Programming Environment Research Articles

Measures to increase the reliability and efficiency of water supply and wastewater disposal systems

The reliability of water supply and wastewater disposal systems has a significant impact on the environment: therefore, it is essential to implement new methods and approaches that reduce the risk of emergency situations. Based on the experience in automation, maintenance and modernization of wastewater disposal and water supply systems, the study suggests introducing additional programmable modules into automated control systems that provide control and regulation directly on the actuator. For this purpose, the study involves OWEN Logic programming environment, which manages pumping stations through programmable relays. The paper presents functional diagrams that have been introduced into standard macros to increase the reliability of pumping units. In addition, the paper demonstrates that the implementation of multi-level management facilitates the improvement of existing water supply and wastewater disposal systems, thereby increasing their functional capabilities and ensuring the efficient operation of technological equipment. The conducted analysis shows that the adoption of this method for managing technological processes will enhance the reliability and durability of the equipment, ensuring uninterrupted operation of pumping stations. With a change in the performance of water supply and wastewater disposal systems, the installed devices will allow for modernization with minimal economic costs, and reprogramming the operation of the low-level automation without affecting the performance of other levels.

Optimization of seismic insulation parameters of frame buildings using adaptive methods

Objective. The purpose of the work is to calculate frame buildings with flexible connections and with flexible and switch-off connections, to make recommendations for the use of seismic insulation methods depending on the characteristics of seismic events. Method. Development of an algorithm for calculating frame buildings of a frame structural system with seismic protection in buildings with flexible connections and with flexible and switchable connections Result. A method for calculating frame buildings of a frame structural system with seismic insulation in the form of flexible connections and flexible and switchable connections has been developed. A computer calculation program for seismically insulated and nonseismically insulated frame buildings in the Delphi 5.0 programming environment in the Object Pascal language using the Runge-Kutta numerical method of the 4th order for solving differential equations has been compiled Conclusion. It is determined that the construction of frame buildings with the seismic insulation methods considered in this paper, namely with flexible connections and with flexible connections and disconnecting connections, is not impractical for territories where long-period fluctuations are possible, due to the fact that excessively high deformations occur.

The design space of visualization tools for data science education: literature review and framework for future designs

Data science education is a rapidly growing field, motivating the development of several tools aimed at engaging students in data-related activities across all educational levels. Within this landscape, new block-based programming (BBP) environments have been developed to integrate data visualization functionalities. However, the construction of visualizations entails distinct goals and forms of interaction from those typically used in conventional programming, which should be considered in designing those environments. Drawing inspiration from taxonomies within the field of Information Visualization, we derived a framework for the analysis of educational tools in this domain comprising four categories: supported goals, expressiveness, abstraction, and transparency. We situate six existing BBP environments within the design space of the framework and illustrate its application by describing the design of [anonymized tool], a BBP environment developed to address a gap in data visualization tools for young audiences. Our goal is to contribute to a more theoretically grounded discussion on the topic by bridging the gap between well-established research on professional tools for data visualization and the design of related educational environments targeted at middle and high school students.

2D23D: 3D images from 2D images using statistical filters and color shading

Below is the development of an algorithm that allows generating 3D models from 2D images for analysis and visualization, with an application focused on images from the health and space sectors, domains chosen for their contrast characteristics. The characteristics used in the project are presented and determined, as well as 3D programming and visualization environment tools that allow the generation of voxel depth, as well as the management of image formats from the medical or spatial sector, including the results obtained with images. from both sectors, from which the 3D models were created.

Advances in ovarian cancer radiomics: a bibliometric analysis from 2010 to 2024.

