Individual Software Research Articles

ScACT: Accurate Cross-modality Translation via Cycle-consistent Training from Unpaired Single-cell Data.

Single-cell sequencing technologies have revolutionized genomics by enabling the simultaneous profiling of various molecular modalities within individual cells. Their integration, especially cross-modality translation, offers deep insights into cellular regulatory mechanisms. Many methods have been developed for cross-modality translation, but their reliance on scarce high-quality co-assay data limits their applicability. Addressing this, we introduce scACT, a deep generative model designed to extract cross-modality biological insights from unpaired single-cell data. scACT tackles three major challenges: aligning unpaired multi-modal data via adversarial training, facilitating cross-modality translation without prior knowledge via cycle-consistent training, and enabling interpretable regulatory interconnections explorations via in-silico perturbations. To test its performance, we applied scACT on diverse single-cell datasets and found it outperformed existing methods in all three tasks. Finally, we have developed scACT as an individual open-source software package to advance single-cell omics data processing and analysis within the research community.

Toward granular search-based automatic unit test case generation

Unit testing verifies the presence of faults in individual software components. Previous research has been targeting the automatic generation of unit tests through the adoption of random or search-based algorithms. Despite their effectiveness, these approaches aim at creating tests by solely optimizing metrics like code coverage, without ensuring that the resulting tests have granularities that would allow them to verify both the behavior of individual production methods and the interaction between methods of the class under test. To address this limitation, we propose a two-step systematic approach to the generation of unit tests: we first force search-based algorithms to create tests that cover individual methods of the production code, hence implementing the so-called intra-method tests; then, we relax the constraints to enable the creation of intra-class tests that target the interactions among production code methods. The assessment of our approach is conducted through a mixed-method research design that combines statistical analyses with a user study. The key results report that our approach is able to keep the same level of code and mutation coverage while providing test suites that are more structured, more understandable and aligned to the design principles of unit testing.

Abstract TP132: Optimal CT Perfusion Post-Processing Method in Posterior Circulation Stroke

Objective: CT-perfusion (CTP) has revolutionised stroke care by improving diagnostic accuracy and expanding eligibility to acute therapies. Software packages utilise various mathematical techniques to transform raw perfusion data into measures of infarct core and ischaemic penumbra. These techniques have been derived from studies of anterior-circulation stroke and not yet validated in posterior circulation stroke (PCS). We examined the optimal CTP thresholds for acute PCS. Methods: Data were analysed from 331-patients diagnosed with a PCS enrolled in the International-stroke-perfusion-registry (INSPIRE). Twenty-seven-patients with baseline multimodal-CT with occlusion of a large posterior-circulation (PC) artery and follow up diffusion-weighted-MRI at 24-48 hours were included. CTP parametric maps were generated using five different post-processing methods. Receiver-operating-curve analysis was used to determine the optimal perfusion parameter and thresholds. Results: Partial deconvolution was the optimal post-processing method for characterisation of ischaemic penumbra and infarct core. Mean transit time (MTT) at a threshold of >165% and >195% most accurately defined ischaemic core (AUC=0.73) and penumbra (AUC=0.78) respectively. Post-processing technique influenced accuracy of core (AUC range=0.54-0.73) and penumbra (AUC range=0.72-0.79) estimates. MTT was consistently the most accurate parameter at distinguishing core and penumbra across all post-processing methods. Conclusion: CTP has significant diagnostic utility in PCS. Accuracy of CTP varies considerably by post-processing method. The underlying post-processing technique employed by individual software packages should be considered when interpreting the accuracy of ischemic core and penumbra estimates.

Pakistan in the Crosshairs and the Rising Stakes of Strategic Information Warfare

Over the past two decades, information and communication technologies (ICTs) have reaped significant attention from security experts, computer scientists, intelligence agencies, and governments for their potential applications in conflict scenarios. Using ICTs for offensive or defensive purposes to instantly invade, disrupt, or control the opponent's resources is known as strategic information warfare (SIW). Although SIW is as ancient as military history, the communication sciences revolution has altered its character. It has evolved into a double-edged weapon that is equally crucial for strong nations, technically underdeveloped states, non-state entities, and individual software experts. Some nations, most notably the US, Russia, and China, have taken the SIW technology seriously and compared it to the danger posed by WMDs. In the south Asian context, Pakistan faces a direct threat from India, which collaborates closely with Israel, by the use of SIW.
 Additionally, the Western media portrays a highly negative picture of Pakistan's administration, law and order, and economy. The national media, suitably supported by foreign players, has begun a propaganda warfare effort against Pakistan's military forces and intelligence institutions. However, SIW is now a global danger, necessitating a worldwide response. Pakistan must create a proactive national strategy to prepare for the problems erupted from SIW strike on the communication network, which is crucial for the operation of its nuclear facilities.

