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Process monitoring systems, e.g., systems based on photodiodes, could be used in laser-based powder bed fusion (PBF-LB/M) to measure various process parameters and process signatures to eventually allow for a local, detailed analysis of the produced parts. Here, simple statements only concerning the occurrence of defects in parts are sufficient in many cases, especially with respect to industrial application. Therefore, a pragmatic approach to rapidly infer the occurrence of defects and their types based on in situ data obtained by commercially available process monitoring systems is introduced. In this approach, a color distribution in form of a histogram is determined for each produced part using layer-wise screenshots of the visualized data provided by the monitoring software. Assessment of the histograms of AlSi10Mg samples, which were processed with different parameter combinations, revealed characteristics depending on the prevailing defect types. These characteristics enable the prediction of the occurring defect types without the necessity to apply conventional downstream testing methods, and thus, a straightforward separation of parts with good quality from defective components. Since the approach presented uses the data visualization of the monitoring software, it can be used even when direct access to the raw data is not provided by the machine manufacturer. [ABSTRACT FROM AUTHOR]

The participation of women in sports and the management of women's sports teams have gained significant attention in recent years, underscoring the need to understand the dynamics and organizational aspects of women's sports. However, there is a noticeable lack of comprehensive bibliometric analyses in this domain, hindering a thorough exploration of the existing literature and the identification of key trends and knowledge gaps. This study aims to address this gap by conducting a rigorous bibliometric analysis of sports management competencies in women's semi-professional teams in Europe. Using the VOSviewer software, advanced data analysis techniques, including citation and co-citation analysis, were employed to gain insights into the research landscape, influential authors, seminal papers, and key research trends. The results of the analysis revealed clusters of research topics related to women's semi-professional sports, including performance, gender, football, and sports. The findings of this analysis will contribute to the advancement and success of women's semi-professional teams by informing the development of tailored training programs, educational curricula, and professional initiatives for sports management roles. Ultimately, this study aims to enhance the understanding of sports management competencies in women's semi-professional teams and guide future research endeavors in this area. [ABSTRACT FROM AUTHOR]

This document offers guidance for reviewing educational case studies for the International Accounting Education (IAE) journal. It explains that reviewing a case study for IAE is different from reviewing other types of papers and outlines the three parts of a case study: the case, the case learning objectives and implementation guidance (CLOIG), and the teaching notes. The document provides specific guidance on assessing the case's contribution, execution problems, adoption by nonauthor faculty, and exposition. The goal of IAE is to publish well-developed cases that are useful to accounting instructors and students. Reviewers are encouraged to provide constructive criticism and suggestions for improvement, and faculty unfamiliar with educational cases are advised to read published cases to understand the format and content. [Extracted from the article]

Highly stretchable and robust strain sensors are rapidly emerging as promising candidates for a diverse of wearable electronics. The main challenge for the practical application of wearable electronics is the energy consumption and device aging. Energy consumption mainly depends on the conductivity of the sensor, and it is a key factor in determining device aging. Here, we design a liquid metal (LM)‐embedded hydrogel as a sensing material to overcome the barrier of energy consumption and device aging of wearable electronics. The sensing material simultaneously exhibits high conductivity (up to 22 S m−1), low elastic modulus (23 kPa), and ultrahigh stretchability (1500%) with excellent robustness (consistent performance against 12 000 mechanical cycling). A motion monitoring system is composed of intrinsically soft LM‐embedded hydrogel as sensing material, a microcontroller, signal‐processing circuits, Bluetooth transceiver, and self‐organizing map developed software for the visualization of multi‐dimensional data. This system integrating multiple functions including signal conditioning, processing, and wireless transmission achieves monitor hand gesture as well as sign‐to‐verbal translation. This approach provides an ideal strategy for deaf‐mute communicating with normal people and broadens the application of wearable electronics. [ABSTRACT FROM AUTHOR]

