rural contexts but not without impact on the existing networks of stakeholders delivering emergency services.

Detection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques

First genosensor for SARS-CoV-2 where multimodal detection principles can be employed, including image analysis based on machine learning.

RETRACTED: Design and research on automatic recognition system of sports dance movement based on computer vision and parallel computing

Professional team sports analyst periodic analysis to obtain strategic and tactical insights into the players and the team's behavior. Target motion analysis team, including systematic determination of hostile team weaknesses, and assess trained team performance and improvement potential. Team video analysis of the current investigation is usually based on workflow. Analysts can also use information visualization techniques to draw the trajectory of the ball and the players. Video analysis is usually a time-consuming process requiring analysts to remember and comment on the scene. In contrast, typically rely on visual data generally used abstract visual mapping model abstraction. They are no longer directly linked to the observed motion context but obtained from the raw tracking data. The proposal provides low-level functions and advanced motion recognition rate by another parallel motion analysis module used as input to evaluate the dancers' performance. Application of computer vision techniques to extract the appropriate data from the track of the video input. Besides, advance besides and motion analysis technology can be used to derive and regional analysis, event analysis and correlation analysis of team players' motion analysis measurements for football analysis. Our system is a visual mode that allows video and analysts to take advantage of both research forms. Some experts on the team sports analyst survey showed the effectiveness of this integrated approach.

A Decision Support System for Optimal Selection of Enterprise Information Security Preventative Actions

Types and complexity of information security related vulnerabilities are growing rapidly and present numerous challenges to the enterprises. One of the key challenges is to identify the optimal set of precautions with limited budget. Despite the fact that majority of enterprises have a budget constraint for installing and maintaining the protection systems, the majority of the previous work only focus on prioritization of security targets and do not consider the preventative actions and budget constraints. This article presents a decision support system (DSS) based on analytical hierarchical process and mixed integer programming techniques for optimal selection of enterprise information security preventative actions. The proposed approach enables maximizing the amount of risk prevented for a fixed amount of budget by identifying the optimal set of precautions. The new DSS also assists enterprise decision-makers in determining the minimum enterprise information security budget for a given level of risk. The main contribution of the paper is that it provides a risk management method to identify a multi-level threat model and the corresponding optimal combination of preventative actions for an enterprise while considering the budget constraints. The treemap information visualization technique is also integrated into the proposed method to improve information security related management decisions.

Визуализация учебной информации как средство активизации познавательной деятельности обучающихся

The article deals with information visualization techniques aimed at effective development of cognitive processes as parts of students' cognitive activity. The research featured the means of visualization of educational information that encourage the cognitive activity in students. The research objective was to identify, justify, and test the possibilities of using visualization tools for educational information. The cognitive activity is represented as a set of cognitive acts, namely explanation, understanding, and reflection. The authors believe that the process of interaction between participants in educational relations needs to be improved. The article focuses on the organization of the informational approach to training. It describes the stages of work with educational information: search for new material, its perception, processing, and application. The visualization technologies include mind maps and denotational graphs. Visualization technologies provide positive changes in students’ cognitive activity and develop cognitive motivation.

Differentia: Visualizing Incremental Game Design Changes

Small changes in the code and assets of a videogame can have drastic impacts on the player experience. The primary way to discover these impacts is with extensive human playtesting. However, the time and effort expended for playtesting is costly enough that it cannot be conducted after every incremental build of a game. We propose an information visualization technique that approximately reifies a game’s space of interactivity as a static image. Considering incremental changes to the game, our visualizations can suggest what has been effectively added, preserved, or removed from the space by those changes. These visual summary reports would ideally be used in the continuous integration (CI) software development process. We demonstrate a prototype implementation of this visualization on two commercial games, considering both minor and major design changes.

A systematic literature review of modern software visualization

We report on the state-of-the-art of software visualization. To ensure reproducibility, we adopted the Systematic Literature Review methodology. That is, we analyzed 1440 entries from IEEE Xplore and ACM Digital Library databases. We selected 105 relevant full papers published in 2013-2019, which we classified based on the aspect of the software system that is supported (i.e., structure, behavior, and evolution). For each paper, we extracted main dimensions that characterize software visualizations, such as software engineering tasks, roles of users, information visualization techniques, and media used to display visualizations. We provide researchers in the field an overview of the state-of-the-art in software visualization and highlight research opportunities. We also help developers to identify suitable visualizations for their particular context by matching software visualizations to development concerns and concrete details to obtain available visualization tools.

