Modeling Software Tools Research Articles

Conformation Study and Design of Novel 6-Hydroxybenzothiazole-2-Carboxamides as Potentially Potent and Selective Monoamine Oxidase B Inhibitors for Neuroprotection.

6-hydroxybenzothiazole-2-carboxamide is a novel, potent, and specific monoamine oxidase B inhibitor that can be used to study the structure of molecules and come up with new ways to protect neurons. The objective of this work was to create an effective model using derivatives of 6- hydroxybenzothiazole-2-carboxamide and establish a dependable predictive foundation for the development of neuroprotective monoamine oxidase B inhibitors for the treatment of neurodegenerative diseases. The construction and optimization of all compounds were carried out sequentially using ChemDraw software and Sybyl-X software. The optimized compounds were further analyzed using the COMSIA approach and the Sybyl-X software tool for QSAR modeling. A set of novel compounds of 6-hydroxybenzothiazole-2-carboxamide were created and their IC50 values were forecasted using QSAR modeling. Ultimately, the recently developed compounds underwent a screening process using their IC50 values, and molecular docking tests were conducted on the ten most promising compounds with the highest IC50 values. The 3D-QSAR model exhibited favorable outcomes. The value of q2 in the COMSIA model was 0.569. The model demonstrated a superior r2 value of 0.915, a lower SEE of 0.109, and a higher F-value of 52.714. The statistical findings and validation of the model were deemed adequate. Furthermore, analyzing the contour plots might assist in identifying the necessary structural specifications. This work has the potential to provide an insight into the development of active medicines that protect the nervous system against neurodegenerative disorders.

Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software.

Burkholderia pseudomallei (Bp), causing melioidosis, is becoming a major global public health concern. It is highly endemic in Southeast Asia (SEA) and Northern Australia and is persisting beyond the established areas of endemicity. This study aimed to determine the environmental variables that would predict the most suitable ecological niche for this pathogenic bacterium in SEA by maximum entropy (MaxEnt) modeling. Systematic review and meta-analysis of data for melioidosis were obtained from public databases such as PubMed, Harmonized World Soil (HWSD) and WorldClim. The potential map showing the environmental layers was processed by ArcGIS, and the prediction for the probability of habitat suitability using MaxEnt software (version 3·4·4) and ENMeval R-based modeling tools was utilized to generate the distribution map with the best-fit model. Both bioclimatic and edaphic predictors were found to be the most important niche-determining environmental variables affecting the geographical distribution of Bp. The highest probability of suitability was predicted in areas with mean temperature of the wettest quarter at ≥26°C, annual precipitation of <2300 mm and Acrisol soil type. Combining those significantly influential variables, our predictive modeling generated a potential distribution map showing the concentration of areas and its location names with high suitability for Bp presence. The predicted distribution of Bp is extensive in the mainland part of SEA. This can be used to draw appropriate measures to safeguard public health and address the true disease burden of melioidosis in the region under the current climate scenario.

Fostering environmental sustainability of leather industry: environmental impact assessment and improvement prospects for leather-tanning technologies.

Because of various negative impacts of chromium intensive manufacturing, the leather-based fashion industry is under pressure to use environmentally friendly tanning technologies. However, there is a lack of scientific research that evaluates the environmental impacts of novel tanning processes. Thus, this study is aimed to quantify and compare the environmental impacts of traditional chromium-based process and a novel metal-free tanning technology. The novel metal-free technology is based on synthetic tannins, instead of metal or vegetable-based tannins. To achieve the objectives, a detailed life cycle assessment was done for 1 m2 of finished leather. The primary data were gathered from two different leather manufacturing plants located in the same Italian municipality and the background data were extracted from the Ecoinvent database. SimaPro 9.4 was used as the modeling software tool, and the impacts were evaluated for midpoint impact categories. For the novel metal-free tanning technology, the results revealed a significant reduction in various impact categories, such as particulate matter impacts were reduced by 25%, human toxicity (non-carcinogenic) by 31%, human toxicity (carcinogenic) by 56%, and acidification by 29%. Overall, based on single point performance score, the novel metal-free tanning system showed 18.4% less environmental impacts than the chrome-based tanning. For the most relevant impact categories, the novel metal-free tanning system again showed significantly less impact. The cattle breeding phase contributed most to various relevant impact categories, including acidification, particulate matter, and terrestrial eutrophication. Two alternative scenarios were also developed and evaluated to show how the solar energy may help further reduce the environmental impacts. A sensitivity analysis was also carried out to see the influence of uncertainty linked with the choice of thermal energy source. Overall, the study highlighted how the green tanning technologies and green energy initiatives could help decarbonize and improve the environmental performance of leather manufacturing industry.

