Graphical Visualization Tools Research Articles

Behavioural determinants of the healthcare providers in Ukraine: Focus on competition context

The development of the healthcare system is an important task for every country, given that long-term economic and social development is absolutely impossible without a healthy nation. Therefore, improving public health and ensuring that the maximum number of people have access to quality healthcare services is one of the state's strategic priorities. In this regard, the authors of the paper set a goal to establish how the reform of the healthcare system in Ukraine has led to changes in the behavioural determinants of healthcare providers and recipients in the domestic healthcare market. The paper uses such research methods as comparison, visualization, graphical data visualization tools, and statistical methods of data analysis. The study revealed that Ukrainian citizens got a chance to freely choose their physicians by signing declarations with them, which led to increased competition among physicians and other doctors and healthcare facilities; at the same time, the number of declarations signed with private healthcare facilities increased significantly. Furthermore, the developed econometric model allows us to identify statistically significant relationships between the amount of state funding and lifestyle and environmental indicators, which will allow us to improve the mechanisms and amount of funding in the sector, improving the health of the nation in the new competitive environment.

Checking Data Quality of Longitudinal Household Travel Survey Data

Ensuring data quality of household travel survey data is often tedious and, thus, time-consuming. To speed up the process of data-checking and to gain an in-depth understanding of the data, data visualization is a practical, fundamental tool. Since 1994, data visualization has been used in the German Mobility Panel (MOP) data-checking process. This paper presents two graphical visualization tools developed for the MOP. Both tools speed up the data checks and ensure high consistency in identifying erroneous data. This paper describes and discusses how the tools provide a continuous data quality assessment.

A novel life cycle assessment and life cycle costing framework for carbon fibre-reinforced composite materials in the aviation industry

PurposeCarbon fibre-reinforced composite materials offer superior mechanical properties and lower weight than conventional metal products. However, relatively, little is known about the environmental impacts and economic costs associated with composite products displacing conventional metal products. The purpose of this study is to develop an integrated life cycle assessment and life cycle costing framework for composite materials in the aviation industry.MethodsAn integrated life cycle assessment (LCA) and life cycle costing (LCC) framework has been developed. The displacement of a conventional aluminium door for an aircraft by a composite door is presented as an example of the use of this framework. A graphical visualisation tool is proposed to model the integrated environmental and economic performances of this displacement. LCA and LCC models for composite applications are developed accordingly. The environmental hotspots are identified, and the sensitivity of the environmental impact results to the different composite waste treatment routes is performed. Subsequently, the research suggests a learning curve to analyse the unit price for competitive mass production. Sensitivity analysis and Monte Carlo simulation have been applied to demonstrate the cost result changes caused by data uncertainty.ResultsEnergy consumption was the hotspot, and the choice of composite waste treatment routes had a negligible effect on the LCA outcomes. Concerning the costs, the most significant cost contribution for the unit door production was labour. The future door production cost was decreased by about 29% based on the learning curve theory. The uncertainties associated with the variables could lead to variations in the production cost of up to about 16%. The comparison between the two doors shows that the composite door had higher potential environmental impacts and cost compared to the conventional aluminium door during the production stage. However, the composite door would have better environmental and financial performance if a weight reduction of 47% was achieved in future designs.ConclusionsThe proposed framework and relevant analysis models were applied through a case study in the aerospace industry, creating a site-specific database for the community to support material selection and product development. The graphical tool was proved to be useful in representing a graphical visualisation comparison based on the integration of the LCA and LCC results of potential modifications to the composite door against the reference door, providing understandable information to the decision-makers.

Customization and flexible manufacturing capacity using a graphical method applied on a configurable multi-agent system