Planning, management and administration of HS contents with BIM and VR in construction: an implementation protocol

PurposeBuilding construction is considered a complex, dynamic and highly hazardous process, which embraces many factors that are potentially dangerous to workers. Many studies proved that the improvement of preventive and proactive measures – dynamically included in the building design, planning and construction – could reduce site accidents as well as increase the site productivity. In this context, process management models and information visualization techniques such as building information modeling (BIM) and virtual reality (VR) seem to be devoted to strongly contribute to the advancement of the current safety management practices. For these reasons, the presented contribution is based on the assumption that a more nuanced approach for construction worker's safety training is warranted and the authors propose a safety training protocol based on BIM-enabled VR activity simulations.Design/methodology/approachThe methodology comprised a safety training protocol based on BIM-enabled VR activity simulations. The protocol addresses three methodological issues: (1) Planning in terms of training typologies and related health and safety contents to be implemented in the VR construction site scenarios; (2) Management regarding the solution to integrate BIM and game technologies to deliver VR training experiences; (3) Administration in terms of definition of standardized rules to define a safety training schedule in a given construction project.FindingsThis work contributes to provide a standardized protocol for a viable integration of BIM and VR technologies for construction safety training in real projects.Practical implicationsThe VR training protocol was applied to a construction project based in Italy that served as case study for the development of the training sessions' contents and their implementation. This case demonstrated the feasibility of the protocol's implementation and pointed out the drawbacks and limitations on which further efforts need to be spent in order to take the proposed protocol from a prototypical stage to a maturity for its larger-scale adoption from the practitioners involved in construction safety training.Originality/valueThe research gives a contribution to reduce the currently existing knowledge gap regarding how BIM and VR can be simultaneously integrated in real projects for construction safety training by using standardized rules to be extensively reproduced in different construction projects. It uses a customized toolkit with a mobile smartphone solution to administer Safety Training Scenarios which increases its portability in construction site compared to PC-based VR solutions.

Visualization Analysis of Health Informatics Research from 2001 to 2018

To analyse the scientific outputs of health informatics research and explore its frontiers and hotspots, we retrieve publications on health informatics research from the Web of Science Core Collection between 2001 and 2018. Geographic information system mapping and visualization techniques were used for analysing the countries, journals, institutions, authors, references and keywords of publications. Timelines of co-citation clusters and keywords with citation bursts were created to study the emerging trends and hotspots. Six thousand seventy-seven publications were identified in health informatics research; the annual number of publications has increased rapidly over the last two decades. Keywords analysis indicated that ‘big data’ for health informatics and clinical informatics could become a research frontier. This study reveals the hot spots, structure and trend of health informatics research. Nevertheless, further research and cooperation are needed.

Graphing Model of Prediction Data for Occupational Incidents in Chemical And Gas Industries

Constant streaming of data for any instances at such high volumes provides insight in various organizations. Analyzing and identifying the pattern from the huge volumes of data has become difficult with its raw form of data. Visualization of information and visual data mining helps to deal with the flood of information. Constant streaming of data for any instances at such high volumes provides insight in various organizations. Analyzing and identifying the pattern from the huge volumes of data has become difficult with its raw form of data. Visualization of information and visual data mining helps to deal with the flood of information. Visual data representation takes the data and its results to all the stakeholders in a meaningful manner which comes out of the data mining process. Recent developments have brought a large number of information visualization techniques to explore the large data sets which can be converted into useful information and knowledge. Observations and inspection data gathered from chemical and gas industries are being piled up on a daily basis as raw data. Continuous analysis is a new term evolving in the industry which continuously performs on the streaming data to have real-time analysis and prediction on-live. In this paper, usage of the various graphing model as per the respective information obtained from the organization have been discussed and justified. It also describes the value addition in making the decisions by representations through graphs and charts for better understanding. Heatmap, Scattergram and customized Radar plots the analyzed data as in the required format to visualize the prediction done for the occupational incidents in chemical and gas industries. As a result of the graphing model, representation provides a higher level of confidence in the findings of the analysis. This fact takes a better visual representation technique and transforms them to provide better results with faster processing and understanding.

