Specific Software Tools Research Articles

Simple Software Simulator for Teaching Embedded Programming

This article presents simple software simulator of a microcontroller evaluation board FRDM-KL25Z. The simulator was developed to make it possible to teach our embedded systems course online during the COVID-19 pandemic. It is in principle a software library that handles function calls and register access from student’s program and displays the outputs in a console window of a standard desktop application. It does not require any special hardware or software tools except an IDE capable of building C++ applications for the desktop computer. It can be easily modified for different microcontrollers and thus can be useful if existing lessons need to be switched from in-person to distance learning at a short notice.

Software Engineering Code Workshop Based on B-RRT ∗ FND Algorithm for Deep Program Understanding Perspective

Developers will perform a lot of search behaviors when facing daily work tasks, searching for reusable code fragments, solutions to specific problems, algorithm designs, software documentation, and software tools from public repositories (including open source communities and forum blogs) or private repositories (internal software repositories, source code platforms, communities, etc.) to make full use of existing software development resources and experiences. This paper first takes a deep programmatic understanding view of the software development process. In this paper, we first define the software engineering code search task from the perspective of deep program understanding. Secondly, this paper summarizes two research paradigms of deep software engineering code search and composes the related research results. At the same time, this paper summarizes and organizes the common evaluation methods for software engineering code search tasks. Finally, the results of this paper are combined with an outlook on future research.

GamaComet: A Deep Learning-Based Tool for the Detection and Classification of DNA Damage from Buccal Mucosa Comet Assay Images.

Comet assay is a simple and precise method to analyze DNA damage. Nowadays, many research studies have demonstrated the effectiveness of buccal mucosa cells usage in comet assays. However, several software tools do not perform well for detecting and classifying comets from a comet assay image of buccal mucosa cells because the cell has a lot more noise. Therefore, a specific software tool is required for fully automated comet detection and classification from buccal mucosa cell swabs. This research proposes a deep learning-based fully automated framework using Faster R-CNN to detect and classify comets in a comet assay image taken from buccal mucosa swab. To train the Faster R-CNN model, buccal mucosa samples were collected from 24 patients in Indonesia. We acquired 275 comet assay images containing 519 comets. Furthermore, two strategies were used to overcome the lack of dataset problems during the model training, namely transfer learning and data augmentation. We implemented the proposed Faster R-CNN model as a web-based tool, GamaComet, that can be accessed freely for academic purposes. To test the GamaComet, buccal mucosa samples were collected from seven patients in Indonesia. We acquired 43 comet assay images containing 73 comets. GamaComet can give an accuracy of 81.34% for the detection task and an accuracy of 66.67% for the classification task. Furthermore, we also compared the performance of GamaComet with an existing free software tool for comet detection, OpenComet. The experiment results showed that GamaComet performed significantly better than OpenComet that could only give an accuracy of 11.5% for the comet detection task. Downstream analysis can be well conducted based on the detection and classification results from GamaComet. The analysis showed that patients owning comet assay images containing comets with class 3 and class 4 had a smoking habit, meaning they had more cells with a high level of DNA damage. Although GamaComet had a good performance, the performance for the classification task could still be improved. Therefore, it will be one of the future works for the research development of GamaComet.