Radiation dose tracking is becoming very important due to the popularity of computerized tomography (CT) scans. One of the challenges of radiation dose tracking is that there are several variables that affect the dose from the patient side, machine side, and procedures side. Although some tracking software programs exists, they are based on static analysis and cause integration errors due to the heterogeneity of Hospital Information Systems (HISs) and prevent users from obtaining accurate answers to their questions. In this paper, a visual analytic approach is utilized to track radiation dose data from computed tomography (CT) through the use of Tableau data visualization software. The web solution is evaluated in real-life scenarios by domain experts. The results show that the visual analytics approach improves the tracking process, as users completed the tasks with a 100% success rate. The process increased user satisfaction and also provided invaluable insight into the analytical process. [ABSTRACT FROM AUTHOR]

Recent advances in training monitoring are centered on the statistical indicators of the concentric phase of the movement. However, those studies lack consideration of the integrity of the movement. Moreover, training performance evaluation needs valid data on the movement. Thus, this study presents a full-waveform resistance training monitoring system (FRTMS) as a whole-movement-process monitoring solution to acquire and analyze the full-waveform data of resistance training. The FRTMS includes a portable data acquisition device and a data processing and visualization software platform. The data acquisition device monitors the barbell's movement data. The software platform guides users through the acquisition of training parameters and provides feedback on the training result variables. To validate the FRTMS, we compared the simultaneous measurements of 30–90% 1RM of Smith squat lifts performed by 21 subjects with the FRTMS to similar measurements obtained with a previously validated three-dimensional motion capture system. Results showed that the FRTMS produced practically identical velocity outcomes, with a high Pearson's correlation coefficient, intraclass correlation coefficient, and coefficient of multiple correlations and a low root mean square error. We also studied the applications of the FRTMS in practical training by comparing the training results of a six-week experimental intervention with velocity-based training (VBT) and percentage-based training (PBT). The current findings suggest that the proposed monitoring system can provide reliable data for refining future training monitoring and analysis. [ABSTRACT FROM AUTHOR]

Background: As the number of tumor cases significantly increases, so does the quantity of tumor data. The mining and application of large-scale data have promoted the development of tumor big data. Among them, the visualization methods of tumor big data can well show the key information in a large volume of data and facilitate the human brain to receive information. Therefore, tumor big data visualization methods are a key part of the development of tumor big data. Process: This paper first summarizes the connotation, sources, characteristics, and applications of tumor big data, and expounds the current research status of tumor big data visualization at home and abroad. Then, this paper focuses on four mainstream visualization presentation methods of tumor big data, namely the visualization of tumor spatiotemporal data, the visualization of tumor hierarchy and network data, the visualization of tumor text data, and the visualization of multidimensional tumor data, and gives specific application scenarios. After this, the paper introduces the advantages, disadvantages, and scope of the use of five data visualization websites and software that can be easily obtained by readers. Finally, this paper analyzes the problems existing in tumor big data visualization, summarizes the visualization methods, and proposes the future of tumor big data visualization. [ABSTRACT FROM AUTHOR]

The practice of review writing is an essential component of postgraduate students' academic studies for graduation requirement and especially for those who are undergoing their postgraduate studies by theses by publication. However, very few studies have focused on review genres. In this review, the researchers would like to offer an overview of different types of review articles and identify the trend in the development of the review article genre. The researchers of this study employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. They identified the published articles specific to the review genres via a structured keyword search in Web of Science, Scopus, and Google Scholar (from the years 2019–2022). A mixed analysis approach (e.g., qualitative analysis combined with quantitative analysis) was conducted to further examine the selected articles using the data visualization software CiteSpace. The results showcased that there were currently a limited number of review types in social science disciplines. The researchers call for more effort to discover new models for writing review genres in the EFL/ESL context. This study also discusses the theoretical and practical implications. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Forensic Medicine / Fayixue Zazhi is the property of Journal of Forensic Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aims: This study aimed to conduct a bibliometric analysis of the relevant literature on the diagnosis of inflammatory bowel disease (IBD), and show its current status, hot spots, and development trends. Methods: The literature on IBD diagnosis was acquired from the Science Citation Index Expanded of the Web of Science Core Collection. Cooccurrence and cooperation relationship analysis of authors, institutions, countries, journals, references, and keywords in the literature were carried out through CiteSpace software and the Online Analysis platform of Literature Metrology. At the same time, the relevant knowledge maps were drawn, and the keywords cluster analysis and emergence analysis were performed. Results: 14,742 related articles were included, showing that the number of articles in this field has increased in recent years. The results showed that PEYRIN-BIROULET L from the University Hospital of Nancy-Brabois was the author with the most cumulative number of articles. The institution with the most articles was Mayo Clin, and the United States was far ahead in the article output and had a dominant role. Keywords analysis showed that there was a total of 818 keywords, which were mainly focused on the research of related diseases caused or coexisted by IBD, such as colorectal cancer and autoimmune diseases, and the diagnosis and treatment methods of IBD. Emerging analysis showed that future research hotspots and trends might be the treatment of IBD and precision medicine. Conclusion: This research was the first bibliometric analysis of publications in the field of IBD diagnosis using visualization software and data information mining, and obtained the current status, hotspots, and development of this field. The future research hotspot might be the precision medicine of IBD, and the mechanism needed to be explored in depth to provide a theoretical basis for its clinical application. [ABSTRACT FROM AUTHOR]