IIOT ПЕРЕДАЧА ДАННЫХ С БПЛА В ПРОМЫШЛЕННУЮ СРЕДУ АГРОКОМПЛЕКСОВ В РЕЖИМЕ РЕАЛЬНОГО ВРЕМЕНИ

Agricultural complexes, including agriculture, are a good environment for the introduction of modern technologies and methods of using unmanned aerial vehicles to solve various tasks. Currently, in distributed control systems in various agricultural complexes using unmanned aerial vehicles, the classical hardware and software architecture for building such systems has been established. However, this approach has a number of significant drawbacks. (Research purpose) The research purpose is selecting the IIoT of the wireless real-time communication protocol of unmanned aerial vehicles for irrigation of agricultural complexes with a ground-based industrial system and developing concepts of a hardware and software complex using modern technologies and practices of the industrial Internet of things. (Materials and methods) Used open sources of international communities in the field of automation and the industrial Internet of Things, as well as domestic and foreign scientific publications on these topics, as source data and materials for the analysis and design of the proposed hardware architecture of the IIoT platform. The method of decomposition according to automation levels was applied; the method of decomposition according to the functionality performed by individual hardware and software components of the system; the method of summarizing information from modern sources on the subject of research; formalization of the hardware and software structure in the form of schematic diagrams. (Results and discussions) Proposed the concept of information data transmission based on the IIoT protocol of DDS-real-time data transmission. (Conclusions) It has been shown that classical architectural approaches to data transmission in the conditions of wireless systems and agro-unmanned aircraft have proven themselves well, however, the need to introduce new architectural and software methods and protocols for data transmission in real time leads to the need to study promising ways to implement this functionality. We analyzed the existing global trends in the field under consideration and proposed an up-to-date and up-to-date concept of IIoT architecture of distributed data transmission systems within the framework of a distributed management and monitoring system for agricultural complexes based on unmanned aircraft.

ПРОТОКОЛ DDS КАК ЕДИНАЯ СРЕДА ПЕРЕДАЧИ ДАННЫХ В РЕЖИМЕ РЕАЛЬНОГО ВРЕМЕНИ

For the effective development of agricultural complexes, the introduction of a variety of advanced technologies, including unmanned aerial vehicles, is especially important. In the distributed control systems used in various agricultural complexes and logging industries using unmanned aerial vehicles, the classical hardware and software architecture for creating such systems has been established. However, this approach has a number of significant drawbacks, in particular, the presence of a large number of different data bus standards at different levels of the platform architecture, which quite often significantly complicates the integration of individual parts of the system. The lack of a single standard within the software protocol for real-time data transmission leads to data fragmentation at all levels of the system as a whole. (Research Purpose) The research purpose is developing the concept of a hardware and software architecture for transmitting information data based on the Data Distribution Service protocol in real time as part of monitoring, managing and distributing tasks between unmanned aerial vehicles, as well as at all levels of a distributed agroforestry system using modern technologies and practices of the industrial Internet of Things. (Materials and methods) Used open sources of international communities in the field of automation and the industrial Internet of Things, as well as domestic and foreign scientific publications on this subject. The method of decomposition by automation levels was applied; the method of decomposition by functionality performed by individual hardware and software components of the system; the method of summarizing information from modern sources on the subject of research; formalization of hardware and software structures in the form of schematic diagrams. (Results and discussion) We have developed a concept for transmitting information data based on the Industrial Internet of Things Data Distribution Service protocol to ensure real-time data transmission. The proposed system makes it possible to implement unified information flows for monitoring and controlling unmanned aerial vehicles at all levels of a distributed agroforestry system. This helps simplify the integration of unmanned aerial systems into agroforestry systems of various orientation and complexity, eliminating difficulties in the interaction of various system components at all levels, including cloud solutions and other Industrial Internet of Things platforms. (Conclusions) As a result of the study, the problems of integrating the information flows of the agroforestry system and data transmission at its various levels were identified. It is proposed to use the Data Distribution Service data transfer protocol as a single standard at all levels of the system, which in the future will ensure compatibility and ease of integration of unmanned aerial vehicles of various manufacturers within a single system.