• Concurrent use of pluggable resources for quick and agile balance of the manufacturing capacity. • Easy adoption to customized products by utilizing in-house knowledge of the manufacturer. • Graphical tool for easy design and visualization of sequential and parallel goals and requirements. • Plug & Produce robot cell controlled by a configurable multi-agent system verified on a wooden house wall pre-manufacturing case. This article proposes a Plug & Produce and goal-oriented configurable multi-agent system that admits adding and removing resources to balance the manufacturing capacity without doing any digital reconfiguration or reprogramming. To handle that a new part-agent strategy is developed and described. Goals are central in designing autonomous multi-agent systems, possibilities to execute goals in parallel are desirable when the process requirements admit concurrent use of resources. Also, a standardized graphical method, the sequence of goals chart, is proposed to define and visualize parallel and sequential goals independently of available resources. Premanufacturing of wooden houses belongs to one of many manufacturing industries that claim flexible automation systems due to the high degree of customized products and a fluctuating market. A physical Plug & Produce robot-based workstation was built up to verify the flexibility in altering capacity and adoption to product modifications of a house wall section. Further, the simplicity of modifying the proposed configurable multi-agent system was compared to more traditionally designed systems and plain multi-agent systems with superior results. The flexibility is built into the proposed system by default as a part of the concept, simple enough to be handled by existing in-house knowledge within manufacturing companies.

Visual Preoperative Risk Depiction Tools for Shared Decision-making: A Pilot Study from the Surgeon's Perspective.

Complications for reduction mammoplasty and skin grafting in a burns setting were sourced from the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator, the American Society of Plastic Surgeons website, peer-reviewed literature, and available clinical data. Pre- and postoperative patient satisfaction data were collected from the published literature on Breast-Q patient-reported outcomes for reduction mammoplasty. Everyday risk comparisons were collected from a general online database search. Three distinct risk depiction tools (spiral, tile, and scatter plot) were developed in the Microsoft Office Suite. Anonymous REDCap surveys were sent to healthcare practitioners for feedback. Twenty-six survey results were collected. Twenty-four respondents (92%) agreed these graphics would be useful for SDM discussions. Nineteen respondents (73%) either agreed or strongly agreed that these graphics depicted risk in a meaningful way. Fifteen respondents (58%) indicated they would use these graphics in daily practice. The majority of respondents preferred the spiral design (58%). Areas for improvement included design simplification and written explanations to accompany graphics. Feedback from the survey was incorporated into the spiral design. Risk visualization tools meaningfully depict surgical risks to improve communication in SDM. This study proposes a tool that can be adapted for many surgical procedures.

3D inversion of vertical gravity gradient with multiple graphics processing units based on matrix compression

Among single-component inversions, vertical gravity gradient data have been proven to be sufficient to obtain reasonable density distribution. However, the increasing numbers of observations and model parameters inevitably produce a large-scale sensitivity matrix, causing problems such as large memory occupation and slow computations in the inversion. Aiming at solving these long-standing problems, we have introduced a matrix compression technique to reduce memory occupation and constructed a hybrid parallel algorithm for accelerating focusing inversion. We develop the source codes and the design pattern for the proposed algorithm using C language with open multiprocessing and compute unified device architecture for further improving algorithm feasibility and reusability. A graphical user interface and visualization tools also are developed using Python. In the tests with synthetic data produced by numerical simulation and real data from Vinton Dome, it is verified that the inversion can produce an accurate result of density values and object location. The performance analysis is conducted using different scales of data. The speedup increases with the increasing number of graphics processing units (GPUs) and model parameters, proving that the proposed parallel algorithm is scalable. We compare this algorithm with others without matrix compression to demonstrate how the compressed sensitivity matrix storing and accessing method influences inversion performance. More specifically, for an inversion with 100 × 100 × 20 cells, the average speed is approximately 6 s per iteration, with a maximum speedup of 36.94. Our algorithm has a short running time and high multiple-GPU parallel efficiency. Hence, the hybrid parallel algorithm is more powerful at implementing large-scale data calculations and could be used for solving computing problems in mass data inversions.

Curating 62 Years of Walnut Gulch Experimental Watershed Data: Improving the Quality of Long-Term Rainfall and Runoff Datasets