Ovarian cancer, a leading cause of death among gynecological malignancies, often eludes early detection, leading to diagnoses at advanced stages. The objective of this bibliometric analysis is to map the landscape of ovarian cancer radiomics research from 2010 to 2024, emphasizing its growth, global contributions, and the impact of emerging technologies on early diagnosis and treatment strategies. A comprehensive search was conducted using the Web of Science Core Collection (WoSCC), focusing on publications related to radiomics and ovarian cancer within the specified period. Analytical tools such as VOSviewer and CiteSpace were employed to visualize trends, collaborations, and key contributions, while the R programming environment offered further statistical insights. From the initial dataset, 149 articles were selected, showing a significant increase in research output, especially in the years 2021-2023. The analysis revealed a dominant contribution from China, with significant inputs from England. Major institutional contributors included the University of Cambridge and GE Healthcare. 'Frontiers in Oncology' emerged as a crucial journal in the field, according to Bradford's Law. Keyword analysis highlighted the focus on advanced imaging techniques and machine learning. The steady growth in ovarian cancer radiomics research reflects its critical role in advancing diagnostic and prognostic methodologies, underscoring the potential of radiomics in the shift towards personalized medicine. Despite some methodological challenges, the field's dynamic evolution suggests a promising future for radiomics in enhancing the accuracy of ovarian cancer diagnosis and treatment, contributing to improved patient care and outcomes.

Modelarea matematică și simularea asistată de calculator a sistemelor mecanice cu multe grade de libertate

The vast majority of phenomena and processes in nature for which computer-assisted simulation is of scientific and methodical-didactic interest, from a mathematical point of view, are described by systems of differential equations of the second order. In this context, the paper describes and implements in the Object Pascal programming language an original algorithm for the numerical solution of systems of differential equations of the second order. Interactive simulation applications are made in the Delphi programming environment (FMX variant). Based on the examples, described in detail in the paper, users can perform interactive simulation activities for any processes, which from a mathematical point of view are described by systems of differential equations of the second degree.

CONSIDERATIONS ON THE ANALYSIS OF THE OPERATING CHARACTERISTICS OF THE HORIZONTAL SYNCHRONOUS MOTORS EQUIPPING THE HYDRO AGGREGATES IN HIGH-POWER ENERGY PUMPING STATIONS

In this paper, the authors present modelling and analysis of the operating characteristics of the synchronous motor with electromagnetic excitation, for driving the centrifugal pump that equips hydro aggregates in high-power energy pumping stations, motor powered from fixed or adjustable voltage sources. Two operating scenarios were considered, namely: the stationary operation of the synchronous motor fed from an ideal, controllable voltage source and the case of its supply from the industrial network. For solving, algorithms and calculation programs developed in the Mathcad programming environment were designed. For example, a representative case study of one of the three identical hydro aggregates from one of a high-power energy pumping station of an existing hydropower facility in Romania was chosen. The hydro aggregate is driven by a horizontal synchronous motor with electromagnetic excitation powered at medium voltage (6 kV).

IMPLEMENTATION OF SIMOYU METHOD FOR MODELING OF TRANSIENTS OF CONTROL OBJECT

In this paper transients in the control system are investigated on the basis of experimental data. The construction of the transfer function of the control object using Simoyu method is realized by means of Python language. The model of the control system of the object, selection of the regulator and its settings are implemented using SimInTech modeling environment. Within the framework of the conducted research, methodological approaches to the formation of transfer functions of control objects represented in the form of polynomial expressions of various degrees of complexity, starting with polynomials of the first degree in the numerator and the second degree in the denominator, and ending with polynomials of the second degree in the denominator against the third degree in the numerator, have been developed and tested. A procedure for reading data in CSV format was used to build the Python program interface, which helped to simplify the integration of experimental results with analytical tools, providing a powerful platform for subsequent analysis, visualization, and interpretation of the resulting transfer functions. The procedures of debugging and optimization of the technique of visualization of results and estimation of calculation errors have been carried out, which allowed to provide a visual representation of data and high accuracy of the obtained transfer functions. In contrast to the known analytical studies in the field of differential equations describing transient processes, the use of numerical methods implemented by means of Python libraries and programming environments, in particular SimInTech, allows to simplify the analysis of transient processes of control objects.

The statistical building blocks of animal movement simulations.