In recent years, studies have been conducted to quantify the relationship between microeconomic and macroeconomic development. Macroeconomics is the orientation of microeconomic development. Existing research hopes to quantify the relationship between macroeconomics and micro-firms, rather than just focusing on economic indicators. And some empirical studies try to use the relationship between them to discuss its usefulness for micro-firm decision-making. This article focuses on applying and developing aggregate earnings in connecting microenterprise earnings and macroeconomic development. To achieve this goal, this research did a comprehensive bibliometric analysis on macro-accounting on the two most influential databases, namely, Web of Science and Scopus. It used the information visualization software VOSviewer to draw knowledge maps to sort research lines. We also analyzed the research hotspots of macro-accounting in recent years according to the year scale and combined it with the neural network PSO-LSTM model to predict their future development. It turns out that the research on aggregate earnings related to economic growth has become a research hotspot in recent years. Scopus research and development potential is better than Web of Science in this field. [ABSTRACT FROM AUTHOR]

Objective To analyze the research status of forensic medicine in China from 2010 to 2019, obtain the development trend of forensic medicine and explore the hotspots and research frontiers. Methods The forensic medical academic papers published on China National Knowledge Infrastructure (CNKI) database from 2010 to 2019 were collected. CiteSpace 5.7. R1, an information visualization analysis software, was used to analyze publication organizations, authors, keywords, and other elements. Results The majority of the research institutions were universities, provincial and ministerial scientific research and forensic institutions. Forensic pathology was still an important branch of forensic medicine and a popular research direction. The"polymorphism"and"Y chromosome"had been the research hotspots in recent years."Medical damage"and"standard"were the most novel studies. Conclusion In order to provide scientific basis and research direction for forensic research, this paper analyzes the cooperation network, research hotspots and research innovation in forensic research. [ABSTRACT FROM AUTHOR]

Since 2006, the Bonneville Power Administration (BPA) Technology Innovation (TI) Office has applied roadmapping processes to help articulate the federal wholesale electric utility's technology research agenda. The TI Office team has evolved its tools, templates, and process steps considerably over the years in response to implementation challenges, shortcomings in deliverables derived from the process, and maturation opportunities enabled by data management and visualization software. Practioners within the TI Office have sustained their commitment to roadmapping during an era of significant evolution of the practice within industry and academia. The practice came out of product manufacturing environments in the 1960s, 1970s, and 1980s. Increasingly since the early 2000s, roadmapping has been applied outside this “traditional” realm, requiring trial, iteration, and customization of processes, tools, and deliverables to meet different requirements. The TI Office's use of roadmapping is one “nontraditional” variant because the agency is not in the business of generating profits by creating products in response to market demands. Instead, the TI Office has used roadmapping to communicate the agency's technology research, development, and demonstration agenda to the broader community—national laboratories, universities, manufacturers, etc.—so these external organizations can respond with proposals delivering products with the desired technology characteristics. These products, in turn, enable BPA to continue to fulfill its public service mission as an electric utility and government entity in providing safe, cost-effective, and reliable electricity throughout the Pacific Northwest region of the United States. [ABSTRACT FROM AUTHOR]