The curation of hydrologic data includes quality control, documentation, database development, and provisions for public access. This article describes the development of new quality control procedures for experimental watersheds like the Walnut Gulch Experimental Watersheds (WGEW). WGEW is a 149 km2 watershed outdoor hydrologic laboratory equipped with a dense network of hydro-climatic instruments since the 1950s. To improve data accuracy from the constantly growing instrumentation networks in numerous experimental watersheds, we developed five new QAQC tools based on fundamental hydrologic principles. The tools include visual analysis of interpolated rainfall maps and evaluating temporal, spatial, and quantitative relationships between paired rainfall-runoff events, including runoff lag time, runoff coefficients, multiple regression, and association methods. The methods identified questionable rainfall and runoff observations in the WGEW database that were not usually captured by the existing QAQC procedures. The new tools were evaluated and confirmed using existing metadata, paper charts, and graphical visualization tools. It was found that 13% of the days (n = 780) with rainfall and 7% of the runoff events sampled had errors. Omitting these events improved the quality and reliability of the WGEW dataset for hydrologic modeling and analyses. This indicated the effectiveness of application of conventional hydrologic relations to improve the QAQC strategy for experimental watershed datasets.

Visualizing and Interacting with a System‐Centric Enterprise Digital Thread

AbstractAs large enterprises embrace Digital Transformation, it is obvious that merely scanning paper documents to digital form is inadequate to achieve their broader goals. These must be transformed into more granular data that are version controlled, configuration managed and connected – i.e., a digital thread.As a digital thread begins to span the product lifecycle, its complexity increases exponentially with the number of lifecycle phases and application areas that it encompasses. This quickly becomes intractable, given the “normal” approach to finding and presenting data in PLM platforms.The goal of creating these enormous and rapidly growing networks of data is not just to archive the data. They must empower the product teams to be productive and to make the most effective use of this dynamic data network to meet the rapidly changing goals of the corporation as it reacts to the market's needs. This requires various graphical query and visualization tools.

Monitoring of the Water Eutrophycation Process in Red Lake, from Harghita County, Romania

The main problem of freshwater lakes in the world, eutrophycation represents the over-enrichment of water by nutrients (nitrogen, phosphorus) and has emerged as one of the leading causes of surface water quality impairment. It is a rapidly growing environmental crisis, and worldwide, the number of coastal areas impacted by eutrophycation phenomenon stands at over 500. This important pollution process sets off a chain reaction in the ecosystem, starting with an overabundance of algae and other aquatic plants, excess which eventually decompose, producing large amounts of carbon dioxide. This paper is the result of researches located in Romania, performed over a period of eight years (2012-2019), in the area of a representative natural dam lake of the country - Red Lake, from Harghita County. Our researches aimed the quality parameters of the Red Lake water, the eutrophication process indicators, and their over time evolution. In order to predict the evolution of the studied pollution phenomenon in time, we used the software package “Surface-water Modeling System SMS 13.0” – the complete surface water solution, which was approached for the first time by Aquaveo. This software provides a comprehensive graphical environment for numerical modeling of eutrophycation, and tools for site characterization, model conceptualization and graphical visualization.

PUMAA: A Platform for Accessible Microbiome Analysis in the Undergraduate Classroom.

Improvements in high-throughput sequencing makes targeted amplicon analysis an ideal method for the study of human and environmental microbiomes by undergraduates. Multiple bioinformatics programs are available to process and interpret raw microbial diversity datasets, and the choice of programs to use in curricula is largely determined by student learning goals. Many of the most commonly used microbiome bioinformatics platforms offer end-to-end data processing and data analysis using a command line interface (CLI), but the downside for novice microbiome researchers is the steep learning curve often required. Alternatively, some sequencing providers include processing of raw data and taxonomy assignments as part of their pipelines. This, when coupled with available web-based or graphical user interface (GUI) analysis and visualization tools, eliminates the need for students or instructors to have extensive CLI experience. However, lack of universal data formats can make integration of these tools challenging. For example, tools for upstream and downstream analyses frequently use multiple different data formats which then require writing custom scripts or hours of manual work to make the files compatible. Here, we describe a microbial ecology bioinformatics curriculum that focuses on data analysis, visualization, and statistical reasoning by taking advantage of existing web-based and GUI tools. We created the Program for Unifying Microbiome Analysis Applications (PUMAA), which solves the problem of inconsistent files by formatting the output files from several raw data processing programs to seamlessly transition to a suite of GUI programs for analysis and visualization of microbiome taxonomic and inferred functional profiles. Additionally, we created a series of tutorials to accompany each of the microbiome analysis curricular modules. From pre- and post-course surveys, students in this curriculum self-reported conceptual and confidence gains in bioinformatics and data analysis skills. Students also demonstrated gains in biologically relevant statistical reasoning based on rubric-guided evaluations of open-ended survey questions and the Statistical Reasoning in Biology Concept Inventory. The PUMAA program and associated analysis tutorials enable students and researchers with no computational experience to effectively analyze real microbiome datasets to investigate real-world research questions.

