Visual Graphical User Interface Research Articles

Graphical Visualisation of the MCNP Mesh Tally File

This paper presents an updated version of the MTV3D (Mesh Tally Visualization in 3D) program with Windows graphical user interface for visualization of the MCNP-based mesh tally files. Several improvements over the previous program version are addressing better figure export functionality ("Save as" option), switching between linear and logarithmic values on axes, dynamic figure scaling in active window, inversion of relative errors from “max” to “min” values, etc. MCNP is a well known and widely used general purpose Monte Carlo computer code for neutron, photon and electron transport simulation through arbitrary three-dimensional configurations. An important feature of the MCNP code is a graphical display of the simulation model using auxiliary program, such as X-window server, which is useful for geometry error-checking during model setup and visualisation of Monte Carlo results from a mesh tally file (i.e. meshtal file) over a structured xyz mesh. Such inspection of the model is useful for the end user, providing an insight of the Monte Carlo convergence process in a phase space and effectiveness of the selected variance reduction parameters in shielding calculations. Basic features and functionalities of the updated MTV3D program are presented on some selected hybrid-shielding problems involving ADVANTG3.0.3 and MCNP6.1.1b codes.

OntoloViz: a GUI for interactive visualization of ranked disease or drug lists using the MeSH and ATC ontologies.

Structured vocabularies for drugs and diseases represent, besides their primary use for annotating scientific literature or scientific information in general, a valuable resource for visualizing aggregated information. The Medical Subject Headings (MeSH) and Anatomical Therapeutic Chemical (ATC) ontologies are widely used structured vocabularies for diseases and drugs, respectively. Their hierarchical tree-like structure can be used as a basis for creating intuitive visual displays for specific diseases and drugs within their higher-order classifications. Such displays are helpful means to contextualize diseases and drugs in various settings such as in drug repositioning. However, there are few tools that can harness the potential of these structured ontologies to create informative visual representations without extensive programming and data processing skills. We have developed OntoloViz, a Graphical User Interface (GUI) for visualizing annotated lists of drugs or diseases in the context of their MeSH or ATC ontologies in an intuitively interpretable sunburst layout. Minimum input is a list of disease or drug names. Users in addition have the option to specify numerical parameters for the input lists to enhance the visualization, e.g. to visualize term frequencies. The GUI allows values to be propagated upwards in the respective ontology tree structure thus facilitating exploration of gene and drug lists. We present two use cases for OntoloViz, namely (i) a graphical representation of clinically tested drugs for coronavirus disease (COVID-19) based on ATC Classification and (ii) a graphical representation of literature annotation of human diseases on the MeSH ontology. The OntoloViz package can be retrieved from PyPi. The source code along with test data, template, and documentations are available at GitHub (https://github.com/Delta4AI/OntoloViz).

Sales Prediction using Linear Regression

This sales prediction uses linear regression to predict sales in the future based on past data available and provides GUI(Graphical User Interface) for better visualization to the user. It predicts the number of sales for the number of advertisements through media like TV, newspaper, and social media. It is trained with the previous data. Sales forecasting is particularly important in industries because of the limited shelf-life of many of the goods, which leads to a loss of income in both shortage and surplus situations. Too many orders lead to a shortage of products and still too few orders lead to a lack of opportunity.

Automated detection of vascular remodeling in tumor-draining lymph nodes by the deep-learning tool HEV-finder.

Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor‐draining lymph nodes (TDLNs). Dilation of the high endothelial venules (HEVs) within TDLNs has been observed in several types of cancer. We recently demonstrated that it is a premetastatic effect that can be linked to tumor invasiveness in breast cancer. Manual visual assessment of changes in vascular morphology is a tedious and difficult task, limiting high‐throughput analysis. Here we present a fully automated approach for detection and classification of HEV dilation. By using 12,524 manually classified HEVs, we trained a deep‐learning model and created a graphical user interface for visualization of the results. The tool, named the HEV‐finder, selectively analyses HEV dilation in specific regions of the lymph nodes. We evaluated the HEV‐finder's ability to detect and classify HEV dilation in different types of breast cancer compared to manual annotations. Our results constitute a successful example of large‐scale, fully automated, and user‐independent, image‐based quantitative assessment of vascular remodeling in human pathology and lay the ground for future exploration of HEV dilation in TDLNs as a biomarker. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

ProThermDB: thermodynamic database for proteins and mutants revisited after 15 years.

