Third-party Software Research Articles

IoT-based Dairy Supply Chain - An Ontological Approach

Emerging digital transformation in industry is noticeable among others in Supply Chain Management (SCM). For instance, applying new-generation digitalized technologies in the Dairy Supply Chain (DSC) enables an increase of manufacturing productivity, improves planning and forecasting, and also enhances competitive capabilities according to Industry 4.0 assumptions. It is worth mentioning, that in modern DSC, high visibility of raw materials, components, products, and processes by all contributors on all stages of DSC is crucial. This article focuses on the transparency aspect of the DSC supported by IoT-based technologies enabling interoperability among all DSC participants. The paper addresses the problem of effective integration of heterogeneous data sources, i.e., deployed new technological IoT solutions with traditional SCM systems and a third-party software component. The main objective of this report is to propose the IoT-based DSC model comprising four chain stages: milk production, milk transportation, milk processing, and dairy products distribution. Moreover, the comprehensive DSC domain ontology as a knowledge model is formulated and described. The ontology aims on improvement of the DSC management efficiency by facilitating interoperability within DSC. The applicability of the proposed ontological model is verified using a sustainable-oriented case study, which estimates the environmental footprint at the milk transportation stage of the DSC.

A Multi-Tier Security Analysis of Official Car Management Apps for Android

Using automotive smartphone applications (apps) provided by car manufacturers may offer numerous advantages to the vehicle owner, including improved safety, fuel efficiency, anytime monitoring of vehicle data, and timely over-the-air delivery of software updates. On the other hand, the continuous tracking of the vehicle data by such apps may also pose a risk to the car owner, if, say, sensitive pieces of information are leaked to third parties or the app is vulnerable to attacks. This work contributes the first to our knowledge full-fledged security assessment of all the official single-vehicle management apps offered by major car manufacturers who operate in Europe. The apps are scrutinised statically with the purpose of not only identifying surfeits, say, in terms of the permissions requested, but also from a vulnerability assessment viewpoint. On top of that, we run each app to identify possible weak security practices in the owner-to-app registration process. The results reveal a multitude of issues, ranging from an over-claim of sensitive permissions and the use of possibly privacy-invasive API calls, to numerous potentially exploitable CWE and CVE-identified weaknesses and vulnerabilities, the, in some cases, excessive employment of third-party trackers, and a number of other flaws related to the use of third-party software libraries, unsanitised input, and weak user password policies, to mention just a few.

Real-time leak detection in oil pipelines using an Inverse Transient Analysis model

Based on Inverse Transient Analysis (ITA) method, a real-time leak detection method is proposed to capture leak location and the associated leak rate in oil pipe conveyance systems. In the proposed approach, location and flow rate of leak (if any), the fluid properties, as well as physical parameters of the system, are calculated in consecutive periods through minimizing the discrepancy between the calculated and measured flow parameters of the system. The method of characteristics is employed to numerically calculate the transient responses of the system and the genetic algorithm is utilized as the optimization engine. The proposed approach was applied to several real pipeline systems in which the required transient flow data are either directly collected from the field or fabricated with a third-party numerical software. Extensive numerical explorations were conducted to investigate the performance of the proposed method in real-time leak detection and to determine the extent to which field data errors, stemming from Supervisory Control and Data Acquisition (SCADA) systems and measurement equipment, affect the leak flow rate and location detectability of the proposed approach. The results show that the proposed approach provides promising results under a variety of transient and steady-state flow conditions even in the case with small leak flow rate of around 2% of the line rate. The results also reveal that the noises in the measurement data and the errors originated from SCADA systems do not significantly compromise the leak detectability of the proposed approach, confirming that the proposed approach can be utilized in practice.

Research on Carbon Emission Measurement of Construction Products Based on BIM

With global warming, environmental issues have gradually received attention. Surprisingly, the construction industry contributes most of the greenhouse gases. In order to reduce carbon emissions, the construction industry has proposed many energy-saving and emission-reduction methods from the perspectives of construction technology, reverse logistics supply chain optimization, and design optimization. However, problems in the prediction and measurement of carbon emissions have always been the focus and difficulty of the construction industry. Recently, BIM technology has continuously penetrated into the construction industry, which has influenced many scholars to gradually use BIM technology to reduce carbon emissions. Unlike other scholars, this research uses the Revit API to integrate carbon emission measurement functions into the Revit environment. These not only reduce the dependence on third-party software and tedious operations, but also provide architectural designers with reference information for environment optimization during the design stage.