Hydria: An Online Data Lake for Multi-Faceted Analytics in the Cultural Heritage Domain

Advancements in cultural informatics have significantly influenced the way we perceive, analyze, communicate and understand culture. New data sources, such as social media, digitized cultural content, and Internet of Things (IoT) devices, have allowed us to enrich and customize the cultural experience, but at the same time have created an avalanche of new data that needs to be stored and appropriately managed in order to be of value. Although data management plays a central role in driving forward the cultural heritage domain, the solutions applied so far are fragmented, physically distributed, require specialized IT knowledge to deploy, and entail significant IT experience to operate even for trivial tasks. In this work, we present Hydria, an online data lake that allows users without any IT background to harvest, store, organize, analyze and share heterogeneous, multi-faceted cultural heritage data. Hydria provides a zero-administration, zero-cost, integrated framework that enables researchers, museum curators and other stakeholders within the cultural heritage domain to easily (i) deploy data acquisition services (like social media scrapers, focused web crawlers, dataset imports, questionnaire forms), (ii) design and manage versatile customizable data stores, (iii) share whole datasets or horizontal/vertical data shards with other stakeholders, (iv) search, filter and analyze data via an expressive yet simple-to-use graphical query engine and visualization tools, and (v) perform user management and access control operations on the stored data. To the best of our knowledge, this is the first solution in the literature that focuses on collecting, managing, analyzing, and sharing diverse, multi-faceted data in the cultural heritage domain and targets users without an IT background.

The Mnemiopsis Genome Project Portal: integrating new gene expression resources and improving data visualization.

Following the completion of the genome sequencing and gene prediction of Mnemiopsis leidyi, a lobate ctenophore that is native to the coastal waters of the western Atlantic Ocean, we developed and implemented the Mnemiopsis Genome Project Portal (MGP Portal), a comprehensive Web-based data portal for navigating the genome sequence and gene annotations. In the years following the first release of the MGP Portal, it has become evident that the inclusion of data from significant published studies on Mnemiopsis has been critical to its adoption as the centralized resource for this emerging model organism. With this most recent update, the Portal has significantly expanded to include in situ images, temporal developmental expression profiles and single-cell expression data. Recent enhancements also include implementations of an updated BLAST interface, new graphical visualization tools and updates to gene pages that integrate all new data types. Database URL: https://research.nhgri.nih.gov/mnemiopsis/.

A Numerical Tool for Simultaneous Targeting and Design of Mass Exchange Networks

Design of cost-effective Mass Exchange Networks (MENs) that involves mass integration can help to minimize the amount of mass separating agent (MSA) purchased, waste MSA generated by industries, reduce operating costs and mitigate environmental issues associated with MSA disposal. Design of MENs can be done using graphical and numerical methods, as well as using mathematical modelling. This work describes a new approach for simultaneous targeting and design of MENs in which both targeting and network design stage can be solved in a single template, in order to overcome the limitation of graphical tools such as MENs Composite Curves (CCs) and Grid Diagram. CCs cannot completely map individual rich and lean process streams, or process and utility streams. On the other hand, the numerical technique known as Composition Interval Table (CIT) failed to show individual rich and lean stream mass cascades and cannot be used for MENs design. The newly developed numerical approach in this paper employs the Segregated Composition Interval Table (SECIT) to simultaneously locate mass pinch point, determine the minimum utility targets and perform SECIT Mass Allocation (SMA) that can be used to visualize in SECIT Network Diagram (SND).This work can be applied in industries to minimize liquid waste and reduce environmental pollution A case study is presented to demonstrate the validity and advantages of the proposed approach. This paper also shows that SECIT and SND can be a vital combination of numerical and graphical visualization tools for targeting and design of complex MENs.

