Modern Software Research Articles

The Advanced Computing Hub at BSC: Improving fusion codes following modern software engineering standards

Abstract Several dedicated High-Performance Computing (HPC) centers provide essential expertise and support in developing a suitable portfolio of EUROfusion standard codes. Barcelona Supercomputing Center (BSC) is one of these HPC hubs involved in this complex task. Several fusion codes were selected, installed and analyzed to meet the developers’ requirements, ranging from portability to GPU, improving the performance, getting better data management, extending the capacity of coupling with other codes, etc. In this paper, we will describe the work developed by BSC and some of the tasks carried out in this project. We will explain briefly how the project is faced and the work required to create good quality codes, i.e. robust and trustable software capable of running efficiently in modern HPC systems.

Applications of AI

Abstract: Artificial Intelligence (AI) is a revolution in computer science that will become an integral part of all modern software in the coming years and decades. This situation creates opportunities as well as threats. Artificial intelligence will be used to improve defense and cybercrime. Additionally, new cyberattack techniques have been developed to exploit specific weaknesses in intelligence technology. Artificial intelligence is a broad field of computing that enables understanding, reasoning and action. The amount of information created by humans and machines today exceeds the human ability to absorb this information, interpret it and make complex decisions based on it. This article explores the characteristics, uses, development and success of artificial intelligence.

Unleashing the Power of DevOps : Revolutionizing Software Development Practices

The integration of development and operations, popularly known as DevOps, has emerged as a transformative force in modern software development practices. This review paper delves into the multifaceted landscape of DevOps, exploring its principles, methodologies, and the profound impact it has on software development processes. Through an examination of historical evolution, cultural shifts, and technological advancements, the paper elucidates how DevOps fosters collaboration, automation, and continuous improvement across the software development lifecycle. Furthermore, it investigates the challenges and opportunities associated with implementing DevOps practices, including cultural barriers, security considerations, and the adoption of cloud technologies. By synthesizing insights from industry best practices, case studies, and academic research, this paper provides a comprehensive overview of the principles and practices that underpin the successful adoption of DevOps. Ultimately, it underscores the potential of DevOps to revolutionize software development, empowering organizations to deliver high-quality software products with speed, efficiency, and agility.

Changing Trends in Teaching Computer Vision at Ukrainian Universities in the Age of Artificial Intelligence

In recent years, professional education in computer vision and artificial intelligence (AI) has witnessed transformative changes, a process significantly accelerated by the COVID-19 pandemic, which catalyzed the shift towards online learning formats. In Ukraine, as in many other countries, universities have rapidly adapted their curricula to align with these new realities. The onset of martial law in Ukraine further entrenched online learning as the dominant mode of education. Additionally, there has been a noticeable shift in research activities towards projects tailored to the defense sector, unfolding against the backdrop of significant global advancements in AI for computer vision. This article explores the impact of these shifts and the “Artificial Intelligence Development Concept” introduced by the Ministry of Digital Transformation of Ukraine on the quality and methodologies of computer vision education. It scrutinizes specific training courses in this domain, along with the literature used in the educational process. The exploration includes how deep neural network technologies such as TensorFlow, PyTorch, OpenCV, and Python libraries are being integrated into computer vision curricula, reflecting the latest advancements in the field. It also examines the needs of Ukrainian startups and companies specializing in computer vision projects, analyzing how curricula are evolving to meet the specific requirements of modern software developers. Furthermore, the article proposes directions for the further development of online education in computer vision teaching in Ukraine.

Modern software and physical education: can online training enhance gym training?

BackgroundThis study discusses the effectiveness of a 12-week intervention aimed at improving squat jump and sprint performance among second-year sports students.MethodsThe students were randomly divided into experimental (n = 89) and control (n = 92) groups. In addition to gym training, students of the experimental group also underwent online PE training. The students’ performance in Squat Jumps, 30 m sprint, and Progressive Aerobic Cardiovascular Endurance Run (PACER), as well as their situational motivation, were assessed before and after the intervention. Furthermore, the students assessed their physical activity weekly using self-reports.ResultsThe implementation of online training has positively impacted intrinsic and identified motivation, as well as external regulation; however, it was less effective in reducing amotivation compared to traditional gym-based training.ConclusionsThe findings of the study contribute to the data synthesis on the expediency of using modern software in physical education.