APPROACH SELECTION METHOD FOR PROJECT PORTFOLIO MANAGEMENT AND ITS APPLICATION

Project portfolio management has evolved in recent decades from an empirical field to a field with advanced management technologies, including the active use of information technology. A number of standards and guidelines for project portfolio management have been created. Many dozens of specialized software tools have been developed. The effectiveness of an organization's project portfolio management significantly depends on the chosen management approach, as well as the level of use of project portfolio management capabilities. The level of utilization of project portfolio management capabilities is the level of maturity of an organization in this area. The aim of the article is to apply the method of project portfolio management approach selection. The article proposes to carry out the selection of a project portfolio management approach by solving a two-criteria problem. The first criterion is the risks inherent in this approach in the management of the organization's project portfolio under specific conditions. The less these risks, the more qualitative approach is applied. The second criterion - the costs of applying the evaluated approach. The application of the proposed method to improve project portfolio management in one of the technical universities in Ukraine was considered. Risks from non-performance or imperfect performance of portfolio management processes at the university were assessed. We also assessed the existing costs of managing the portfolio of projects. To improve the quality of management at the university, it is advisable to improve the execution of portfolio management processes and implement those processes that are not yet performed. This can be done by implementing a computerized portfolio and project management system for the university. Jira Portfolio Commercial can be used as such a system. With the use of computerization, new processes for project portfolio management will appear. For a number of existing processes in the organization, employee payroll costs will be reduced. For many processes, risks from non-performance or imperfect execution will be reduced. Computerization of project portfolio management will enable to reduce management costs by 1.8% and risks by 49.4%, i.e. almost by half.

Tools for simultaneous online and in‐person teaching in a Linear Circuit Analysis subject

AbstractDuring the first semester of 2020–2021, classes for Linear Circuit Analysis subjects (Mechanical Engineering Degree, Miguel Hernandez University of Elche, Spain) were taught in a dual way because of the COVID‐19 pandemic: students were able to attend in‐person or online, as long as the in‐person attendance limit was not surpassed. The same strategy was used for exams: each student decided whether to take the exam in‐person or online. Specific software tools were used for the in‐advance seat reservation and simultaneous online and in‐person class attendance, and examination tools and strategies, with a special emphasis on avoiding online cheating. Online attendance was preferred by students (averaging 64.9% of global attendance for lectures and 84.5% for exams), with abrupt increases during the worst episodes of the pandemic. Video recordings of the lectures were made available to all of the students, with the most viewed video being accessed over 200 times. Concerning evaluation, no statistically significant differences were found between in‐person or online average examination marks (p = .133), which may be an indicator of low online cheating. Student feedback showed their satisfaction with the dual teaching strategy, despite their initial doubts at the beginning of the course.

Использование сторонних библиотек при написании программ для обработки статистических данных

The technology of statistical data processing using software and the C# programming language is considered. Various approaches to the study of statistical data are considered, both with the help of special mathematical software tools such as Scilab, MATLAB, Octave and by writing their own programs using specialized mathematical libraries. An overview of the methods of mathematical processing of the results of the experiment is given. A comparative analysis of various libraries for performing statistical data processing for the C# programming language is performed. A comparative analysis of the choice of programming language is performed from the point of view of the use of application libraries, depending on the presence of mathematical libraries for statistical data processing. Software constructs are being built for the IL Numerics Ultimate VS library, which is an extension for Visual Studio and allows you to write and execute mathematical algorithms in a very fast and efficient way. Data interpolation and visualization functions are studied based on the construction of graphs of functions based on statistical data. The Microsoft Word XX library is considered. YY Object Library which allows you to process text, tabular and graphical data in order to place them and save them in MS Word.

SOFTWARE ARCHITECTURE FOR MATHEMATICAL MODELING BASED ON INTERVAL AND ONTOLOGICAL APPROACH

Mathematical knowledge is a term often used to describe various components of mathematical science, such as theorems, lemmas, axioms, proofs, etc.. By the term “knowledge from mathematical modeling” we understand the definition of a huge amount of knowledge, which is formalized both within the framework of a specific mathematical model and in the process of its construction, as well as related procedures of practical use. Compared to other forms of knowledge, such as rules, solution trees, mathematical knowledge is more abstract and more structured. In general, the ontological approach to mathematical modeling refers to the use of ontology, as it is based on the terms of mathematical modeling and descriptions of relationships between the main processes of its course.. The general ontological approach to mathematical modeling from an applied point of view does not allow to manage the processes of building mathematical models, because it can only be used to describe the area of mathematical modeling. From an applied point of view, most basic forms of mathematical knowledge are either embedded in specific software tools, such as models of aggregate operation in simulation software, or must be formally interpreted into a more general mathematical tool, following appropriate syntactic rules. Most of this type of knowledge relates to specific modeling tasks and is clearly implemented with the help of appropriate procedural descriptions, rather than declarative representations, unlike the philosophical vision of mathematical modeling. The paper substantiates the use of the ontological approach as an effective tool for managing the processes of building mathematical models based on interval data and using these models for applied problems. The use of the ontological model made it possible to formalize the process of obtaining, storing and using knowledge obtained in the process of mathematical modeling. The article also presents the features of building a software architecture for mathematical modeling based on interval analysis and an ontological approach. The technology for creating software based on the developed ontological add-on for mathematical modeling using interval data for various objects, as well as various forms of user interface implementation, is described. A number of diagrams illustrating the peculiarities of using the ontological approach based on interval data are presented and the peculiarities of its interpretation in applied fields, in particular, in the tasks of environmental monitoring, are described.