Depicting More Information in Enriched Squarified Treemaps with Layered Glyphs

The Treemap is one of the most relevant information visualization (InfoVis) techniques to support the analysis of large hierarchical data structures or data clusters. Despite that, Treemap still presents some challenges for data representation, such as the few options for visual data mappings and the inability to represent zero and negative values. Additionally, visualizing high dimensional data requires many hierarchies, which can impair data visualization. Thus, this paper proposes to add layered glyphs to Treemap’s items to mitigate these issues. Layered glyphs are composed of N partially visible layers, and each layer maps one data dimension to a visual variable. Since the area of the upper layers is always smaller than the bottom ones, the layers can be stacked to compose a multidimensional glyph. To validate this proposal, we conducted a user study to compare three scenarios of visual data mappings for Treemaps: only Glyphs (G), Glyphs and Hierarchy (GH), and only Hierarchy (H). Thirty-six volunteers with a background in InfoVis techniques, organized into three groups of twelve (one group per scenario), performed 8 InfoVis tasks using only one of the proposed scenarios. The results point that scenario GH presented the best accuracy while having a task-solving time similar to scenario H, which suggests that representing more data in Treemaps with layered glyphs enriched the Treemap visualization capabilities without impairing the data readability.

Synthetic Datasets Generator for Testing Information Visualization and Machine Learning Techniques and Tools

Data generators are applications that produce synthetic datasets, which are useful for testing data analytics applications, such as machine learning algorithms and information visualization techniques. Each data generator application has a different approach to generate data. Consequently, each one has functionality gaps that make it unsuitable for some tasks (e.g., lack of ways to create outliers and non-random noise). This paper presents a data generator application that aims to fill relevant gaps scattered across other applications, providing a flexible tool to assist researchers in exhaustively testing their techniques in more diverse ways. The proposed system allows users to define and compose known statistical distributions to produce the desired outcome, visualizing the behavior of the data in real-time to analyze if it has the characteristics needed for efficient testing. This paper presents in detail the tool functionalities and how to create datasets, as well as a usage scenario to illustrate the process of data creation.

An Application of Data Visualization in Electronic Health Records

An Application of Data Visualization in Electronic Health Records Asikur Rahman, Sherrie Komiak Abstract Recent development in Electronic Health Record (HER) systems has resulted in producing data at an unprecedented rate. The complex, growing, and high-dimensional big data available in EHRs represent great opportunities and challenges for researchers and practitioners in the healthcare section. To deal with such a challenge, we can take the advantage of advanced technology like information visualization techniques. This paper presents an outline of how we will apply different visualization techniques such as zooming, focusing, multiple coordinated views (MCVs), and details on demand etc. on the e-health data to visualize the medical and health information in a very interactive way. The proposed application can help the doctors and medical students with their decision making. Doctors or medical students will be able to visualize the information based on their needs which will improve the decision accuracy and decision time as well. Full Text: PDF DOI: 10.15640/jmise.v7n2a1

Visualization multi-instance data sets [Visualización de conjuntos de datos de múltiples instancias

In pattern recognition, multiple-instance learning algorithms have gained importance since they avoid that the user must delimit, the images individually in order to recognize the objects. This is an advantage over traditional learning algorithms since these considerably reduce the time required to prepare the data set. However, a disadvantage is that the resulting data sets are often complex, making it difficult to visualize them using traditional information visualization techniques. Thus, this work proposes a tool for the visualization and analysis of data sets of the multi-instance learning paradigm. The visualization proposal was evaluated using the expert criteria. In addition, different tests were carried out that show that a correct visualization can help to make decisions about the data set to improve the classification precision. © 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.

WMA: Wizard System Architecture for the execution of meta-analysis: A case study applied to verify the efficacy of fluquinconazole in the control of Asian soybean rust.