КОМПЛЕКС АЛГОРИТМОВ ОПТИМАЛЬНОГО ПРОЕКТИРОВАНИЯ И ОЦЕНКИ ЭФФЕКТИВНОСТИ ВИЗУАЛЬНОЙ СОСТАВЛЯЮЩЕЙ ГРАФИЧЕСКИХ ПОЛЬЗОВАТЕЛЬСКИХ ИНТЕРФЕЙСОВ

Modernity is characterized by comprehensive digitalization, leading to an increase in the number of software products, an integral part of which are graphical user interfaces, which act as an intermediary between users and software algorithms, allowing them to comfortably and efficiently perform the required tasks. Most modern software products have low-efficiency interfaces, which leads to a decrease in the performance of users and an increase in intrapsychological stress on them. In order to improve the efficiency of interfaces, this article describes the formulation of the problem of developing a set of algorithms for optimal design and evaluation of the effectiveness of the visual component of graphical user interfaces.
 To develop a set of algorithms, this article presents a range of proprietary indicators for each of the areas, as well as an analysis of existing quantitative methods for assessing the effectiveness of interfaces for the possibility of using them to calculate the indicators mentioned above. It is concluded that existing approaches are capable of providing a formalized representation of only part of the author’s indicators.
 The planned set of algorithms, after implementation, will hypothetically allow for a comprehensive assessment of interfaces, as well as finding defects in them that reduce their effectiveness, which, if eliminated, will improve the quality of both interfaces and programs 
 in general, increasing the performance and comfort of interaction with user programs.

Examining Differential Item Functioning from a Multidimensional IRT Perspective.

Differential item functioning (DIF) is a standard analysis for every testing company. Research has demonstrated that DIF can result when test items measure different ability composites, and the groups being examined for DIF exhibit distinct underlying ability distributions on those composite abilities. In this article, we examine DIF from a two-dimensional multidimensional item response theory (MIRT) perspective. We begin by delving into the compensatory MIRT model, illustrating and how items and the composites they measure can be graphically represented. Additionally, we discuss how estimated item parameters can vary based on the underlying latent ability distributions of the examinees. Analytical research highlighting the consequences of ignoring dimensionally and applying unidimensional IRT models, where the two-dimensional latent space is mapped onto a unidimensional, is reviewed. Next, we investigate three different approaches to understanding DIF from a MIRT standpoint: 1. Analytically Uniform and Nonuniform DIF: When two groups of interest have different two-dimensional ability distributions, a unidimensional model is estimated. 2. Accounting for complete latent ability space: We emphasize the importance of considering the entire latent ability space when using DIF conditional approaches, which leads to the mitigation of DIF effects. 3. Scenario-Based DIF: Even when underlying two-dimensional distributions are identical for two groups, differing problem-solving approaches can still lead to DIF. Modern software programs facilitate routine DIF procedures for comparing response data from two identified groups of interest. The real challenge is to identify why DIF could occur with flagged items. Thus, as a closing challenge, we present four items (Appendix A) from a standardized test and invite readers to identify which group was favored by a DIF analysis.

Unit Testing in ASP Revisited: Language and Test-Driven Development Environment

Abstract Unit testing frameworks are nowadays considered a best practice, included in almost all modern software development processes, to achieve rapid development of correct specifications. Knowledge representation and reasoning paradigms such as Answer Set Programming (ASP), that have been used in industry-level applications, are not an exception. Indeed, the first unit testing specification language for ASP was proposed in 2011 as a feature of the ASPIDE development environment. Later, a more portable unit testing language was included in the LANA annotation language. In this paper we revisit both languages and tools for unit testing in ASP. We propose a new unit test specification language that allows one to inline tests within ASP programs, and we identify the computational complexity of the tasks associated with checking the various program-correctness assertions. Test-case specifications are transparent to the traditional evaluation, but can be interpreted by a specific testing tool. Thus, we present a novel environment supporting test-driven development of ASP programs.

К вопросу о смертности населения и проблемах здравоохранения в сельских поселениях.