Integrating computational fluid dynamics data into medical image visualization workflows via DICOM.

Communicating complex blood flow patterns generated from computational fluid dynamics (CFD) simulations to clinical audiences for the purposes of risk assessment or treatment planning is an ongoing challenge. While attempts have been made to develop new software tools for such clinical visualization of CFD data, these often overlook established medical imaging/visualization practice and data infrastructures. Here, leveraging the clinical ubiquity of the DICOM file format, we present techniques for the translation of CFD data to DICOM series, facilitating interactive visualization in standard radiological software. Unstructured CFD data (volumetric fields of velocity magnitude, Q-criterion, and pathlines) are resampled to structured grids. Novel raster-based techniques that simulate experimental optical blurring are presented for bringing simulated pathlines into structured image volumes. DICOM series are created by strategically encoding these data into the file's PixelArray tag. Lumen surface information is also strategically encoded into a different range of pixel intensities, allowing hemodynamics and morphology to be co-visualized in a single volume using opacity-based rendering transfer functions. We show that 3D temporal CFD data represented as structured DICOM series can be rendered interactively in Horos, a widely-used medical imaging/radiology software. Our transfer function-based approach allows for representations of scalar isosurfaces, volumetric rendering, and tubular pathlines to be modified in real-time, resembling conventional unstructured visualizations. Careful selection of voxelization ROIs helps to ensure that data are kept lightweight for real-time rendering and minimal storage. While our approach inherently sacrifices some of the advanced visualization capabilities of specialized software tools, we believe our closer consideration of standardization can help to facilitate meaningful clinical interaction. This work opens up possibilities for the complete integration of measured and simulated data in established radiological software environments and workflows from PACS storage to 3D/4D visualization.

On the analysis of makespan and performance of the task‐based execution model for enterprise application integration platforms: An empirical study

SummaryIncreasingly enterprises rely on software applications to support their business processes. Since such processes are continually evolving to keep up with market dynamism, companies strive to increase their efficiency, for example, by optimising the integration of applications supporting these processes. Integration platforms are specialised software tools that allow creating integration processes so that applications can share data and functionality. However, this integration involves several challenges, especially when large volumes of heterogeneous data should be integrated and shared. The performance of an integration process, in terms of message processing, is directly related to the run‐time system of the integration platform. This article investigates the impact of the volume of messages and the number of threads used by a run‐time system on makespan and performance of an integration process. The greater is the number of messages per second received by the integration process, the high is the volume of messages. The study was based on a run‐time system with task‐based execution model and follows a strict protocol to conduct and report our empirical study. We observed an increment of makespan when increasing the volume of messages to integration processes and different behaviours when increasing the number of threads used in their executions. Makespan reduces as the number of threads increases, but only when the volume of inbound messages is not very high. We confirmed that there is a performance gain by increasing the number of threads to execute an integration process, but observed that the continuous increment of threads leads to degradation of the performance in this model.