Animal movement plays a key role in many ecological processes and has a direct influence on an individual's fitness at several scales of analysis (i.e., next-step, subdiel, day-by-day, seasonal). This highlights the need to dissect movement behavior at different spatio-temporal scales and develop hierarchical movement tools for generating realistic tracks to supplement existing single-temporal-scale simulators. In reality, animal movement paths are a concatenation of fundamental movement elements (FuMEs: e.g., a step or wing flap), but these are not generally extractable from a relocation time-series track (e.g., sequential GPS fixes) from which step-length (SL, aka velocity) and turning-angle (TA) time series can be extracted. For short, fixed-length segments of track, we generate their SL and TA statistics (e.g., means, standard deviations, correlations) to obtain segment-specific vectors that can be cluster into different types. We use the centroids of these clusters to obtain a set of statistical movement elements (StaMEs; e.g.,directed fast movement versus random slow movement elements) that we use as a basis for analyzing and simulating movement tracks. Our novel concept is that sequences of StaMEs provide a basis for constructing and fitting step-selection kernels at the scale of fixed-length canonical activity modes: short fixed-length sequences of interpretable activity such as dithering, ambling, directed walking, or running. Beyond this, variable length pure or characteristic mixtures of CAMs can be interpreted as behavioral activity modes (BAMs), such as gathering resources (a sequence of dithering and walking StaMEs) or beelining (a sequence of fast directed-walk StaMEs interspersed with vigilance and navigation stops). Here we formulate a multi-modal, step-selection kernel simulation framework, and construct a 2-mode movement simulator (Numerus ANIMOVER_1), using Numerus RAMP technology. These RAMPs run as stand alone applications: they require no coding but only the input of selected parameter values. They can also be used in R programming environments as virtual R packages. We illustrate our methods for extracting StaMEs from both ANIMOVER_1 simulated data and empirical data from two barn owls (Tyto alba) in the Harod Valley, Israel. Overall, our new bottom-up approach to path segmentation allows us to both dissect real movement tracks and generate realistic synthetic ones, thereby providing a general tool for testing hypothesis in movement ecology and simulating animal movement in diverse contexts such as evaluating an individual's response to landscape changes, release of an individual into a novel environment, or identifying when individuals are sick or unusually stressed.

AI and Cloud Computing in Healthcare: Transforming Patient Care with AWS and Java

A new era in healthcare is being ushered in by the convergence of artificial intelligence (AI) and cloud computing, which will significantly improve patient care through improved diagnosis, individualized treatment planning, and effective patient management. This article explores the potent combination of Java and Amazon Web Services (AWS) and how these technologies may be used to develop cutting-edge AI-driven healthcare solutions that optimize healthcare operations and dramatically enhance patient outcomes. Together with Java's robust and flexible programming environment, healthcare providers can leverage AWS's scalable infrastructure and advanced machine learning capabilities to create and implement sophisticated AI models that analyze massive amounts of medical data at a speed and accuracy never seen before. These developments are making it possible to make more accurate diagnoses, customized treatment plans, and proactive patient monitoring, which can result in better clinical judgment and possibly life-saving measures. But even as we consider the enormous positive effects these technologies have on society, we also have to face the ethical problems they raise, such as issues with data privacy, potential biases in algorithms, and unequal access to cutting-edge medical treatments.

Approach to Sorting Line Control using PLC and Factory I/O

The article presents the possibility of using a 3D environment to simulate the operation of a manufacturing process and control a virtual object with a PLC. A sample application of the Factory I/O environment compatible with TIA Portal software and the real S7-1214 DC/DC/DC controller is presented. Visualization and program code written in LAD language correlated with the 3D environment were presented. The results showed the importance of a dynamic programming environment that reflects the program code designed to sort virtual production line components. The research showed that working with the code and the virtual object experiences students and is closer to industrial solutions than just laboratory ones.