Meta-analysis is a probabilistic technique that combines results from several studies that approach the same topic and produce a result that sums up the whole. In the agricultural field, it is used to make empirical estimates of efficiency for the development of productivity and economic research on agriculture. Meta-analysis can be applied through software such as R, which is executed through commands, and produces results without providing user interactivity, nor does it reproduce a friendly and easy-to-understand interface. This paper presents the creation of a computer system, the WMA, which aims to simplify the execution of meta-analysis, providing a graphical interface and improves the display of the results through an interactive visualization using the Hierarchical Information Visualization Technique Bifocal Tree. For validation, the meta-analysis was applied in the agricultural area in a case study that grouped studies that used the fungicide fluquinconazole to combat the soybean rust disease, the results obtained through the application of the meta-analysis were analyzed using the WMA proposed tool.

Visual Data Mining for Multimedia Databases

With computers and communication dominating technology in different fields, the need to look for media-based information processing, MBIP –rather than data-based information processing, DBIP- is increasingly being felt and this is compounded by the explosive developments in cellular communication, which brought computing and interaction on the move. The basis is to explore possibilities of using conventional data-mining approaches with visualization and object orientation so that human interaction is easier. Data Mining involves exploring databases to try and discover data relationships which are not explicitly stored with in the databases. Traditional techniques involve statistical analysis, clustering and pattern matching. Many current efforts are underway to integrate visualization in to this process. Visual data mining is a novel approach to data mining. The aim is to combine traditional data mining algorithms with information visualization techniques to utilize the advantages of both approaches. The utilization of both automatic analysis methods and human perception/understanding promises better and more effective data exploration. Visualization is a key process in visual data mining. Here the focus is on the presentation of all aspect of multimedia objects, their identification, their analysis and relationships.

Social Media Analytics: Data Utilization of Social Media for Research

The amount of production data generated by social media opportunities that can be exploited by various parties, both government and private sectors to produce the information. Social media data can be used to know the behavior and public perception of the phenomenon or a particular event. To obtain and analyze social media data needed depth knowledge of Internet technology, social media, databases, data structures, information theory, data mining, machine learning, until the data and information visualization techniques. In this research, social media analysis on a particular topic and the development of prototype devices software used as a tool of social media data retrieval or retrieval of data applications. Social Media Analytics (SMA) aims to make the process of analysis and synthesis of social media data to produce information can be used by those in need. SMA process is done in three stages, namely: Capture, Understand and Present. This research is exploratorily focused on understanding the technology that became the basis of social media using various techniques exist and is already used in the study of social media analytic previously.

Data by Proxy - Material Traces as Autographic Visualizations.

Information visualization limits itself, per definition, to the domain of symbolic information. This paper discusses arguments why the field should also consider forms of data that are not symbolically encoded, including physical traces and material indicators. Continuing a provocation presented by Pat Hanrahan in his 2004 IEEE Vis capstone address, this paper compares physical traces to visualizations and describes the techniques and visual practices for producing, revealing, and interpreting them. By contrasting information visualization with a speculative counter model of autographic visualization, this paper examines the design principles for material data. Autographic visualization addresses limitations of information visualization, such as the inability to directly reflect the material circumstances of data generation. The comparison between the two models allows probing the epistemic assumptions behind information visualization and uncovers linkages with the rich history of scientific visualization and trace reading. The paper begins by discussing the gap between data visualizations and their corresponding phenomena and proceeds by investigating how material visualizations can bridge this gap. It contextualizes autographic visualization with paradigms such as data physicalization and indexical visualization and grounds it in the broader theoretical literature of semiotics, science and technology studies (STS), and the history of scientific representation. The main section of the paper proposes a foundational design vocabulary for autographic visualization and offers examples of how citizen scientists already use autographic principles in their displays, which seem to violate the canonical principles of information visualization but succeed at fulfilling other rhetorical purposes in evidence construction. The paper concludes with a discussion of the limitations of autographic visualization, a roadmap for the empirical investigation of trace perception, and thoughts about how information visualization and autographic visualization techniques can contribute to each other.

Information visualisation methods and techniques: State-of-the-art and future directions

Abstract Visualisation research explores techniques for conveying information in a meaningful way to allow users to make sense of data. This paper aims to review state-of-the-art information visualisation methods and techniques particularly for farmed data in defence simulations. It also discusses some of the key visualisation design challenges and outlines a conceptual framework for future research directions in information visualisation. It further presents a concept demonstrator that has been designed and developed to visualise joint force simulations for the purpose of showcasing some of the key concepts in the proposed information visualisation conceptual framework.