Utilizing 3D Model and Comparison Software Tools in Improving Assessment Methods: A Pilot Study

Purpose/Objectives: This manuscript investigates the effectiveness of computer-assisted design and manufacturing (CAD/CAM) technology in preclinical dental education. The COVID-19 pandemic created a need for remote teaching approaches. In preclinical fixed prosthodontics courses, traditional evaluation methods rely on faculty to visually grade laboratory projects utilizing rubrics and 2D images. Assessment and feedback vary amongst faculty, and faculty calibration has been inconsistent in reducing intra-and inter-rater variability. This study aimed to compare faculty assessment of student full coverage crown (FCC) preparations traditionally versus digitally through 3D model visual assessment and/or comparative analysis software reports. Methods: Eighteen UTHealth Houston School of Dentistry faculty participated, each randomly assigned into one of three assessment groups: traditional visual Group (TV), 3D Group (3D), and 3D visual assessment supplemented with comparative analysis software report (3D+) Group. Faculty graded the same eight lithium disilicate typodont preparations for all three assessment groups. Results: Survey results showed the ease of use and efficiency among the three assessment methods varied significantly. Grading scores revealed that axial wall reduction significantly differed among the three assessment methods. Conclusion: This study concludes that the combination of the two digital assessment methods can overcome the limitations of traditional evaluation methods and digital methods alone by providing objective feedback to students and enhancing their learning experience.

DEVELOPMENT PROCESS OF A FREQUENCY CONVERTER FOR INDUCTION HEATING OF OIL PIPELINE

The article provides a detailed overview of the history, development and applications of frequency converters, with particular emphasis on their use in the oil and gas industry. It traces the evolution of frequency converters from their inception in the late 19th and early 20th centuries to their modern applications, which use microprocessors and digital signal processing to precisely control the output frequency. In the oil and gas industry, frequency converters are critical to efficient and accurate induction heating of pipelines. They convert a fixed frequency and voltage power supply into a variable frequency and variable voltage output, controlling the speed of the induction motors used in the heating process. The article also covers the design and modeling of frequency converters, discussing the process of characterizing them, creating mathematical models, and using modeling software tools such as MatLab. It presents equations for inductive energy, capacitor energy, resonance conditions and power factor, which are necessary in the mathematical modeling of frequency converters. The article concludes by highlighting the impact of frequency converters on the efficiency and economics of induction heating systems. It emphasizes the need for careful design and modeling to ensure optimal performance and safety.

Жиһаз индустриясы үшін мамандар даярлаудағы инновациялық цифрлық шешімдер

In the context of the rapid development of technologies and changing market requirements, this approach is becoming increasingly relevant, as it contributes to the formation of creative and innovative specialists. The purpose of the study is to analyze the use of digital design and design thinking in the educational process, as well as to assess their impact on the formation of professional competencies of students. The paper examines modern practices and methodologies, including the use of 3D modeling software, virtual reality and other digital tools that allow students to interact with real-time projects. The study used interactive multimedia tools, digital methods of graphic design, and virtual experiences adapted in the learning process. The results of the analysis show that the integration of digital technologies into training not only increases the level of student participation, but also contributes to the development of critical thinking, teamwork skills and the ability to solve practical problems in furniture design and production. These conclusions indicate the need to adapt educational programs to modern requirements and challenges, and also open up new opportunities for the use of innovative teaching methods in the furniture industry, which, in turn, can contribute to increasing the competitiveness of specialists in the labor market.

Improving environmental and economic sustainability of cutlery manufacturing in adeveloping nation through energy reduction and energy transition initiatives.