ProThermDB is an updated version of the thermodynamic database for proteins and mutants (ProTherm), which has ∼31 500 data on protein stability, an increase of 84% from the previous version. It contains several thermodynamic parameters such as melting temperature, free energy obtained with thermal and denaturant denaturation, enthalpy change and heat capacity change along with experimental methods and conditions, sequence, structure and literature information. Besides, the current version of the database includes about 120 000 thermodynamic data obtained for different organisms and cell lines, which are determined by recent high throughput proteomics techniques using whole-cell approaches. In addition, we provided a graphical interface for visualization of mutations at sequence and structure levels. ProThermDB is cross-linked with other relevant databases, PDB, UniProt, PubMed etc. It is freely available at https://web.iitm.ac.in/bioinfo2/prothermdb/index.html without any login requirements. It is implemented in Python, HTML and JavaScript, and supports the latest versions of major browsers, such as Firefox, Chrome and Safari.

A novel syntax-aware automatic graphics code generation with attention-based deep neural network

Recent advances in deep learning have made it possible to automatically translate graphical user interface (GUI) into code by an encoder-decoder framework. This framework generally uses deep convolutional neural network (CNN) to extract image features, which are then translated into hundreds of code tokens by a code generator based on a recurrent neural network (RNN). However, there are two challenges in the implementation of this framework: one is how to make full use of the information contained in the GUI and domain specified language (DSL) code, the other is how to make generated DSL code conform to syntax rules. To fully leverage the information in GUI and DSL code, we first propose a model named HGui2Code that integrates visual attention-enabled GUI features (extracted by CNN) with DSL attention-enabled semantic features (extracted by LSTM). Besides, we propose SGui2Code, a novel model that makes use of a ON-LSTM network to generate DSL code that is correct in syntax. HGui2code pays more attention to semantic information, while SGui2code focuses on grammar rules. Extensive experimental results show that our models outperform state-of-the-art methods on the web dataset, yielding 5.5% higher accuracy with the HGui2Code model and 1.5% using the SGui2Code model respectively. Although our models do not have huge boost on IOS and Android dataset, DSL code generated by our models are very close to the layout of components in corresponding GUI.

ECOGEMS: efficient compression and retrieve of SNP data of 2058 rice accessions with integer sparse matrices.

We proposed to store large-scale genotype data as integer sparse matrices, which consumed much fewer computing resources for storage and analysis than traditional approaches. In addition, the raw genotype data could be readily recovered from integer sparse matrices. Utilizing this approach, we stored the genotype data of 1612 Asian cultivated rice accessions and 446 Asian wild rice accessions across 8584244 SNP sites in the ECOGEMS database with 310 MB of disk usage. Graphical interface for visualization, analysis and download of SNP data were implemented in ECOGEMS, which made it a valuable resource for rice functional genomic studies. The code and data of ECOGEMS are freely available at https://github.com/venyao/ECOGEMS. ECOGEMS is deployed at http://ecogems.ncpgr.cn and http://150.109.59.144: 3838/ECOGEMS/ for online use. Supplementary data are available at Bioinformatics online.

MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra.

The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. Graphical abstract ᅟ.

Visual Basic GUI for an Improved of M&V Framework Considering Risk Assessment

This paper presents a development of Visual Basic based Graphical User Interface (GUI) for an improved of Measurement and Verification Protocol (M&V) Whole Facility framework to quantify an investment in energy savings considering risks. Monte Carlo simulations are presented to assess the risks of an Energy Conservation Measure (ECM) project. The proposed M&V framework produces a continuous range of savings and rate of return of the investment with associated probabilities instead of a single value assessment without margin of error. The GUI was tested for a commercial building using three different variables that are affecting the energy use: 1) Cooling Degree Days (CDD), 2) Number of Working Days (NWD) and 3) Multi-Variable that combining CDD and NWD. From the findings, it shows that the proposed Visual Basic based GUI of M&V with Monte Carlo simulation provides a more comprehensive overview of energy savings investment in a building.

PGG.Population: a database for understanding the genomic diversity and genetic ancestry of human populations.