Using the Saga design pattern for transaction management in a microservice architecture

The use of microservice architecture in software development, in which each service is a self-sufficient participant with its own area of responsibility, its own data store, set of technologies, and work environment, is challenging in the context of transactions in a distributed service mode. After all, from the point of view of reliability and integrity of the system, it is extremely important to ensure data consistency, which implies compliance with defined restrictions and rules, absence of contradictions and consistency of data between system components. The architecture built on microservice interaction provides capabilities for decomposition of complex tasks, operational implementation of new functionality, isolation of critical components and scaling of individual software components. As a rule, the microservice architecture implements the principle «Database per service» — an approach according to which each microservice uses its own database, instead of a single shared database, as is usually implemented in a monolithic architecture. To ensure data consistency, the SAGA design pattern can be used, which provides a set of instructions for the correct management of transactions in a distributed architecture. To avoid the use of distributed transactions, it is recommended to use the SAGA design pattern, which allows for global data consistency through sets of local and compensating transactions. The template is fault-tolerant and ensures system reliability and integrity.

Dynamic TWGH: Client-Server Optimization for Scalable Combinatorial Test Suite Generation

To ensure that a software/hardware product is of sufficient quality and functionality, it is essential to conduct thorough testing and evaluations of the numerous individual software components that make up the application. Many different approaches exist for testing software, including combinatorial testing and covering arrays. Because of the difficulty of dealing with difficulties like a two-way combinatorial explosion, this brings up yet another problem: time. Using client-server architectures, this research introduces a parallel implementation of the TWGH algorithm. Many studies have been conducted to demonstrate the efficiency of this technique. The findings of this experiment were used to determine the increase in speed and compare it to the results obtained from the various methodologies. TWGH was shown to be a demonstration of scalability in studies involving speedups. When the recommended method was implemented, the rate of acceleration increased by eight.

Guidelines for the classification and management of risk, for the evaluation of safety and for the monitoring of existing bridges: differential analysis of experimental software applications for level 0,1,2 assessments

This paper investigates the application of the procedure described by the Italian Guideline for existing bridges and its related Operating Instructions for an existing bridge through three different IT (Information Technology) applications in order to evaluate its compliance with the regulation, and its effectiveness and efficiency, also in perspective of product certification. The work initially describes the result obtained applying manually the Guidelines with the aid of a non-commercial software developed at Sapienza for the definition of the level of defectiveness. Thus, the same procedure is repeated using two open - source commercial software, Inspicio and InBee which allow to operate within a Bridge Management System framework. Finally, a differential analysis among the three analyses is performed, highlighting the differences and the main characteristics of the software for the definition of the level of defectiveness, which is crucial for determining the attention class and to properly schedule the maintenance operations. Pros and cons of each individual software are detailed, followed by some suggestions for their potential improvement.

Ergonomic analysis of the classroom using the LiDAR system

This article presents an innovative method of using LiDAR technology to analyze and measure the current ergonomic conditions of a university classroom. The purpose of this research is to provide a detailed analysis of the working environment and to identify collision points, proposing changes and improvements to meet the rules and standards of ergonomic correctness. The outcome of this analysis is a 3D model containing detailed information about the current state of the environment. This model was subsequently utilized to identify ergonomic deficiencies, which formed the basis for proposed modifications. The article also discusses the applications of modern LiDAR technology, its functions, and accessibility for ordinary users, as well as accessibility on individual software platforms.

Software Maintainability and Refactorings Prediction Based on Technical Debt Issues

Software maintainability is a crucial factor impacting cost, time and resource allocation for software development. Code refactorings greatly enhance code quality, readability, understandability and extensibility. Hence, accurate prediction methods for both maintainability and refactorings are vital for long-term project sustainability and success, offering substantial benefits to the software community as a whole. This article focuses on prediction of software maintainability and the number of needed code refactorings using technical debt data. Two approaches were explored, one compressing technical debt issues per software component and employing machine learning algorithms such as ExtraTrees, Random Forest, Decision Trees, which all obtained a high accuracy and performance. The second approach retained multiple debt issue entries and utilized a Recurrent Neural Network, although less effectively. In addition to the prediction of the requisite number of code refactorings and software maintainability for individual software components, a comprehensive analysis of technical debt issues was conducted before and after the refactoring process. The outcomes of this study contribute to the advancement of a dependable prediction system for maintainability and refactorings, presenting potential advantages to the software community in effectively managing maintenance resources. Of all the employed models, the ExtraTrees model yielded the most optimal predictive outcomes. To the best of our knowledge no other approaches of using ML techniques for this problem have been reported in the literarture. Keywords and phrases: Software Quality, Sonarqube, Refactoring, Code Smells.