Oxford nanopore sequencing in clinical microbiology and infection diagnostics.

Extended turnaround times and large economic costs hinder the usage of currently applied screening methods for bacterial pathogen identification (ID) and antimicrobial susceptibility testing. This review provides an overview of current detection methods and their usage in a clinical setting. Issues of timeliness and cost could soon be circumvented, however, with the emergence of detection methods involving single molecule sequencing technology. In the context of bringing diagnostics closer to the point of care, we examine the current state of Oxford Nanopore Technologies (ONT) products and their interaction with third-party software/databases to assess their capabilities for ID and antimicrobial resistance (AMR) prediction. We outline and discuss a potential diagnostic workflow, enumerating (1) rapid sample prep kits, (2) ONT hardware/software and (3) third-party software and databases to improve the cost, accuracy and turnaround times for ID and AMR. Multiple studies across a range of infection types support that the speed and accuracy of ONT sequencing is now such that established ID and AMR prediction tools can be used on its outputs, and so it can be harnessed for near real time, close to the point-of-care diagnostics in common clinical circumstances.

Low-Cost Precision Monitoring System of Machine Tools for SMEs

Digital manufacturing technology promotes the application of digital information to manufacturing processes and machine tools. However, the high entry cost and complexity of existing offerings limit the wide application of digital manufacturing in small and medium-sized enterprises (SMEs). For CNC machine tools, precision parameters can be acquired either by a visual inspection by the operator or by third-party connection software or hardware. To decrease human error, cost and time in data recording, this research proposes a machine tool data acquisition process for monitoring purposes using a novel monitoring system based on low-cost hardware (Arduino and low-cost camera) and open-source computation platforms (Node-RED). Remote data processing in a tablet is rendered possible by wireless data communication. Prototypes were tested with a HU40-T Five-axis machine tool. Tests show that the proposed system is capable of acquiring precision parameters such as the pitch error and backlash error of machine tools at a system cost of less than $200 CAD.

АРХИТЕКТУРА ПОСТРОЕНИЯ БАЗЫ ЗНАНИЙ ПРОЕКТНОЙ ОРГАНИЗАЦИИ

The article presents the results of software package development to create a knowledge base for a design organization. The definition of the concept of knowledge is presented on the basis of existing definitions in open sources. The architecture of the software package is described, its main modules are listed, as well as third-party software systems used in the development of the software package. The article considers the organization of data storage subsystem of the software complex and describes the data model of this subsystem. An approach to organize a repository of the software package ontologies based on a database in an RDF format is described. The software structure for the implementation of connectors for integration with the existing systems of the design organization is presented. The article also describes a method for expanding a search query using ontology and a full-text search to take into account the features of the subject area in the search process. The information and digital model of the user of the design organization is described with reference to the artifacts of the design organization.

CREATING A THREE-DIMENSIONAL MODEL OF THE TERRAIN BASED ON THE SURVEY DATA FROM AN UNMANNED AERIAL VEHICLE

. Today, three-dimensional models of objects and terrain are a very popular product and are found almost everywhere in our life: in the gaming and film industries, in various industries and complex technological areas such as architecture, construction, medicine, etc. The article considers the creation of a three-dimensional terrain model based on data obtained from an unmanned aerial vehicle to the territory of an aluminum alloy plant located in the city of Podolsk (Lviv microdistrict), Moscow region. The initial data for processing were obtained by a passive aerial survey method – the Phantom 4 PRO apparatus. The main part of the article is devoted to the stages of processing in the Agisoft Metashape software, which include such processes as: importing and aligning the position of cameras (as well as their optimization); building a sparse and dense point cloud; reconstruction of a polygonal three-dimensional terrain model; applying a texture created on the basis of images;optimization of the model and consideration of possible formats for export to third-party software. As a result of the work, a three-dimensional terrain model was obtained with an accuracy of binding to the centers of images of 1.14 m. The time spent on processing the survey data from an unmanned aerial vehicle is no more than 5 hours.