Construction and Visualization of the Ontology of the Educational Course for the Digital Information Space of the University

Despite the significant volume of educational courses published on the university's information portals, there is no full or partial mechanism for obtaining the necessary information in one place and an accessible form. Each course is a separate resource, without the ability to build logical connections (navigational transitions) between adjacent or sequential courses and courses of the same thematic cluster or subject area. The lack of systematization of e-courses does not allow realizing a full-fledged contextual search and navigation between related resources.
 Within the framework of this study, the problem of constructing and presenting an ontology of an electronic course is considered. Applied solutions to this problem will significantly increase the constructiveness of existing services for working with training courses and provide a new set of opportunities based on the systematization of knowledge. As a structure of knowledge representation, it is proposed to use a structured set of concepts (terms) that describe the theoretical and practical aspects of the electronic course. Such a domain ontology is represented as a semantic network, which can be visualized by a specialized software tool or using a graphical library, for example, d3 for the JavaScript language.

Secondary or Specialized Metabolites, or Natural Products: A Case Study of Untargeted LC-QTOF Auto-MS/MS Analysis.

The large structural diversity of specialized metabolites represents a substantial challenge in untargeted metabolomics. Modern LC–QTOF instruments can provide three- to four-digit numbers of auto-MS/MS spectra from sample sets. This case study utilizes twelve structurally closely related flavonol glycosides, characteristic specialized metabolites of plant tissues, some of them isomeric and isobaric, to illustrate the possibilities and limitations of their identification. This process requires specific software tools that perform peak picking and feature alignment after spectral deconvolution and facilitate molecular structure base searching with subsequent in silico fragmentation to obtain initial ideas about possible structures. The final assignment of a putative identification, so long as spectral databases are not complete enough, requires structure searches in a chemical reference database, such as SciFindern, in attempts to obtain additional information about specific product ions of a metabolite candidate or check its feasibility. The highlighted problems in this process not only apply to specialized metabolites in plants but to those occurring in other organisms as well. This case study is aimed at providing guidelines for all researchers who obtain data from such analyses but are interested in deeper information than just Venn diagrams of the feature distribution in their sample groups.

Analysis and comparison of different approaches to the extraction of parameters of the memristor model

The paper analyzes various approaches to the problem of extracting the parameters of an empirical memristor model. A description of the features of the extraction process for the memristor mobility modification model is given, and an original version of the extraction algorithm is proposed, based on the Nelder—Mead optimization algorithm with an objective function based on the calculation of features of the studied current-voltage characteristic. The proposed algorithm is compared with two others — with an objective function based on the symmetric difference between the areas of the model and experimentally obtained current-voltage characteristics and with an objective function based on the MSE between the points of the considered current-voltage characteristics. The comparison is carried out according to the criterion of a fixed budget using a specialized software tool. The proposed extraction algorithm is not inferior to the other two in accuracy, while offering the possibility of fine tuning.

Modeling of processes of creation and organization of bank employees qualification improvement courses using ARIS Express

The article analyzes the role of bank staff qualifications in the financial component of the banking system. The influence of the human factor on the activity of a banking institution is also analyzed. Crisis phenomena greatly affect every element of the banking sector, which encourages the use of risk management to respond to new realities. Under these circumstances, it is not necessary to forget about the bank's staff, providing them with opportunities to acquire knowledge and improve the level of qualifications in order to adapt to new realities. This approach will help to improve the professional and moral condition of employees even in crisis conditions of operation. In connection with the fact that some of the bank's employees are now in less safe working conditions due to the significant duration of air alarms and the high risk of missile attacks, the question arose, how can it be possible in the current conditions to ensure the opportunity to acquire new knowledge by taking qualification improvement courses. To solve the existing problem, the creation of an online course platform is proposed as an option that will provide the opportunity to take courses in a distance format. The process of creating, organizing and checking the effectiveness of courses was modelled using the ARIS Express program using special software tools. The online platform is an effective alternative for the bank and employees, as it will provide an opportunity to improve qualifications remotely at a convenient time and allow the bank's staff to stay in a safe place. The developed platform will be an indicator for checking the results of courses, will provide an opportunity for top management to monitor employees' grows to develop in this area. The creation of an online platform for training courses for bank employees will contribute to increasing the efficiency of the bank's work, which will become the basis for the development of professional skills of employees. The use of the proposed approach to improving the qualifications of bank employees will, as a result, have a positive effect on the economic indicators of the banking institution.