Laboratory information systems for research management in biology

Laboratory information systems for research management in biology

Информационные системы учета и анализа данных жилищно-коммунального хозяйства многоквартирных домов

The article discusses the development of information systems of housing and communal services of the Russian Federation from the point of view of resource consumption data accounting and analysis. The object of the study is "smart" apartment buildings. The subject of the research is information platforms, information systems and individual software developments for monitoring resource consumption in apartment buildings. It is noted that the digitalization of housing and communal services is just beginning and mainly refers to new construction. There is a potential for using digital services to manage a "smart" apartment building, including for the organization of telemetry. Three levels of development of digital services for resource management are identified. The list of the main digital platforms supporting the telemetry function in apartment buildings is presented. The possibilities of integration of various automated information systems are discussed. It is noted that the analytical processing of housing and communal services information is focused on the traditional tasks of management companies, such as the formation of statistics and reporting on resource consumption. It is proposed to pay attention to machine learning methods and intelligent big data analysis technologies.

Pair Programming – Cubic Prediction Model Results for Random Pairs and Individual Junior Programmers

Due to the rapidly evolving technology in the dynamic world, there is a growing desire among software clients for swift delivery of high-quality software. Agile software development satisfies this need and has been widely and appropriately accepted by software professionals. The maintainability of such software, however, has a significant impact on its quality. Unfortunately, existing works neglected to consider timely delivery and instead concentrated primarily on the flexibility component of maintainability. This research looked at maintainability as a function of time to rectify codes among Individual Junior and Random pair software developers. Data was acquired from an experiment performed on software developers in the agile environment and analyzed to develop the quality model metrics for maintainability which was used for prediction. One hundred programmers each received a set of agile codes created in the Python programming language, with deliberate bugs ranging from one to ten. The cubic regression model was used for predicting time spent on debugging errors above ten bugs. Results show that the random pair programmers spent an average time of 21.88 min/error while the individual programmers spent a lesser time of 16.57 min/error.

Software systems supporting remote education – Fuzzy assessment using a multi-criteria group decision-making method

During the COVID-19 pandemic, the demand for systems supporting remote education increased significantly, and after the pandemic this form of education remained in place to supplement the stationary education. Among the tools that comprehensively support remote learning, there are two most popular systems, i.e. Google Workspace for Education and Microsoft Office 365, available in several different variants, differing in the functionalities offered. The aim of the article is to analyse the functionality, as well as to compare and evaluate this software. Since the assessment of e-learning systems is based on the subjective judgements of experts, and the assessment criteria are qualitative in nature, a new MCGDM (Multi-Criteria Group Decision Making) method called NEAT F-PROMETHEE GDSS (New Easy Approach To Fuzzy PROMETHEE – Group Decision Support System) was developed for the purposes of the study. This method captures the uncertain and imprecise qualitative assessments expressed by many experts and aggregates them into an overall quantitative assessment. As a result of the assessment, it was found that all variants of Google Workspace for Education and Microsoft Office 365 meet the basic requirements for tools for conducting remote learning. In addition, the use of the NEAT F-PROMETHEE GDSS method made it possible to create a ranking of individual software variants. Based on the group evaluation, it was determined that the best system in terms of the relationship between the offered capabilities and the cost of use is Google Workspace for Education Plus, with other variants of Google Workspace for Education taking subsequent positions in the ranking. In turn, Microsoft Office 365 solutions received a worse group rating, largely due to the higher cost of use and slightly less ability to control student work.

The use of mobile applications in logistics of services

The article focuses on the importance of mobile applications in enterprises with a focus on logistics in the service sector. In the theoretical part, individual software applications in the field of occupational health and safety, fire protection, which are used in Slovakia and the Czech Republic are clearly described. The article contains a brief overview of the legislative regulations on the basis of which the obligations for management decisions in enterprises arise. A telephone survey was conducted in 110 micro, small and medium-sized enterprises between 2022 and 2023 in order to determine the use of software solutions in ensuring the fulfilment of obligations in the field of occupational safety and health and fire protection. To collect data, research questions were set and a questionnaire was developed, which included 6 merit questions, identification questions and a specific question aimed at finding out the prioritisation of the most preferred mobile application features in the study area. The questions were closed-ended, with options where the respondent could choose only one answer. SPSS for Windows version 21.0 was used for statistical analysis and processing of the collected data. We used methods of statistical description, analysed using relative abundance, arithmetic mean, standard deviation and median. At the level of statistical inference, we used chi-square goodness-of-fit tests to analyse categorical variables. We also used nonparametric tests, Friedman analysis of variance, 3D pie charts, and 3D group bar charts. We found that business representatives had a significantly higher preference for the functionality "record of initial and recurrent BOZP and PO training", followed by the second most preferred functionality "OSH inspections and fire prevention inspections". The research focused on logistics enterprises.