There are a growing number of studies focusing on delineating genetic variations that are associated with complex human traits and diseases due to recent advances in next-generation sequencing technologies. However, identifying and prioritizing disease-associated causal variants relies on understanding the distribution of genetic variations within and among populations. The PGG.Population database documents 7122 genomes representing 356 global populations from 107 countries and provides essential information for researchers to understand human genomic diversity and genetic ancestry. These data and information can facilitate the design of research studies and the interpretation of results of both evolutionary and medical studies involving human populations. The database is carefully maintained and constantly updated when new data are available. We included miscellaneous functions and a user-friendly graphical interface for visualization of genomic diversity, population relationships (genetic affinity), ancestral makeup, footprints of natural selection, and population history etc. Moreover, PGG.Population provides a useful feature for users to analyze data and visualize results in a dynamic style via online illustration. The long-term ambition of the PGG.Population, together with the joint efforts from other researchers who contribute their data to our database, is to create a comprehensive depository of geographic and ethnic variation of human genome, as well as a platform bringing influence on future practitioners of medicine and clinical investigators. PGG.Population is available at https://www.pggpopulation.org.

APEX_SCOPE: A graphical user interface for visualization of multi-modal data in inter-disciplinary studies.

In multi-disciplinary studies, different forms of data are often collected for analysis. For example, APEX, a study on the automated prediction of extubation readiness in extremely preterm infants, collects clinical parameters and cardiorespiratory signals. A variety of cardiorespiratory metrics are computed from these signals and used to assign a cardiorespiratory pattern at each time. In such a situation, exploratory analysis requires a visualization tool capable of displaying these different types of acquired and computed signals in an integrated environment. Thus, we developed APEX_SCOPE, a graphical tool for the visualization of multi-modal data comprising cardiorespiratory signals, automated cardiorespiratory metrics, automated respiratory patterns, manually classified respiratory patterns, and manual annotations by clinicians during data acquisition. This MATLAB-based application provides a means for collaborators to view combinations of signals to promote discussion, generate hypotheses and develop features.

Development of the open-source dose calculation and optimization toolkit matRad.

We report on the development of the open-source cross-platform radiation treatment planning toolkit matRad and its comparison against validated treatment planning systems. The toolkit enables three-dimensional intensity-modulated radiation therapy treatment planning for photons, scanned protons and scanned carbon ions. matRad is entirely written in Matlab and is freely available online. It re-implements well-established algorithms employing a modular and sequential software design to model the entire treatment planning workflow. It comprises core functionalities to import DICOM data, to calculate and optimize dose as well as a graphical user interface for visualization. matRad dose calculation algorithms (for carbon ions this also includes the computation of the relative biological effect) are compared against dose calculation results originating from clinically approved treatment planning systems. We observe three-dimensional γ-analysis pass rates ≥ 99.67% for all three radiation modalities utilizing a distance to agreement of 2 mm and a dose difference criterion of 2%. The computational efficiency of matRad is evaluated in a treatment planning study considering three different treatment scenarios for every radiation modality. For photons, we measure total run times of 145 s-1260 s for dose calculation and fluence optimization combined considering 4-72 beam orientations and 2608-13597 beamlets. For charged particles, we measure total run times of 63 s-993 s for dose calculation and fluence optimization combined considering 9963-45574 pencil beams. Using a CT and dose grid resolution of 0.3 cm3 requires a memory consumption of 1.59 GB-9.07 GB and 0.29 GB-17.94 GB for photons and charged particles, respectively. The dosimetric accuracy, computational performance and open-source character of matRad encourages a future application of matRad for both educational and research purposes.