In the Russian Federation, the problem of reducing population mortality, incl. in rural settlements. Strategic guidelines and initiatives adopted in regulatory documents at the federal level do not reflect the severity and depth of demographic challenges and processes of depopulation in modern conditions. The purpose of this study is to analyze current trends and mortality trends in rural areas in Russia, as well as health problems in rural areas, and make appropriate recommendations and adjustments. Materials and methods. At all stages of the study, analytical materials from official statistics (Rosstat and the Ministry of Health of the Russian Federation), data from modern literature sources and regulatory documents were used; processing of statistical data was carried out based on modern software packages SPSS, Excel‑2007. Research methods – study and generalization of experience, statistical, bibliographic. Results. Analysis of the accumulated data showed trends in the mortality of the rural population; specific areas and features inherent in rural healthcare and requiring special attention considering new challenges in the system were clearly shown and systematized. Conclusions. The data obtained can be applied when adjusting and recommendations to existing regional programs operating within the framework of preserving and strengthening the health of the rural population in the territory.

Design and Implementation of Educonnect: A Cloud Native Application for Educational Institutions

Abstract: In modern software environments, a paradigm known as the MERN stack has emerged as an important force due to its breadth of development and management capabilities. Leveraging native MERN (MongoDB, Express.js, React.js, Node.js) software development, deployment, and management techniques with Cloud services, "Educonnect" emerges as an innovative solution for educational institutions seeking efficient and cost-effective data management. This paper deals with the implementation of a cloud native web application Educonnect after a dexterous development strategy to create a cloud native web application. The main focus of this cloud native application is to provide a solution for data organization and collection along with an effective way of sending communication to the students by using cloud services

Cost Bearing of Individual Project due to Use of Modern Software in Project Management and Detailed Analysis of Same for Making Cost Effective Path

Abstract: Project management in India is witnessing impact of IT Development on its core field. Particularly in India project management had undergone lot of changes. Post industrialisation era demand of skilled project management had reached a statutory requirement. Introduction of RERA enforced private developer and builders to develop the project in stipulated time. The requirement of quick update, organised effort, errorless drawing and documentations, integrated approach demanded use of IT infrastructure alike other Field. As per the other infrastructure Cost of modern use of Software’s demanded Financial Planning and Consideration for Annual basis. The study aims at study of IT infrastructure required for individual project. To list out strategies to control this cost and make a cost-effective way.

Survivability Prediction of Open Source Software with Polynomial Regression

In modern software development, OSS (Open Source Software) has become a crucial element. However, if OSS have few contributors and are lacking in maintenance activities, such as bug fixes, are used, it can lead to significant costs and resource allocation due to maintenance discontinuation. Since OSS are developed by a diverse group of contributors, the consistency of their involvement may vary, making continuous support and maintenance unpredictable. Therefore, it is necessary to identify the status of each OSS to avoid increased maintenance costs when selecting OSS for use. To address these issues, we use polynomial regression to predict trends in bug-fixing activities and evaluate the survivability of OSS accordingly. We predict the trend of bug-fixing activities in OSS, using factors such as popularity, number of contributors, and code complexity. A lower trend value indicates more vigorous activity. In this paper, we conduct data collection and extraction, generating model, and model testing and evaluation to predict survivability using these data. After collecting data through various tools, the models of different degrees are generated using K-fold cross-validation. The model with the highest performance is selected based on the RMSE (Root Mean Squared Error) and RSE (Residual Standard Error). Then, the chosen model is employed to predict the survivability of OSS and compare it with actual outcomes. This method is experimented with on OSS used in the KakaoTalk commercial messenger app. As a result, several OSS are predicted to have low survivability, and among them, five are analyzed. It is observed that, in reality, activities such as delayed or discontinued release updates occurred. These findings can support OSS users in selecting OSS for cost-saving purposes and alert OSS administrators to the need for solutions to ensure project survival.

An analysis of conventional and modern packaging approaches for cut flowers: a review article.