AI and Cloud Computing in Healthcare: Transforming Patient Care with AWS and Java

A new era in healthcare is being ushered in by the convergence of artificial intelligence (AI) and cloud computing, which will significantly improve patient care through improved diagnosis, individualized treatment planning, and effective patient management. This article explores the potent combination of Java and Amazon Web Services (AWS) and how these technologies may be used to develop cutting-edge AI-driven healthcare solutions that optimize healthcare operations and dramatically enhance patient outcomes. Together with Java's robust and flexible programming environment, healthcare providers can leverage AWS's scalable infrastructure and advanced machine learning capabilities to create and implement sophisticated AI models that analyze massive amounts of medical data at a speed and accuracy never seen before. These developments are making it possible to make more accurate diagnoses, customized treatment plans, and proactive patient monitoring, which can result in better clinical judgment and possibly life-saving measures. But even as we consider the enormous positive effects these technologies have on society, we also have to face the ethical problems they raise, such as issues with data privacy, potential biases in algorithms, and unequal access to cutting-edge medical treatments. The goal of this thorough investigation is to present a fair assessment of the revolutionary potential of artificial intelligence (AI) and cloud computing in the healthcare industry, while also discussing the wider ramifications and obligations associated with incorporating these formidable technologies into our healthcare systems.

Analysis of the Structural Organization of the Human Finger Phalanges Using Anatomical Network Models

Despite the fact that the morphogenetic mechanisms of human finger transformation during ontogenesis are currently known, the issues of how they are organized into a complex integrated structure of the distal hand remains open. This question remains unanswered for several reasons, including the lack of consensus on conceptual definitions and approaches, as well as tools for assessing and comparing variations in several anatomical parts of the hand. The aim of the study was to investigate the structural organization of the human finger phalanges using anatomical network analysis (AnNA). Material and methods. In this study, the authors applied the IGRAPH package functions in the R data analysis programming environment for AnNA. Network modeling and layout were performed using the Fruchterman-Reingold algorithm. Analysis of the structure, as well as modularity and integration in the networks, was performed using the spin-glass algorithm. X-ray osteometric indices of the I–V fingers phalanx length were used to assess AnNA in 100 men and 100 women of the middle age without traumatic changes, deformations, and developmental deviations. Results. AnNA demonstrates a two-level organization of the distal hand in the form of a proximal module including the proximal phalanges and a distal module combining the middle and distal phalanges. When comparing the features of the network models of the distal hand, it was found that in women, the organization of the finger phalanges is characterised by higher morphological integration and modularity (modularity 0.43) than in men (modularity 0.38). orphological modularity and integration are organizing factors in the structure of the finger phalanges of the human distal hand. Conclusion. The study results demonstrate that the structural organization of the finger phalanges of the human hand is a system of individual anatomical modules of the phalanges.

Inversion of Gravity Anomalies by a Hybrid Metaheuristic Algorithm

In this work, we introduce application of a hybrid algorithm (DE/PSO) to estimate the model parameters from residual gravity anomalies due to some simple geometrical bodies. This algorithm combines differential evolution (DE) and particle swarm optimization (PSO). To investigate the performance of the hybrid algorithm, test studies were carried out using synthetic and field data sets. The synthetic data sets include noise-free and noisy synthetic anomalies. Two published gravity anomalies from Cuba and Canada were used as the field data. In the hybrid algorithm, DE and PSO yield [premature] solutions separately and share their best solutions during an iterative process. An openly accessible metaheuristics package (NMOF) in R programming environment was used to implement the hybrid algorithm. Through simulations using synthetic anomalies, DE/PSO algorithm was successful to provide improved results. In comparison to the solutions from the single algorithms (DE and PSO), the DE/PSO algorithm shows more effectiveness in terms of accuracy and convergence. The true model parameters of noise-free and noisy synthetic gravity anomalies were recovered well by the hybrid algorithm. The results of inversion for the field examples are characterized by low residual values between the observed gravity anomalies and the calculated ones.

EstuarySAT Database Development of Harmonized Remote Sensing and Water Quality Data for Tidal and Estuarine Systems.