Background: This paper introduces DynamoVis version 1.0, an open-source software developed to design, record and export custom animations and multivariate visualizations from movement data, enabling visual exploration and communication of patterns capturing the associations between animals' movement and its affecting internal and external factors. Proper representation of these dependencies grounded on cartographic principles and intuitive visual forms can facilitate scientific discovery, decision-making, collaborations, and foster understanding of movement. Results: DynamoVis offers a visualization platform that is accessible and easily usable for scientists and general public without a need for prior experience with data visualization or programming. The intuitive design focuses on a simple interface to apply cartographic techniques, giving ecologists of all backgrounds the power to visualize and communicate complex movement patterns. Conclusions: DynamoVis 1.0 offers a flexible platform to quickly and easily visualize and animate animal tracks to uncover hidden patterns captured in the data, and explore the effects of internal and external factors on their movement path choices and motion capacities. Hence, DynamoVis can be used as a powerful communicative and hypothesis generation tool for scientific discovery and decision-making through visual reasoning. The visual products can be used as a research and pedagogical tool in movement ecology. [ABSTRACT FROM AUTHOR]

The Women of Shaheen Bagh as Muslim political actors foregrounded an alternative form of Indian nationalism defined by peaceful, artistic protest and leveraged their previous hyper-invisibility and rhetorical position as wives and mothers to advocate against the CAA-NRC. The Wire Twitter feed has an informative flowchart that explains the connection between the CAA and NRC. When the right-wing Hindu-nationalist Bharatiya Janata Party (BJP) of India passed the Citizenship Amendment Act (CAA) on December 11, 2019, and quickly followed up the legislative amendment with the implementation of the National Registry of Citizens (NRC), protests blossomed in India and across the globe.[6] As a feminist research collective based at Bowling Green State University (BGSU) - including Radhika Gajjala, Oladoyin Olubukola Abiona, and Olayombo Tejumade Raji-Oyelade, along with collaborators at other institutions - we were immediately struck by the images of a specific anti-CAA-NRC protest in Shaheen Bagh neighborhood of Delhi, a protest dominated by images of Muslim women - often mothers and grandmothers - peacefully protesting for weeks in streets. [Extracted from the article]

This paper aims to clarify the current status, hotspots, historical evolution and development trend of the research on funding and management of basic research in China. Firstly, 736 relevant papers indexed during 1992-2019 in the core journal database of China National Knowledge Infrastructure (CNKI) were analyzed in details. Using the information visualization software CiteSpaceV5.6.R3, the institutional cooperation co-occurrence map, author cooperation co-occurrence map, keyword co-occurrence map, and keyword timeline view maps were plotted through content mining. The results show that: the research institutions in the research field of basic research funding and management have formed three core cooperation networks, and the institutions in Beijing attract the most attention; most of the prolific and active authors choose teamwork over independent research; the research topics mainly fall into four aspects of basic research: input, subjects, results, and talents; the research hotspots are in line with policies and demands, and evolve through three stages: exploration and gradual progress, adjustment and development, and expansion and acceleration. The research results open up a new direction for relevant studies, and provide a reference for innovative parties to implement basic research. [ABSTRACT FROM AUTHOR]

In research articles, cities usually occur as topics (e.g., subjects or actors) or places of studies (e.g., sites, destinations, locations, or spaces). Investigation of more general patterns is rare because research usually focuses on individual cities. We use science mapping, based on Scopus data and Vosviewer visualization software, to examine city-related research across journals and disciplines (subject areas), and to assess how multiple city functions are reflected in journals. Comparable European Union capital cities (Berlin, Madrid, Rome, and Warsaw) serve as models. The patterns are remarkably similar regardless of the city. National and regional journals are the most common publication venues. Research takes place within three major disciplinary clusters: 1) the social sciences, and arts and humanities, 2) medicine, and 3) natural/technical sciences (environmental, earth and planetary, agricultural, and biological sciences). Medicine shows an early prevalence, and recently the social sciences have been strongly represented in these studies. Although the relationships are based on different journals, they are comparable for all cities and can be used to assess cities of similar size. This study was conducted just before the Covid-19 pandemic, and it can serve as a reference to identify research patterns before and after because the outbreak may bring about changes in future city-related research. [ABSTRACT FROM AUTHOR]