Efficiency increasing by development of district heating systems operational modes using graphical analysis

The tasks of analyzing, developing and justifying of the district heating systems (DHS) operation modes arise at different stages of their life cycle. The article provides a brief description of the tasks, steps and methods for calculating and analyzing DHS modes, which are implementing as subtasks of the "ANGARA-HN" software. Special attention is paying to the automation of analysis processes. The developed computational and graphical software tools for parameters analyzing of the DHS operating modes consists of the means: analyzing of the initial information, calculating the values of the mode parameters and analyzing results of the calculation. Various tools allow you to visualize the distribution of selected parameters values on the graphical city plan, highlight bottlenecks, building pressure distribution graphs. The developed software designed to automate the workplaces of regimes group engineers at operational enterprises or for designer workers, when developing and justifying development schemes for urban DHS. Tools for analysis and graphical visualization significantly increase the efficiency of work by reducing the time of analysis, development and justification of operating conditions, as well as improve the quality of the results.

Structural, spectroscopic properties and theoretical studies of (E)-1-(4-Bromophenyl)-3-(2,3,4-trimethoxyphenyl)prop-2-en-1-one as a potential anti-oxidant agent

ABSTRACTThe new chalcone compound namely (E)-1-(4-Bromophenyl)-3-(2,3,4-trimethoxyphenyl)prop-2-en-1-one (C18H17BrO4) is crystallized in the monoclinic crystal system of P21/c space group. The unit cell dimensions are: a = 8.0753 (10) Å, b = 21.873 (3) Å, c = 9.3362 (12) Å, α = 90°, β = 99.369 (2), γ = 90° and Z = 4. The single crystal was grown using slow evaporation solution growth technique. The newly synthesized compound was characterized by using IR, 1H- and 13C-NMR, UV-Vis and single crystal X-ray diffraction analyses. Quantum chemical method of Density Functional Theory (DFT) with B3LYP/6-311++G(d,p) has been employed to study the structural and spectral properties of the compound. The electronic absorption spectrum was calculated using the time dependent functional theory (TDDFT) method. The most stable conformer of the title chalcone is identified from the computational results. Hirshfeld surface analysis with fingerprint plots has been used as a graphical tool for visualization and understanding of intermolecular interactions. Intermolecular C‒H····O interaction observed stabilize the crystal structure, forming an infinite one dimensional column. The effect of this intermolecular interaction in the solid state can be seen in the difference between the experimental and the theoretically optimized geometrical parameters. The crystal is transparent in the entire visible region and absorptive in the UV region. Information about the size, shape, charge density distribution and site of chemical reactivity of the molecule has been obtained by mapping electron potential (MEP). The other molecular properties like charge transfer are explain using Mulliken population analysis. The antioxidant test indicated that the 2,3,4-trimethoxy substitution on the bromide chalcone to be one of the favorable modification to enhance its metal chelating activity.

GSAR: Bioconductor package for Gene Set analysis in R

BackgroundGene set analysis (in a form of functionally related genes or pathways) has become the method of choice for analyzing omics data in general and gene expression data in particular. There are many statistical methods that either summarize gene-level statistics for a gene set or apply a multivariate statistic that accounts for intergene correlations. Most available methods detect complex departures from the null hypothesis but lack the ability to identify the specific alternative hypothesis that rejects the null.ResultsGSAR (Gene Set Analysis in R) is an open-source R/Bioconductor software package for gene set analysis (GSA). It implements self-contained multivariate non-parametric statistical methods testing a complex null hypothesis against specific alternatives, such as differences in mean (shift), variance (scale), or net correlation structure. The package also provides a graphical visualization tool, based on the union of two minimum spanning trees, for correlation networks to examine the change in the correlation structures of a gene set between two conditions and highlight influential genes (hubs).ConclusionsPackage GSAR provides a set of multivariate non-parametric statistical methods that test a complex null hypothesis against specific alternatives. The methods in package GSAR are applicable to any type of omics data that can be represented in a matrix format. The package, with detailed instructions and examples, is freely available under the GPL (> = 2) license from the Bioconductor web site.