Fresh-cut flowers are considered to be one of the most delicate and challenging commercial crops. It is important to take into consideration how to minimize loss during storage and transportation when preserving cut flowers. Many impinging (bad effect) forces can interact to shorten the flowers' vase life. In the flower industry, effective methods need to be developed to extend freshly cut flowers' life. Fresh-cut flowers' vase life can be shortened by a variety of interlocking causes. The flower industry must develop new techniques to extend the flowers' vase lifespan. This review provides comprehensive, up-to-date information on classical, modified atmosphere packaging (MAP), and controlled atmosphere packaging (CAP) displays. According to this review, a promising packaging technique for fresh flowers can be achieved through smart packaging. A smart package is one that incorporates new technology to increase its functionality. This combines active packaging, nanotechnology, and intelligence. This technology makes it easier to keep an eye on the environmental variables that exist around the packaged flowers to enhance their quality. This article offers a comprehensive overview of creative flower-saving packaging ideas that reduce flower losses and assist growers in handling more effectively their flower inventory. To guarantee the quality of flowers throughout the marketing chain, innovative packaging techniques and advanced packaging technologies should be adopted to understand various package performances. This will provide the consumer with cut flowers of standard quality. Furthermore, sustainable packaging is achieved with circular packaging. We can significantly reduce packaging waste's environmental impact by designing reused or recyclable packaging.

COMPUTATIONAL MODELING OF A FOOD PACKAGING USING FINITE ELEMENTS

Food packaging has, among others, the main function of protecting food from external biochemical contamination. Nowadays, packages can be formed by different combinations of materials in order to maximize the barrier against external agents, so ensuring food safety. This naturally leads to understand modern packages as multilayer objects, with different characteristics and purposes. In this work, it’s intended to simulate the diffusion of oxygen (responsible for the oxidation of food) in a package consisting of three polymeric materials (in ABA and ABC format) by means of a mathematical model, which resulted in a partial differential equation to be solved, along with initial and boundary conditions. Then, a Finite Element Method (FEM) implementation was devised using Fortran 77, not only to get results for the firstly chosen materials, but also to try other polymer combinations, thus generating different sets of data that could be compared further.

DEVELOPMENT OF A PROCESS AUTOMATION SYSTEM FOR HEATING, VENTILATION AND AIR CONDITIONING FOR THE FOOD INDUSTRY ON THE BASIS OF HONEYWELL EQUIPMENT

Currently, the development of industrial automation makes it possible to implement high-precision control systems that consider the dynamic properties of complex objects. The construction of distributed control systems based on modern software products provides decentralized management of technological processes. The modernization of existing control systems with the help of modern industrial equipment makes it possible to increase the productivity of enterprises and safety at work. This study is devoted to the development of an automated control system for heating, ventilation, and air conditioning processes for the food industry. In this study, a heat exchanger was selected as the control object. A mathematical model of the control object for stability, controllability, and observability was investigated. A PID regulator was synthesized, and its coefficients of the PID regulator were obtained. A comparative analysis of the behavior of the system dynamics at different regulator coefficients was carried out. The results of the modeling and experiments were carried out using real industrial equipment at the Honeywell laboratory at JSC KBTU. Software implementation was carried out using the Experion PKS distributed control system. The configuration of the C300 controller is presented. A Safety Instrumented System (SIS) was developed for the safe and trouble-free operation of the system. SIS was also developed using the Safety Manager and Safety Controller tools. Risk reduction factors (RRF) and Safety Integrity Level (SIL) were calculated and analyzed. A process-controlled mnemonic was developed.

AdaCCD: Adaptive Semantic Contrasts Discovery Based Cross Lingual Adaptation for Code Clone Detection

Code Clone Detection, which aims to retrieve functionally similar programs from large code bases, has been attracting increasing attention. Modern software often involves a diverse range of programming languages. However, current code clone detection methods are generally limited to only a few popular programming languages due to insufficient annotated data as well as their own model design constraints. To address these issues, we present AdaCCD, a novel cross-lingual adaptation method that can detect cloned codes in a new language without annotations in that language. AdaCCD leverages language-agnostic code representations from pre-trained programming language models and propose an Adaptively Refined Contrastive Learning framework to transfer knowledge from resource-rich languages to resource-poor languages. We evaluate the cross-lingual adaptation results of AdaCCD by constructing a multilingual code clone detection benchmark consisting of 5 programming languages. AdaCCD achieves significant improvements over other baselines, and achieve comparable performance to supervised fine-tuning.