ИНТЕРАКТИВНЫЕ ИНСТРУМЕНТЫ МОДЕЛИРОВАНИЯ ПОТЕРЬ УПРАВЛЕНЧЕСКИХ РЕШЕНИЙ

The purpose of the work was to study losses in making managerial decisions and provide decision makers with modern interactive tools for modeling, analyzing and visualizing losses associated with the nonoptimality of such decisions. It is shown that the main criterion in making a managerial decision should be considered the losses associated with the magnitude of the deviation of the actual value of the decision quality index from the optimal value. To achieve the goal, the following tasks were solved: an analytical representation of the penalty function was proposed and justified, taking into account the region of no losses and the possibility of specifying a nonlinear behavior of losses; selected and substantiated tools for developing interactive tools for modeling and visualizing penalty functions. The main research methods are the penalty function method and highlevel programming methods. As a result of the study, a specialized software tool was developed that allows you to design and analyze loss functions on a browser page, which makes it possible to work with the application both on a personal computer and on a mobile device.

Immune Repertoire Analysis on High-Performance Computing Using VDJServer V1: A Method by the AIRR Community.

AIRR-seq data sets are usually large and require specialized analysis methods and software tools. A typical Illumina MiSeq sequencing run generates 20-30 million 2×300bp paired-end sequence reads, which roughly corresponds to 15GB of sequence data to be processed. Other platforms like NextSeq, which is useful in projects where the full V gene is not needed, create about 400million 2×150bp paired-end reads. Because of the size of the data sets, the analysis can be computationally expensive, particularly the early analysis steps like preprocessing and gene annotation that process the majority of the sequence data. A standard desktop PC may take 3-5days of constant processing for a single MiSeq run, so dedicated high-performance computational resources may be required.VDJServer provides free access to high-performance computing (HPC) at the Texas Advanced Computing Center (TACC) through a graphical user interface (Christley et al. Front Immunol 9:976, 2018). VDJServer is a cloud-based analysis portal for immune repertoire sequence data that provides access to a suite of tools for a complete analysis workflow, including modules for preprocessing and quality control of sequence reads, V(D)J gene assignment, repertoire characterization, and repertoire comparison. Furthermore, VDJServer has parallelized execution for tools such as IgBLAST, so more compute resources are utilized as the size of the input data grows. Analysis that takes days on a desktop PC might take only a few hours on VDJServer. VDJServer is a free, publicly available, and open-source licensed resource. Here, we describe the workflow for performing immune repertoire analysis on VDJServer's high-performance computing.

Development of a digital twin operational platform using Python Flask

Abstract The digital twin concept has developed as a method for extracting value from data, and is being developed as a new technique for the design and asset management of high-value engineering systems such as aircraft, energy generating plant, and wind turbines. In terms of implementation, many proprietary digital twin software solutions have been marketed in this domain. In contrast, this paper describes a recently released open-source software framework for digital twins, which provides a browser-based operational platform using Python and Flask. The new platform is intended to maximize connectivity between users and data obtained from the physical twin. This paper describes how this type of digital twin operational platform (DTOP) can be used to connect the physical twin and other Internet-of-Things devices to both users and cloud computing services. The current release of the software—DTOP-Cristallo—uses the example of a three-storey structure as the engineering asset to be managed. Within DTOP-Cristallo, specific engineering software tools have been developed for use in the digital twin, and these are used to demonstrate the concept. At this stage, the framework presented is a prototype. However, the potential for open-source digital twin software using network connectivity is a very large area for future research and development.