The Modelling of Digital Twins Technology in the Construction Process of Prefabricated Buildings

In the process of building construction, traditional architectural design and construction methods take a long time. The built buildings perform poorly in terms of energy usage and energy conservation. The study expects to explore the potential safety hazards of prefabricated buildings during the construction process. On this basis, a modelling study of the construction process is carried out. The study uses Digital Twins (DTs) technology and prefabricated Building Information Modelling (BIM) to conduct in‐depth modelling research on the building construction process. The prefabricated building construction system oriented to DTs technology can well solve the problems of structural damage and deformation in the production, transportation, and assembly process of building components. Especially in prefabricated buildings, it can monitor and accurately predict the damage of building components that may occur in the entire system due to structural problems and material problems in real time. Regarding the building information model, the study uses third‐party software to transfer the assembly information to the network cloud to further realize the display of the BIM. The study shows that the maximum value of the effective risk cases selected is 130, and its effective rate is 100%; after processing the data, it is found that the initial value is always stable, and its value is 1; the extracted value is always changing, the maximum value is 0.86, and the minimum is 0.75. By this result, the conclusion is that DTs technology and BIM can effectively monitor the indicators of risk problems during the construction of prefabricated buildings and can further reduce potential safety hazards. Through building information modelling, the development of intelligent industrialization of building construction design and the in‐depth study of construction modelling has practical application value.

Functional bases of the software development and operation in avionics

The study analyzes the functional principles and approaches to determine the main features of the software used for the aircraft operation. Theoretical aspects of creating the software architecture in the field of civil aviation based on modern approaches to the automation systems development are described. The main regulatory requirements for organizational and technological support of the process of developing software solutions in the field of civil aviation are considered. The peculiarities of the V-shaped model of aircraft operation software development are determined. The documentation for the software should consist of a description of the main blocks of the program, the order of modules integration, system architecture and other formalities that reflect the results of the source code. Based on the described approach to the development of a software package for the aircraft operation, the vision and criteria of the cycle of development of information solutions in the field of civil aviation is created. Depending on the functional characteristics of the obtained software solutions, the final documentation is compiled, which also contains the results of its testing under the conditions of pre-industrial operation. Modern avionics systems have a modular multilevel structure. At the same time, the classical approaches to the development of aircraft operation systems are inefficient, which requires the development of a specific methodology that takes into account the studied subject area. This is due to the need to integrate software for the operation of civil aircraft with third-party software and hardware used for flight control.

Web-Based Genome Analysis of Bacterial Meningitis Pathogens for Public Health Applications Using the Bacterial Meningitis Genomic Analysis Platform (BMGAP).

Effective laboratory-based surveillance and public health response to bacterial meningitis depends on timely characterization of bacterial meningitis pathogens. Traditionally, characterizing bacterial meningitis pathogens such as Neisseria meningitidis (Nm) and Haemophilus influenzae (Hi) required several biochemical and molecular tests. Whole genome sequencing (WGS) has enabled the development of pipelines capable of characterizing the given pathogen with equivalent results to many of the traditional tests. Here, we present the Bacterial Meningitis Genomic Analysis Platform (BMGAP): a secure, web-accessible informatics platform that facilitates automated analysis of WGS data in public health laboratories. BMGAP is a pipeline comprised of several components, including both widely used, open-source third-party software and customized analysis modules for the specific target pathogens. BMGAP performs de novo draft genome assembly and identifies the bacterial species by whole-genome comparisons against a curated reference collection of 17 focal species including Nm, Hi, and other closely related species. Genomes identified as Nm or Hi undergo multi-locus sequence typing (MLST) and capsule characterization. Further typing information is captured from Nm genomes, such as peptides for the vaccine antigens FHbp, NadA, and NhbA. Assembled genomes are retained in the BMGAP database, serving as a repository for genomic comparisons. BMGAP’s species identification and capsule characterization modules were validated using PCR and slide agglutination from 446 bacterial invasive isolates (273 Nm from nine different serogroups, 150 Hi from seven different serotypes, and 23 from nine other species) collected from 2017 to 2019 through surveillance programs. Among the validation isolates, BMGAP correctly identified the species for all 440 isolates (100% sensitivity and specificity) and accurately characterized all Nm serogroups (99% sensitivity and 98% specificity) and Hi serotypes (100% sensitivity and specificity). BMGAP provides an automated, multi-species analysis pipeline that can be extended to include additional analysis modules as needed. This provides easy-to-interpret and validated Nm and Hi genome analysis capacity to public health laboratories and collaborators. As the BMGAP database accumulates more genomic data, it grows as a valuable resource for rapid comparative genomic analyses during outbreak investigations.