Researchers and environmental managers need big datasets spanning long time periods to accurately assess current and historical water quality conditions in fresh and estuarine waters. Using remote sensing data, we can survey many water bodies simultaneously and evaluate water quality conditions with greater frequency. The combination of existing and historical water quality data with remote sensing imagery into a unified database allows researchers to improve remote sensing algorithms and improves understanding of mechanisms causing blooms. We report on the development of a water quality database "EstuarySAT" which combines data from the Sentinel-2 multi-spectral instrument (MSI) remote sensing platform and water quality data throughout the coastal USA. EstuarySAT builds upon an existing database and set of methods developed by the creators of AquaSat, whose region of interest is primarily larger freshwater lakes in the USA. Following the same basic methods, EstuarySAT utilizes open-source tools: R v. 3.24+ (statistical software), Python (dynamic programming environment), and Google Earth Engine (GEE) to develop a combined water quality data and remote sensing imagery database (EstuarySAT) for smaller coastal estuarine and freshwater tidal riverine systems. EstuarySAT fills a data gap that exists between freshwater and estuarine water bodies. We are able to evaluate smaller systems due to the higher spatial resolution of Sentinel-2 (10 m pixel image resolution) vs. the Landsat platform used by AquaSat (30 m pixel resolution). Sentinel-2 also has a more frequent revisit (overpass) schedule of every 5 to 10 days vs. Landsat 7 which is every 17 days. EstuarySAT incorporates publicly available water quality data from 23 individual water quality data sources spanning 1984-2021 and spatially matches them with Sentinel-2 imagery from 2015-2021. EstuarySAT currently contains 299,851 matched observations distributed across the coastal USA. EstuarySAT's primary focus is on collecting chlorophyll data; however, it also contains other ancillary water quality data, including temperature, salinity, pH, dissolved oxygen, dissolved organic carbon, and turbidity (where available). As compared to other ocean color databases used for developing predictive chlorophyll algorithms, this coastal database contains spectral profiles more typical of CDOM-dominated systems. This database can assist researchers and managers in evaluating algal bloom causes and predicting the occurrence of future blooms.

Green momentum? An age-period-cohort analysis of support for the environmental movement in 24 countries

Over the past decade, the climate movement and especially action groups like Fridays for Future have been effective in raising awareness of environmental issues and mobilizing protesters, especially among younger age groups. However, it remains unclear whether this recent surge in activism reflects a broader societal shift or if this trend is primarily driven by younger generations. Using data from 24 countries that participated in waves three and four of the International Social Survey Programme Environment Module, this study employs, for the first time, an Age-Period-Cohort (APC) analysis of environmental Public-Sphere Behavior in an international comparative context. Based on Bayesian negative binominal multilevel models, the results provide empirical evidence for a period effect: PSB have indeed increased across generational cohorts and age groups.

Exploring digital competence among Vietnamese EFL preservice teachers: the role of ICT self-efficacy, collegial collaboration, and infrastructural support

This study investigated factors influencing digital competence among Vietnamese preservice EFL teachers, focusing on ICT self-efficacy, collegial collaboration, and infrastructural support. Employing a quantitative research design, data were collected from 183 final-year EFL preservice teachers across various Vietnamese universities using validated scales. Structural equation modeling was utilized to examine the relationships between variables. Results validated a four-factor model comprising digital competence, ICT self-efficacy, collegial collaboration, and infrastructural support. ICT self-efficacy emerged as a strong predictor of digital competence (β = 0.43, p < .001), collegial collaboration (β = 0.81, p < .001), and infrastructural support (β = 0.57, p < .001). Collegial collaboration (β = 0.43, p < .001) and infrastructural support (β = 0.09, p < .05) also positively related to digital competence. The model explained 78% of the variance in digital competence. These findings underscore the importance of fostering ICT self-efficacy and collaborative learning environments in EFL teacher preparation programs, contributing to the development of evidence-based strategies for enhancing digital competence in preservice teacher education.