Имитационные модели в цифровых двойниках железнодорожных узлов

The development of information technologies and technical means of data registration creates conditions for filling simulation models of railway transport with actual data. It allows us to use simulation models to create digital counterparts of railway stations and junctions. The experience of using simulation models to perform the tasks of designing and operational planning of railway transport systems of various complexity is analyzed. An overview of modern computer programs for simulation of railway transport is presented, the advantages and disadvantages of the specialized software tools are illustrated. The authors propose an approach to build a digital twin of a railway junction based on the universal simulation tool AnyLogic. The problems and limitations of using simulation models in digital twins for operational management of railway stations and junctions are systematized. Software solutions are proposed, the implementation of which makes it possible to provide an adequate representation of the operational situation at the railway station in the digital twin. A three-level architecture of a digital twin of a railway junction has been developed, including a description of the track development scheme, the technology of the transportation process, as well as a method for synchronizing model and actual data. Examples of the interface of a digital twin of non-public railway tracks are presented. The implementation of the developed twin at the mining enterprise allowed to increase the efficiency of decisions taken to coordinate the work of production units and transport, reduce idle time and increase the productivity of the ore-processing mill as a result of supplying it with raw materials of the required range at a given time.

Development of a specialized software complex for modeling the biogeochemical cycles in the Azov sea, including calculation modules of transformation of phosphorus, nitrogen, silicon, sulfur and dissolved oxygen forms, as well as the dynamics of phyto-and zooplatonkton

The paper is devoted to the development of a software complex for predictive modeling of biogeochemical cycles in the Azov Sea on high-performance computer systems in a limited time. The complex development includes the creation of software modules of the computational structure to calculate the concentrations of phosphorus, nitrogen, silicon, sulfur, dissolved oxygen forms and describe in detail phyto- and zooplankton dynamics in the Azov Sea; the integration of various environmental databases, satellite monitoring. The complex is adapted to solve a wide class of predictive problems of water ecology and water resources management. It includes the implementation of developed 3D mathematical model of hydrophysics and biological kinetics on computational grids, consistent with the complex shape of the water coastline. Parallel algorithms have been developed for numerical implementation of water ecology problems, oriented to high-performance computer systems. To increase the calculation efficiency of computational grid fragments assigned to graphics accelerators, an algorithm and its software implementation were developed in the CUDA C language. Based on the developed specialized software tools focused on supercomputers, scenarios for the development of the environmental situation and sustainable development management at biological rehabilitation of the Azov Sea were developed, including forecasts of changes in harmful algae concentration; dynamics of spatial interaction processes between phyto- and zooplankton populations; evolution of biological kinetics processes on the example of plankton interaction.

Ensembl 2022.

Ensembl (https://www.ensembl.org) is unique in its flexible infrastructure for access to genomic data and annotation. It has been designed to efficiently deliver annotation at scale for all eukaryotic life, and it also provides deep comprehensive annotation for key species. Genomes representing a greater diversity of species are increasingly being sequenced. In response, we have focussed our recent efforts on expediting the annotation of new assemblies. Here, we report the release of the greatest annual number of newly annotated genomes in the history of Ensembl via our dedicated Ensembl Rapid Release platform (http://rapid.ensembl.org). We have also developed a new method to generate comparative analyses at scale for these assemblies and, for the first time, we have annotated non-vertebrate eukaryotes. Meanwhile, we continually improve, extend and update the annotation for our high-value reference vertebrate genomes and report the details here. We have a range of specific software tools for specific tasks, such as the Ensembl Variant Effect Predictor (VEP) and the newly developed interface for the Variant Recoder. All Ensembl data, software and tools are freely available for download and are accessible programmatically.

A social media-based over layer on the edge for handling emergency-related events

Online Social Networks (OSNs), together with messaging services are tools for the exchange of entertainment-related information. However, they represent virtual environments capable of providing relevant information related to emergency or criminal events. Thanks to the simple way of using OSNs in combination to modern ubiquitous Internet of Things (IoT) smart devices, the generation and exploitation of such information is made available to users in real-time even more easily. Unfortunately, its reuse has not been taken into consideration yet due to the lack of specific models and related software tools. In this context, the paper presents a social media-based over layer for supporting the monitoring, detection, computation and information sharing of social media information related to emergency scenarios centered on smartphones and text mining techniques. The proposal is assessed through two different case studies, by evaluating the performances of different classifiers and by showing the logic of the functionalities of the related apps.