Client-server architecture for pre and post-processing of real problems involving two-dimensional generalized coordinates

Purpose – The aim of this paper is to propose a Web environment for pre-processing and post-processing for 2D problems in generalized coordinate systems. Design/methodology/approach – The system consists of a Web service for client-server communication, a database for user information, simulation requests and results storage, a module of (for) calculation processing (front-end) and a graphical interface for visualization of discretized mesh (back-end). Findings – The Web system was able to model real problems and situations, where the user can describe the problem or upload a geometry file descriptor, generated from computer graphics software. The Web system, programmed for finite difference solutions, was able to generate a mesh from other complex methods, such as finite elements method, adapting it to the proposed Web system, respecting the finite difference mesh structure. Research limitations/implications – The proposed Web system is limited to solve partial differential equations by finite difference discretization. We need to study about refinement and parameters adaptations to solve partial differential equations simulated with other methods. Practical implications – The Web system includes implications for the development of a powerful real problems simulator, which is useful for computational physics researchers and engineers. The Web system uses several technologies, such as Primefaces, JavaScript, JQuery and HTML, to provide an interactive user interface. Originality/value – The main contribution of this work is the availability of a generic Web architecture for including other types of coordinate systems and to solve others partial differential equations. Moreover, this paper presents an extended version of the work presented in ICCSA 2014.

Visual GUI testing in practice

In today's software development industry, high-level tests such as Graphical User Interface (GUI) based system and acceptance tests are mostly performed with manual practices that are often costly,...

Visual GUI testing in practice: challenges, problemsand limitations

In today's software development industry, high-level tests such as Graphical User Interface (GUI) based system and acceptance tests are mostly performed with manual practices that are often costly, tedious and error prone. Test automation has been proposed to solve these problems but most automation techniques approach testing from a lower level of system abstraction. Their suitability for high-level tests has therefore been questioned. High-level test automation techniques such as Record and Replay exist, but studies suggest that these techniques suffer from limitations, e.g. sensitivity to GUI layout or code changes, system implementation dependencies, etc. Visual GUI Testing (VGT) is an emerging technique in industrial practice with perceived higher flexibility and robustness to certain GUI changes than previous high-level (GUI) test automation techniques. The core of VGT is image recognition which is applied to analyze and interact with the bitmap layer of a system's front end. By coupling image recognition with test scripts, VGT tools can emulate end user behavior on almost any GUI-based system, regardless of implementation language, operating system or platform. However, VGT is not without its own challenges, problems and limitations (CPLs) but, like for many other automated test techniques, there is a lack of empirically-based knowledge of these CPLs and how they impact industrial applicability. Crucially, there is also a lack of information on the cost of applying this type of test automation in industry. This manuscript reports an empirical, multi-unit case study performed at two Swedish companies that develop safety-critical software. It studies their transition from manual system test cases into tests automated with VGT. In total, four different test suites that together include more than 300 high-level system test cases were automated for two multi-million lines of code systems. The results show that the transitioned test cases could find defects in the tested systems and that all applicable test cases could be automated. However, during these transition projects a number of hurdles had to be addressed; a total of 58 different CPLs were identified and then categorized into 26 types. We present these CPL types and an analysis of the implications for the transition to and use of VGT in industrial software development practice. In addition, four high-level solutions are presented that were identified during the study, which would address about half of the identified CPLs. Furthermore, collected metrics on cost and return on investment of the VGT transition are reported together with information about the VGT suites' defect finding ability. Nine of the identified defects are reported, 5 of which were unknown to testers with extensive experience from using the manual test suites. The main conclusion from this study is that even though there are many challenges related to the transition and usage of VGT, the technique is still valuable, flexible and considered cost-effective by the industrial practitioners. The presented CPLs also provide decision support in the use and advancement of VGT and potentially other automated testing techniques similar to VGT, e.g. Record and Replay.

Graphical user interface for visualization of a decision support system for PEEP titration

The analysis of dynamic volume-dependent compliance provides the rationale basis for PEEP titration during mechanical ventilation. Due to its volume dependence, the compliance of the respiratory system is nonlinear within each single breath (intratidal), which is reflected in the compliance-volume curve (CV curve). The shape of the CV curve is determined by the PEEP level. The mechanical stress for the mechanically ventilated lung is expected to be minimal when the lung is ventilated within the volume range of maximal compliance. We present a new graphical user interface (GUI) that supports the clinician to titrate the PEEP level by means of a shape category analysis of the CV curve.

Digital health, microfluidics, and bedside genetic testing.