Rapid generation of optimal generalized Monkhorst-Pack grids

Computational modeling of the properties of crystalline materials has become an increasingly important aspect of materials research, consuming hundreds of millions of CPU-hours at scientific computing centers around the world each year, if not more. A routine operation in such calculations is the evaluation of integrals over the Brillouin zone. We have previously demonstrated that performing such integrals using generalized Monkhorst-Pack k-point grids can roughly double the speed of these calculations relative to the widely-used traditional Monkhorst-Pack grids. However the generation of optimal generalized Monkhorst-Pack grids is not implemented in most software packages due to the computational cost and difficulty of identifying the best grids. To address this problem, we present new algorithms that allow rapid generation of optimal generalized Monkhorst-Pack grids on the fly. We demonstrate that the grids generated by these algorithms are on average significantly more efficient than those generated using existing algorithms across a range of grid densities. For grids that correspond to a real-space supercell with at least 50 Å between lattice points, which is sufficient to converge density functional theory calculations within 1 meV/atom for nearly all materials, our algorithm finds optimized grids in an average of 0.19 s on a single processing core. To facilitate the widespread adoption of this approach, we present new open-source tools including a library designed for integration with third-party software packages.

MIN3P-HPC: A High-Performance Unstructured Grid Code for Subsurface Flow and Reactive Transport Simulation

The numerical simulation of flow and reactive transport in porous media with complex domains is nontrivial. This paper presents a method to implement fully unstructured grid capabilities into the well-established software ParMIN3P-THCm, a process-based numerical model designed for the investigation of subsurface fluid flow and multicomponent reactive transport in variably saturated porous media with parallelization capability. The enhanced code, MIN3P-HPC, is modularized to support different cell types, spatial discretization methods and gradient reconstruction methods. MIN3P-HPC uses a vertex-centered control volume method with consideration of both vertex-based and cell-based material properties (e.g., permeability). A flexible parallelization scheme based on domain decomposition and thread acceleration was implemented, which allows the use of OpenMP, MPI and hybrid MPI-OpenMP, making optimized use of computer resources ranging from desktop PCs to distributed memory supercomputers. The code was verified by comparing the results obtained with the unstructured grid version to those produced by the structured grid version. Numerical accuracy was also verified against analytical solutions for 2D and 3D solute transport, and by comparison with third-party software using different cell types. Parallel efficiency of OpenMP, MPI and hybrid MPI-OpenMP versions was examined through a series of solute transport and reactive transport test cases. The results demonstrate the versatility and enhanced performance of MIN3P-HPC for reactive transport simulation.

HOPS: high-performance library for (non-)uniform sampling of convex-constrained models.

The C++ library Highly Optimized Polytope Sampling (HOPS) provides implementations of efficient and scalable algorithms for sampling convex-constrained models that are equipped with arbitrary target functions. For uniform sampling, substantial performance gains were achieved compared to the state-of-the-art. The ease of integration and utility of non-uniform sampling is showcased in a Bayesian inference setting, demonstrating how HOPS interoperates with third-party software. Source code is available at https://github.com/modsim/hops/, tested on Linux and MS Windows, includes unit tests, detailed documentation, example applications and a Dockerfile. Supplementary data are available at Bioinformatics online.

Quantitative Monte Carlo-based brain dopamine transporter SPECT imaging.

Brain dopamine transporter imaging with I-123-labeled radioligands is technically demanding due to the small size of the imaging target relative to the spatial resolution of most SPECT systems. In addition, I-123 has high-energy peaks which can penetrate or scatter in the collimator and be detected in the imaging energy window. The aim of this study was to implement Monte Carlo (MC)-based full collimator-detector response (CDR) compensation algorithm for I-123 into a third-party commercial SPECT reconstruction software package and to evaluate its effect on the quantitative accuracy of dopaminergic-image analysis compared to a method where only the geometric component of the CDR is compensated. In this work, we utilized a full Monte Carlo collimator-detector model and incorporated it into an iterative SPECT reconstruction algorithm. The full Monte Carlo model reconstruction was compared to standard reconstruction using an anthropomorphic striatal phantom filled with different I-123 striatal/cortex uptake ratios and with clinical I-123 Ioflupane DaTScan studies. Reconstruction with the full model yielded higher (13-25%) striatal uptake ratios than the conventional reconstruction, but the uptake ratios were still much lower than the true ratios due to partial volume effect. Visually, images reconstructed with the full Monte Carlo model had better contrast and resolution than the conventional images, with both phantom and patient studies. Reconstruction with full Monte Carlo collimator-detector model yields higher quantitative accuracy than conventional reconstruction. Additional work to reduce the partial volume effect related errors would improve the accuracy further.