This study presents the results of the 3D microstructure, thermal conductivity, and heat flow in cement-based foams and examines their changes with a range of densities. Images were captured using X-ray micro computed tomography (micro-CT) imaging technique on cement-based foam samples prepared with densities of 400, 600, and 800 kg/m3. These images were later simulated and quantified using 3D data visualization and analysis software. Based on the analysis, the pore volume of 11000 µm3 was determined across the three densities, leading to optimal results. However, distinct pore diameters of 15 µm for 800 kg/m3, and 20 µm for 600 and 400 kg/m3 were found to be optimum. Most of the pores were spherical, with only 10% appearing elongated or fractured. In addition, a difference of 15% was observed between the 2D and 3D porosity results. Moreover, a difference of 5% was noticed between the experimentally measured thermal conductivity and the numerically predicted value and this variation was constant across the three cast densities. The 3D model showed that heat flows through the cement paste solids and with an increase in porosity this flow reduces. [ABSTRACT FROM AUTHOR]

Online, web-based cartography workflows use a dizzying variety of software suites, libraries, and programming languages. This proliferation of mapmaking technologies, often developed from a software engineering rather than a cartographic foundation, creates a series of challenges for cartography education, research, and practice. To address these challenges, we introduce a JavaScript-based open-source framework for web-based cartography and data visualization. It is built on top of existing open web standards that are already in intensive use for online mapmaking today, but provides a framework that is firmly based on cartographic and visualization theory rather than software engineering concepts. Specifically, we adopt concepts from Bertin's Semiology of Graphics and Wilkinson's Grammar of Graphics to create a language with a limited number of core concepts and verbs that are combined in a declarative style of "writing" visualizations. In this paper, we posit a series of design guidelines that have informed our approach, and discuss how we translate these tenets into a software implementation and framework with specific use cases and examples. We frame the development of the software and the discussion specifically in the context of the use of such tools in cartography education. With this framework, we hope to provide an example of a software for web-based data visualization that is in sync with cartographic theories and objectives. Such approaches allow for potentially greater cartographic flexibility and creativity, as well as easier adoption in cartography courses. [ABSTRACT FROM AUTHOR]

The article discusses a paper presented at the Association of Survey Computing's (ASC) Think Opportunity! Smart Technology for Cost-Conscious Times Conference that was held at Imperial College London in England on April 27, 2012 about the use of smart technology in market research. Topics include the management of unstructured datasets and text, policies for the use of mobile devices to take online surveys, and technology used for advanced data visualisation.

Effective data visualisation is a key part of the scientific process with complex geometric datasets. It is the bridge between the quantitative content of the data and human intuition. Immersion in virtual reality (VR) provides benefits beyond the traditional “desktop” visualization tools and it leads to a demonstrably better perception of dataspace geometry, more intuitive data understanding, and a better retention of the perceived relationships in the data. VR has a great potential for fusion research and in the analysis of its complex physics-based datasets. The work presented in this paper is one of the applications that have been implemented at UKAEA which combines shutdown dose calculations with a virtual reality model of the Joint European Tokamak (JET) in a new code called VORTEX (Virtual Operator RadiaTion EXposure). The shutdown dose calculations were performed for various time steps during the JET DTE2 campaign using the UKAEA code MCR2S which links MCNP and FISPACT-II using the rigorous two step method. The 3 Dimensional dose and activation data created by MCR2S is integrated into the game engine Unity using C# routines to create VORTEX. A virtual reality model has been created from JET CAD data combined with the 3 dimensional radiation and activation data to create of virtual model of the radiological environment after the DTE2 campaign. This model enables more precise planning of operational procedures by having the operator/planner walk around the virtual environment using a virtual reality headset such as the Oculus rift or the HTC vive. [ABSTRACT FROM AUTHOR]

With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA) has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC), an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets. [ABSTRACT FROM AUTHOR]

Background: During the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community. Results: We developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function--regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice and exhibit applications for metagenomics, metaproteomics and metabolomics samples. Conclusion: MetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis. Moreover, since the automatically chosen two-group sample test is verified to be outperformed, MetaComp is friendly to users without adequate statistical training. These improvements are aiming to overcome the new challenges under big data era for all meta-omics data. [ABSTRACT FROM AUTHOR]