The Data Product-service Composition Frontier: A Hybrid Learning Approach

The service dominant logic is a base concept behind modern economies and software products, with service composition being a well-known practice for companies to gain a competitive edge over others by joining differentiated services together, typically assembled according to a number of features. At the other end of the spectrum, product compositions are a marketing device to sell products together in bundles that often augment the value for the customer, e.g., with suggested product interactions, sharing, and so on. Unfortunately, currently each of these two streams—namely, product and service composition—are carried out and delivered individually in splendid isolation: anything is being offered as a product and as a service, disjointly. We argue that the next wave of services computing features more and more service fusion with physical counterparts as well as data around them. Therefore a need emerges to investigate the interactive engagement of both (data) products and services. This manuscript offers a real-life implementation in support of this argument, using (1) genetic algorithms (GA) to shape product-service clusters, (2) end-user feedback to make the GAs interactive with a data-driven fashion, and (3) a hybridized approach which factors into our solution an ensemble machine-learning method considering additional features. All this research was conducted in an industrial environment. With such a cross-fertilized, data-driven, and multi-disciplinary approach, practitioners from both fields may benefit from their mutual state of the art as well as learn new strategies for product, service, and data product-service placement for increased value to the customer as well as the service provider. Results show promise but also highlight plenty of avenues for further research.

Analysis of the Impact of Cybersecurity on the Stability of Financial Institutions

"The issue of the impact of cybersecurity is a top priority for the functioning of a financial institution. Therefore, its provision becomes a priority in organizing the further activities of the institution itself. The article aims to analyze the current trends in ensuring the cybersecurity of financial institutions and its role in their functioning. The paper describes the theoretical foundations of the cyber protection concept. The authors also outline the specifics of cybersecurity and the leading technological solutions for achieving these goals. Special attention is paid to modern, innovative solutions to maintain the stability of financial institutions and the possibility of further development. An important area of research is the disclosure of the practical experience of information corporations in providing technical solutions to ensure the security of financial transactions and support the global financial system. The study presents the experience of Ukrainian financial institutions that use variable digital defense strategies and maintain their functionality based on an effective cybersecurity system in the context of a global military conflict. The results of the study include a detailed profile of effective practical solutions to ensure the stability of financial institutions based on the implementation of blockchain technologies. The authors pay attention to the issue of modern software, hardware, and management solutions to improve the quality of cybersecurity in the context of growing cyberattacks and digital threats to the stability of financial institutions. The research findings may be helpful for further analytical studies on the effectiveness of cybersecurity and the stability of financial institutions."

DEVELOPMENT OF A CYBERPHYSICAL SYSTEM FOR MONITORING FIRE SAFETY

The Megamart company's cyber-physical fire safety system was developed with the possibility of flexible changing types and sets of functions performed by reprogramming. system uses RFID technology with the development of a computer network. The computer system allows for the system's technical and software modernization, as well as ensures the fulfillment of all functions of the technical assignment. The system was validated using a model of the corporate network scheme using the program Cisco Packet Tracer program.

Algorithm for Surface Wave Suppression on 2D Seismic Data Using the Slant Karhunen–Loeve Transform in a Time-Frequency Domain

Abstract —Surface waves are the main source of coherent noise in land seismic survey, and their suppression is one of the main stages of common depth point data processing designed to improve the quality of tracking primary reflections on time sections. In practice, noise reduction is carried out using procedures from modern software based on numerical modeling of waveforms. However, they are too resource-intensive and have a large number of subjectively customizable parameters. The known algorithms have a common drawback: either the energy of reflected waves is distorted in an interference zone with a noise wave or the noise suppression quality is unsatisfactory. The current research is aimed at improving the filtering algorithm in a time-frequency domain using the slant Karhunen–Loeve transform in order to overcome these limitations, to increase the accuracy and rate of its software implementation, and also to test it when processing profile field data from land-based 2D seismic surveys. The algorithm is modified by developing a new method for determining static corrections for surface wave hodograph rectification in a time-frequency domain and by the application of preprocessing in which the reflected wave signal is removed preliminarily. These and other modifications ensure faster calculations and improve the quality of surface wave interference suppression. In addition, the slant Karhunen–Loeve transform is accelerated by parallelizing calculations across logical processor cores. In this paper, the algorithm is described in detail, its significant advantage over the standard methods of bandpass filtering and F–K filtering is shown, and the results of processing the field data obtained by the SWANA procedure (Geovation 2.0) and by the slant Karhunen–Loeve transform. The result obtained by the slant Karhunen–Loeve transform is superior to the SWANA procedure in terms of the surface wave filtering quality and has only four adjustable parameters (SWANA has 20 parameters)