MT-SOTA: A Merkle-Tree-Based Approach for Secure Software Updates over the Air in Automotive Systems

The automotive industry has seen a dynamic transformation from traditional hardware-defined to software-defined architecture enabling higher levels of autonomy and connectivity, better safety and security features, as well as new in-vehicle experiences and richer functions through software and ongoing updates of both functional and safety-critical features. Service-oriented architecture plays a pivotal role in realizing software-defined vehicles and fostering new business models for OEMs. Such architecture evolution demands new development paradigms to address the increasing complexity of software. This is crucial to guarantee seamless software development, integration, and deployment—all the way from cloud or backend repositories to the vehicle. Additionally, it calls for enhanced collaboration between car manufacturers and suppliers. Simultaneously, it introduces challenges associated with the necessity for ongoing updates and support ensuring vehicles remain safe and up to date. Current approaches to software updates have primarily been implemented for traditional vehicle architectures, which mostly comprise specialized electronic control units (ECUs) designed for specific functions. These ECUs are programmed with a single comprehensive executable that is then flashed onto the ECU all at once. Different approaches should be considered for new software-based vehicle architectures and specifically for ECUs with multiple independent software packages. These packages should be updated independently and selectively for each ECU. Thus, we propose a new scheme for software updates based on a Merkle tree approach to cope with the complexity of the new software architecture while addressing safety and security requirements of real-time and resource-constrained embedded systems in the vehicle. The Merkle-tree-based software updates over the air (MT-SOTA) proposal enables secure updates for individual software clusters. These clusters are developed and integrated by diverse entities with varying release timelines. Our study demonstrates that the MT-SOTA scheme can enhance the speed of software update execution without significantly increasing the process overhead. Additionally, it offers necessary defense against potential cyberthreats. The results of the performed technical analysis and experiments of the MT-SOTA implementation are presented in this paper.

Challenges of Working from Home in Software Development During Covid-19 Lockdowns

The COVID-19 pandemic in 2020/2021/2022 and the resulting lockdowns forced many companies to switch to working from home, swiftly, on a large scale, and without preparation. This situation created unique challenges for software development, where individual software professionals had to shift instantly from working together at a physical venue to working remotely from home. Our research questions focus on the challenges of software professionals who work from home due to the COVID-19 pandemic, which we studied empirically at a German bank. We conducted a case study employing a mixed methods approach. We aimed to cover both the breadth of challenges via a quantitative survey, as well as a deeper understanding of these challenges via the follow-up qualitative analysis of 15 semi-structured interviews. In this article, we present the key impediments employees faced during the crisis, as well as their similarities and differences to the known challenges in distributed software development (DSD). We also analyze the employees’ job satisfaction and how the identified challenges impact job satisfaction. In our study, we focus on challenges in communication, collaboration, tooling, and management. The findings of the study provide insights into this emerging topic of high industry relevance. At the same time, the study contributes to the existing academic research on work from home and on the COVID-19 pandemic aftermath.

Big Data for the Social Good: The Drought Early-Warning Experience Report

Data deluge is growing exponentially, but the consumption of the data is not growing at the same pace. DataOps is an emerging family of techniques and tools that harnesses the potential of data continuously whilst incrementally using complex cloud systems orchestration techniques. This paper offers a proof-of-concept implementation of a DataOps pipeline for the social good. Specifically, we prototype—using a combined field-lab Action Research and Design Science approach—a DataOps system to incrementally and iteratively mitigate the devastating effects of droughts for high-risk areas. The context of our study is a game reserve in the Waterberg area in the province Limpopo in South Africa. The objective of this paper is threefold: to (1) develop and study a proof of concept for DataOps, by (2) exploring the applicability of individual software components in a complex and large-scale continuous pipeline, and, finally (3) elaborate on the spatial classification of such components in a new-frontier Drought Early-Warning System (DEWS). As a result, we offer an overview of the challenges and opportunities laid bare by our experimentation in a complex societal scenario while combining Artificial Intelligence and DataOps technologies. We conclude that a combined model of local, regional, and global data performs best on all tests within a stakeholder-acceptable timeframe.

Software compatibility analysis for quantitative measures of [18F]flutemetamol amyloid PET burden in mild cognitive impairment

RationaleAmyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods.MethodsComposite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software’s MIMneuro, Syntermed’s NeuroQ, Hermes Medical Solutions’ BRASS and GE Healthcare’s CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores.ResultsUsing an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss’) and individual software pairings (Cohen’s), were ≥ 0.9 signifying “almost perfect” inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957–0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r2 = 0.98).ConclusionUsing an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.