With the increasing number of matches day by day, it has become difficult to manage or extract useful information from the available data of all the matches. The paper presents a data visualization and prediction tool in which an open-source, distributed, and non-relational database, HBase is utilized to keep the data related to IPL (Indian Premier League) cricket matches and players. This data is then used for visualizing the past performance of players’ performance. Additionally, the data is used to predict the outcome of a match through various machine learning approaches. The proposed tool can prove beneficial for the team managements in the player auctions for selecting the right team. [ABSTRACT FROM AUTHOR]

Geospatial data visualization systems have been predominantly through applications that are installed and run in a desktop environment. Over the last decade, with the advent of web technologies and its adoption by Geospatial community, the server-client model for data handling, data rendering and visualization respectively has been the most prevalent approach in Web-GIS. While the client devices have become functionally more powerful over the recent years, the above model has largely ignored it and is still in a mode of serverdominant computing paradigm. In this paper, an attempt has been made to develop and demonstrate LSIViewer - a simple, easy-to-use and robust online geospatial data visualisation system for the user's own data that harness the client's capabilities for data rendering and user-interactive styling, with a reduced load on the server. The developed system can support multiple geospatial vector formats and can be integrated with other web-based systems like WMS, WFS, etc. The technology stack used to build this system is Node.js on the server side and HTML5 Canvas and JavaScript on the client side. Various tests run on a range of vector datasets, upto 35MB, showed that the time taken to render the vector data using LSIViewer is comparable to a desktop GIS application, QGIS, over an identical system. [ABSTRACT FROM AUTHOR]

Microarray is a general scheme to identify differentially expressed genes for a target concept and can be used for biology. The output is presented utilizing a heatmap that biologists analyze in related terms of gene ontology to determine the characteristics of differentially expressed genes. In this paper, we propose an integrated visualization tool for a heatmap and gene ontology graph. Most of the previous methods used were static and none of them were combined. The proposed visualization tool integrates these and provides users with an interactive management ability. Users can easily identify and confirm related terms of gene ontology for given differentially expressed genes. Further, the proposed tool visualizes the connections between genes on the heatmap and gene ontology graph. Therefore, the proposed tool can be used for precision healthcare. [ABSTRACT FROM AUTHOR]

R (R Development Core Team, 2011) is a powerful tool to analyze statistical data. In recent years R has gained popularity because the software is free and open source. However, evaluators and researchers do not exclusively use quantitative data. It is possible to perform qualitative analysis in R. Using data from a case study exploring a family psychoeducation recovery course, this article provides users a tutorial on how to perform a qualitative analysis and data visualization using R. [ABSTRACT FROM AUTHOR]

The paper presents application of Kroki tool to creation of executable specification of CERIF standard. Kroki (fr. croquis – sketch) is an open-source tool that is being developed in order to foster development agility and better communication among team members with different specialties. It can be used for creating of specification of data-driven applications using two different notations (UML based and mockup based) and for generating application over the specification. This paper presents usage of Kroki tool for visualization and further development of CERIF data model, as well as using of Kroki for generating a prototype of CRIS system over CERIF data model. CERIF 1.5 specification was taken from euroCRIS web site and entered into Kroki tool. More than 280 CERIF classes are divided into 31 packages, in order to make CERIF model easier to read and comprehend. Thanks to its mockup and lightweight UML editor, Kroki enables each user, with or without background in information technologies, to understand and change CERIF specification. [ABSTRACT FROM AUTHOR]

Due to their trans-modal affordances, techniques mainly used for the production of glitch art such as pixel sorting and data-bending are potential data visualization tools that can be effectively adapted to the representation of abstract relations. To demonstrate this assertion, we present a method intended for the visualization of data through these techniques. The method presented here consists in sorting the composite pixels of greyscale images to make evident relationships between pixels that otherwise would be impossible to perceive. Here, we use this method to arrange an array of images in a very specific order, but this is only one of the potential applications that this method could have. [ABSTRACT FROM AUTHOR]

This paper choosed the documents on subject of knowledge network of industrial cluster included in Web of Science from 2004 to 2014 as object of research and used an information visualization analysis software CiteSpace to make visual analysis of data information in this field. Then it introduced some key indicators of knowledge map, such as frequency, centrality of knot points, burst term and so on to show the distribution of main research countries and institutions, research hotspots and research fronts in different periods. [ABSTRACT FROM AUTHOR]