Features of the information and control system of the car's hybrid power plants

Abstract. Problem. Until now, a number of features of IBS power plants of electric and hybrid cars remain unexplored. The applied IIUS analysis and synthesis methods do not pay enough attention to the multi-criteria nature of the arising optimization tasks. Management adaptation methods to changingexternal operating conditions are insufficiently effective. These circumstances do not allow to fully reveal the potential possibilities of IISD power plants of electric and hybrid cars. This determines the relevance of improvement and development of new methods of modeling and optimization of IIUS control of power plants of electric and hybrid cars based on modern theory of automatic control, vector optimization, neural network and neuro-fuzzy adaptive methodology. A methodology for the construction of IIUS invariant to various power plants of electric and hybrid cars has been developed for operational management of modes according to quality, energy and other criteria. Results. The mathematicalsupport of the "Recovery" mode differs from classical problems of optimal control in that it allows changing the parameters of the control power plant, its model type, limit values for control influences, and phase coordinates. Originality. The core of the IICS GSU software is a knowledge base, in which procedural knowledge is presented in the form of frames that implement the algorithmic support of IICS GSU. The knowledge base has a stratified, hierarchical structure that reflects an integrated graph of the synthesis technology of the ZOU solution. The content of the frames of the knowledge base ensures the search for a solution to the ZOU problem in the state space. Frames contain slots that hold not only specific data but also the names of procedures that process them according to a given algorithm. Some frames contain slots filled with product rules. During the creation of the knowledge base of the research prototype, work was carried out on the unification of frame names, which makes it possible to quickly build the knowledge bases of working prototypes. Knowledge frames are a set of classes developed in a visual programming environment. Practical value. The resulting optimal program is worked out using simulation modeling modules, which include direct modeling of systems in multiple states of operation, and if it satisfies the specified requirements, the resulting data is converted into a file containing optimal control influences, which is stored in the database.

Gut mucosa alterations after kidney transplantation: a cross sectional study.

Kidney transplant recipients (KTRs) rely on immunosuppressants like mycophenolate to prevent organ rejection. However, mycophenolate often causes intestinal symptoms and inflammation in various organs, including the skin and the colon. While KTRs have an increased risk for skin cancer, the risk of colorectal cancer is not increased. Elucidating the histological alterations in the colon of KTRs and comparing these changes with known skin alterations would help understand how immunosuppressants influence cancer development and progression. Whole slide images from gut biopsies (Non-transplanted subjects n = 35, KTRs n = 49) were analyzed using the ImageJ and R programming environment. A total of 22,035 epithelial cells, 38,870 interstitial cells, 3465 epithelial cell mitoses, and 7477 endothelial cells, each characterized by multiple microscopy parameters, from a total of 1788 glands were analyzed. The large database was subsequently analyzed to verify the changes of inflammatory milieu in KTRs and in cancer. KTRs without colon-cancer showed a significantly higher density of interstitial cells in the colon compared to non-transplanted patients. Moreover, the increase in interstitial cell number was accompanied by subtle modifications in the architecture of the colon glands, without altering the epithelial cell density. We could not identify significant structural modifications in cancer samples between KTRs and non-transplanted patients. Our findings demonstrate an increased number of resident interstitial cells in the colon of KTRs, as in other patients treated with mycophenolate. These changes are associated with subtle alterations in the architecture of colon glands.

Model i implementacja dwurdzeniowego sterownika programowalnego opartego na maszynie wirtualnej

The concept, semantic model, and prototype implementation of a dual-core programmable controller have been presented. The controller’s design concept involves parallel processing of two execution programs through a virtual machine, utilizing a shared memory area for global variables. The presented model provides a formal description of the execution of portable binary programs created based on the languages of the IEC 61131-3 standard in the CPDev programming environment. The architecture described outlines the operation of the virtual machine using abstract algebraic objects. The solution has been implemented in C/C++ on a dual-core microcontroller platform.