Large-Scale Dataset of Local Java Software Build Results

When a person decides to inspect or modify a third-party software project, the first necessary step is its successful compilation from source code using a build system. However, such attempts often end in failure. In this data descriptor paper, we provide a dataset of build results of open source Java software systems. We tried to automatically build a large number of Java projects from GitHub using their Maven, Gradle, and Ant build scripts in a Docker container simulating a standard programmer’s environment. The dataset consists of the output of two executions: 7264 build logs from a study executed in 2016 and 7233 logs from the 2020 execution. In addition to the logs, we collected exit codes, file counts, and various project metadata. The proportion of failed builds in our dataset is 38% in the 2016 execution and 59% in the 2020 execution. The published data can be helpful for multiple purposes, such as correlation analysis of factors affecting build success, build failure prediction, and research in the area of build breakage repair.

Parametric synthesis of the controller by metaheuristic algorithm in the SimInTech environment

Efficiency and quality of operation of local automatic control systems as part of an autonomous object is mainly determined by the regulator in their composition and the used control law, for the synthesis of which is necessary to use modern computer-aided design systems. The article presents the results of the application of genetic algorithm as a method of parametric synthesis of the PID-controller implemented in the SimInTech visual dynamic modeling environment, which currently is used by enterprises in the rocket and space sectors of Russian Federation. Object of research is the dynamic negative feedback system on the example of the automatic angular position of artificial satellite control system. The functional scheme and the simplified mathematical model of the system in the form of the transfer functions of its links are presented. The computer model of the system as well as a process of synthesis of the controller are implemented as a package of projects, based on standard blocks and submodels SimInTech. Projects interact using a common signal base, which provides information exchange between projects, making the system model flexible and versatile. An interactive computing environment for programming language Python, Jupyter Notebook, is used as a third-party software. The organization of interaction between SimInTech and Jupyter Notebook is described, scripts of programs for its implementation are presented.

FINTECH SERVICES MARKET IN UKRAINE: CURRENT SITUATION, PROBLEMS AND PROSPECTS

In a globalized world there are radical changes in the construction of national financial systems, their organization and functioning under the influence of technological and financial innovations. Today, Fintech is the biggest driver of essentially revolutionary changes in financial systems at both the national and global levels. Ukraine does not stand aside from these processes, the state has some achievements, but according to experts, it lags behind developed markets, and therefore it is necessary to make up for lost. Most Fintech startups in Ukraine depend on equity in the absence of a functioning capital market. The infrastructure of electronic financial services remains imperfect. It is essential to change outdated legislation to promote a favorable business environment. The Ukrainian regulator should also promote the development of regulatory ‘sandboxes’ so that Fintech companies can use this tool. The classical banking system in ‘connections’ with the Fintech industry should be more active in digital multichannel banking, use artificial intelligence in its operations, do big data analytics based on artificial intelligence, use ‘cloud’ infrastructure. As for Ukrainian Fintech companies, their unique collective image looks like they are focused on the European market, have no investment from banks, focused on the B2B service model, are self-financed, top management has experience in traditional financial services, operates more than 3 years and still in development. Services are dominated by card payments and other types of payments. Competition in the market is insignificant due to the small number of Fintech companies. Ukrainian banks, in turn, do not have shares in the capital of third-party Fintech companies, have limited experience and understanding of the Fintech industry at the board level, but have specialists responsible for working with third-party software developers. There is no full-fledged interaction between banks and Fintech companies in Ukraine, although it is necessary for the further development of the financial services market, as currently market growth is less dependent on competition and more on raising awareness of the problems and technologies that can solve these problems.

UQpy: A general purpose Python package and development environment for uncertainty quantification

This paper presents the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

A methodology for analyzing renewable energy opportunities for desalination and its application to Aruba

There are numerous possible technology combinations for providing desalination using renewable energy sources. This paper presents a model that captures facets ranging from hourly availability of the renewable energy sources to economic parameters such as inflation and discount rate without relying on third-party software. The proposed approach considers different combinations of reverse osmosis and multi-stage-flash distillation driven by wind, solar PV and solar thermal with reference systems driven from the electric grid or natural gas. The levelized cost of water and the primary energy usage are presented as the main indicators for the performance of the different system architectures. Aruba is chosen as an example to show an application of the model. The project duration and the efficiency of desalination technologies is used to demonstrate the model capability for sensitivity analyses. The authors provide all used equations in the supplemental material to this paper.