Decentralized, bedside, or point of care analysis of nucleic acids (DNA/RNA/mRNA/microRNA)-based markers is expected to be a key component of digital healthcare. Nucleic acids-based approaches allow for screening of disease and pathogens, disease surveillance, selection of treatment, treatment effectiveness, differential diagnosis, risk assessment, staging, and prognosis. Hand-held genetic analysis systems have the potential to provide all these capabilities in a simple, affordable, field deployable, rapid, multiplexed, and robust manner without the need for electrical power or refrigerated reagents. Even the need for specific language can be eliminated by translatable or visual graphical user interface truly integrating the analytical system with the communication network. The presentation will introduce Gene-Z and iDx, two networkable platforms that are developed to provide simplified analysis of genetic markers. Gene-Z has Android/iPod based operation using BluetoothTM and capable of carrying out quantitative isothermal amplification for 64 reactions in a disposable microfluidic chip. The device is battery operated and can be charged by solar panels integrated at the top of the device. A smaller version (iDx) working as an attachment to cell phones, also with real time amplification and quantification capabilities, allows 8 reactions in parallel. Both these devices are networkable and currently being validated for a number of key applications important to human and animal health, plant safety, industrial microbiology, and environmental protection. Simplification, reliability, and cost-effectiveness are key factors ensuring successful implementation of such approaches. Business model for adoption of such low cost approaches, however, is still evolving and major challenges need to be addressed about how to sustain a business that is built on small margins usually by small companies engaged in biomedical research.

A web-based intelligent disease-diagnosis system using a new fuzzy-logic based approach for drawing the inferences in crops

This paper suggests a new approach for providing intelligence in the system for diagnosis of diseases of the oilseed-crops. It reports the development of a web-based intelligent disease diagnosis system (WIDDS). The WIDDS is based on a new fuzzy logic approach. The approach is based on use of a rule-promotion methodology. This approach enables the drawing of inferences with the enhanced intelligence. The WIDDS also incorporates new features that improve the presently existing expert systems. The new features are (i) object-oriented (O-O) inference model, (ii) dynamic knowledge base creation strategy. The dynamically promoted rules are derived from those diagnosis sessions, which resulted in successful decisions. This enables more efficient decision-making in the future sessions, (iii) audio–visual–graphical user interface using text-to-speech (TTS) conversion tools. The WIDDS results in decreasing not only the number of interactive question–answer sessions with the clients but also leads to acceptable diagnosis. Further, the inferences are drawn faster compared to the traditional approach, which is the expert based reasoning method. The suggested WIDDS, which is based on rule-promotion approach, has been tested for three oilseeds crops – soybean, groundnut and rapeseed-mustard.

Design and implementation of a data acquisition system for the study of dynamics signals in the time Domain

The purpose of this research was to design and implement a data acquisition system for the study of dynamic signals in the time in order of nanoseconds, through the use of electronic instrumentation to obtain the temporal profiles of light signals, such as pulses of light from a laser or fluorescent light signals. To carry out the design and implementation of the data acquisition system proposed, we used a rapid response transducer and a data acquisition card of high speed. As well, it was developed a graphical user interface for visualization, analysis and study of the data acquired. Thus, it was possible to perform the digitization of a pulse on the order of nanoseconds, as well as the acquisition of fluorescence signals of different wavelengths, from which to obtain theoretical and experimental valuable knowledge based on the physics of spectroscopy.

MEG/EEG source reconstruction, statistical evaluation, and visualization with NUTMEG.

NUTMEG is a source analysis toolbox geared towards cognitive neuroscience researchers using MEG and EEG, including intracranial recordings. Evoked and unaveraged data can be imported to the toolbox for source analysis in either the time or time-frequency domains. NUTMEG offers several variants of adaptive beamformers, probabilistic reconstruction algorithms, as well as minimum-norm techniques to generate functional maps of spatiotemporal neural source activity. Lead fields can be calculated from single and overlapping sphere head models or imported from other software. Group averages and statistics can be calculated as well. In addition to data analysis tools, NUTMEG provides a unique and intuitive graphical interface for visualization of results. Source analyses can be superimposed onto a structural MRI or headshape to provide a convenient visual correspondence to anatomy. These results can also be navigated interactively, with the spatial maps and source time series or spectrogram linked accordingly. Animations can be generated to view the evolution of neural activity over time. NUTMEG can also display brain renderings and perform spatial normalization of functional maps using SPM's engine. As a MATLAB package, the end user may easily link with other toolboxes or add customized functions.