Automated generation of dynamics-based runtime certificates for high-level control

This paper addresses the problem of synthesizing controllers for reactive missions carried out by dynamical systems operating in environments of known physical geometry but consisting of uncontrolled elements that the system must react to at execution time. Such problems have value in semi-structured industrial automation settings, especially those in which robots must behave collaboratively yet safely with their human counterparts. The proposed synthesis framework addresses cases where there exists no satisfying controller for the mission, given the dynamical system and the environment's assumed behaviors. We introduce an approach that leverages information about an abstraction of the dynamical system to automatically generate a concise set of revisions to such specifications. We provide a graphical visualization tool as a design aid, allowing the revisions to be conveyed to the user interactively and added to the specification at the user's discretion. Any accepted statements become certificates that, if satisfied at runtime, provide guarantees for the current mission on the given dynamics. Our approach is cast into a general framework that works with various discrete representations (i.e. abstractions) of the system dynamics. We present case studies that illustrate application of our approach to controller synthesis for two example robotic missions employing different abstractions of the system.

A LEARNING EXERCISE USING SIMPLE AND REAL-TIME VISUALIZATION TOOL TO COUNTER MISCONCEPTIONS ABOUT ORBITALS AND QUANTUM NUMBERS

Misconception is one of the most widely researched topics in science education, including chemical education. This research aims to apply simple graphical visualization tool named Winplot for a learning exercise activity and explore its potency to counter misconceptions about orbitals and quantum numbers. Misconceptions that were countered in this research are the existence of orbitals in atoms and the relationship of magnetic quantum numbers to orbital orientation. This quasi experimental research using pre-test-post-test control group design was conducted to 43 first-year undergraduate students as control class and 45 as experimental class of chemical education at the University of Lampung. The students’ pre-existing concepts were analyzed using a pre-test instrument and explored further using in-depth interview. Then, after implementing a learning exercise activity, the conceptual changes were analyzed using a post-test instrument. The results showed that students in experimental class had significant conceptual changes compared to control class. Applying this computer-based strategy is highly recommended to guide students in understanding chemical concepts, especially the topics of orbitals and quantum numbers. Key words: learning exercise, first-year undergraduate, computer-based learning, misconceptions, quantum chemistry.

Piper diagram – A novel visualisation tool for process design

In process synthesis, it is often useful to have generic design tools to allow process designers to assess various important aspects of chemical processes. In this work, a novel graphical visualisation tool, i.e. Piper diagram is proposed to trace the changes of composition of the process streams, while establishing relationship that contributes to various strategies for process design. This tool is generic in nature, hence is applicable to all processes and various process aspects that meet the objectives of the designer. Two case studies on the production of cinnamaldehyde and butanal are used to demonstrate the novel approach, with safety, environmental and economic aspects being investigated using the Piper diagram.

A systematic technique for cost-effective CO2 emission reduction in process plants

There has been growing interests to reduce the environmental impact caused by greenhouse gas emissions from process plants through various energy conservation strategies. CO2 emissions are closely linked to energy generation, conversion, transmission and utilisation. Various studies on the design of energy-efficient processes, optimal mix of renewable energy and hybrid power system are driven to reduce reliance on fossil fuel as well as CO2 emissions reduction. This paper presents a systematic technique in the form of graphical visualisation tool for cost-effective CO2 emission reduction strategies in industry. The methodology is performed in four steps. The first step involves calculating the energy consumption of a process plant. This is followed by identification of potential strategies to reduce CO2 emissions using the CO2 management hierarchy as a guide. In the third step, the development of “Investment” versus “CO2 Reduction” (ICO2) plot is constructed to measure the optimal CO2 emission reductions achieved from the implementation of possible CO2 reduction strategies. The Systematic Hierarchical Approach for Resilient Process Screening (Wan Alwi and Manan in AIChE J 11:3981–3988, 2006) method is used in the fourth step via substitution or partial implementation of the various CO2 reduction options in order to meet the cost-effective emission reduction within the desired investment limit or payback period (PP). An illustrative case study on a palm oil refinery plant has been used to demonstrate the implementation of the method in reduction of CO2 emissions. The developed graphical tool provides an insight-based approach for systematic CO2 emission reduction in the palm oil refinery considering both heat and power energy sources. Result shows that 31.2 % reduction in CO2 emissions can be achieved with an investment of USD 38,212 and PP of 10 months based on the present energy prices in Malaysia.