Manufacturing industries are vital for economic development, but they cause significant environmental damages. As there are scarce research studies for this industrial sector from developing countries, this article reports a comprehensive environmental and economic analyses for cutlery manufacturing in Pakistan. SimaPro 9.5 was used as a modelling software tool, while ReCiPe 2016 methods were used to evaluate various midpoint and endpoint environmental impacts. Various economic indicators were used to evaluate the economic performance of different alternative scenarios. The results revealed that injection molding process, due to its energy-intensive nature caused the most environmental impacts as compared to other manufacturing processes. Global warming and terrestrial ecotoxicity were the most affected impact categories with values of 11.8 kg CO2 eq and 12.0 kg 1,4-DCB, respectively. Meanwhile, at endpoint level, human health category was most damaged as compared to others. Based on technical process intervention and energy transition, four different alternative scenarios were developed. In comparison with baseline scenario, the alternative scenario with double-cavity mold resulted in a reduction of more than 30% for various impact categories. The other three alternatives were grounded on the use of solar energy (50% or 100%) and injection mold with double or single cavity. Overall, the alternative scenario with 50% solar energy and double-cavity mold was the best solution that showed more than 50% reduction in most of the impact categories, less than 3-year payback time, 2.12 million (Pakistani Rupees) net present value, and 36.3% of return on investment. This study clearly shows the importance of renewable energy resources and simple changes in process technology for improving sustainability performance. The relevant stakeholders can effectively use the results and methodology of this study as a reference and guide for future research and practical interventions, especially in developing countries.

МОДЕЛЮВАННЯ ФУНКЦІОНУВАННЯ ЛОГІСТИЧНИХ ПРОЦЕСІВ ЗА ДОПОМОГОЮ МАТЕМАТИЧНИХ ТА КОМП’ЮТЕРНИХ ПІДХОДІВ

his paper addresses the modeling of logistics processes using mathematical and computational approaches. In today's globalized market, optimizing logistics processes is crucial for minimizing costs and enhancing the efficiency of supply chain management and product delivery. The study explores various mathematical models and algorithms designed to optimize delivery routes and inventory management. Specifically, it discusses the formulation of a mathematical model for route optimization using Dijkstra's algorithm and inventory management through formulas that account for demand, lead time, and service levels. The primary objective of the research is to develop and implement a mathematical model that improves logistics efficiency by applying computational tools. The work includes the formalization of the mathematical model, which considers routing and inventory management, the creation of iterative algorithms for optimizing delivery routes and inventory levels, and the use of modern software tools for modeling and analysis. The results demonstrate that the proposed models effectively reduce transportation costs and enhance overall logistics performance. By employing Dijkstra’s algorithm, the study achieves optimal routing solutions that minimize costs while considering factors such as transportation expenses, delivery time, and contract requirements. The inventory management model, based on safety stock calculations and demand forecasting, ensures a balanced approach to maintaining optimal inventory levels. The findings indicate that the developed model not only addresses current logistics challenges but also has the potential for future improvements. Future research directions include expanding the model to incorporate additional constraints, adapting it to various types of enterprises, and refining algorithms for greater accuracy and efficiency. In conclusion, the study highlights the potential of mathematical modeling and computational methods in optimizing logistics processes, offering a valuable tool for modern supply chain management systems. The research contributes to the advancement of logistics optimization by providing practical solutions and a foundation for further development.

On-board radar complex for high-precision direction finding of radio sources for autonomous guidance of winged UAVs

The subject of this article is the design of a cheap, simple, and highly accurate on-board radar system for determining the angular position of radio-signal emission stations, which can be used to guide UAVs to a specified area of space. The aim of this study is to develop high-precision functioning algorithms, practical recommendations for implementation, and experimental measurements of the main parameters of the onboard radio direction finders of radio radiation sources placed on winged UAVs. Objectives of the research: 1) analysis of the statistical theory of optimization of signal processing algorithms in radar systems; 2) synthesis of direction-finding algorithms for radio measurement sources capable of performing measurements with high accuracy and in a wide range of unambiguous measurement angles; 3) synthesis of the radio direction finder structural scheme and its simulation modelling; 4) design of radio direction finder receiving antennas capable of operating separately and in a complex; 5) justification of the choice of components for the input paths of receivers, parameters of ADC and microcomputers that make up the main components of the radar complex; 6) manufacturing of a working model of the radar complex; 7) experimental measurements in the laboratory. The methods for solving the tasks are based on the statistical theory of optimization of radio engineering systems for remote sensing and radar, existing software tools for simulation modelling, and the theory of radio measurements. The main idea behind creating a cheap, simple, and highly accurate on-board radar system for radio emitter direction finding is to combine the results of angular position measurements from several amplitude and phase meters. This approach allows us to create an easy-to-implement radio system with the advantages of different measuring instruments. The following results were obtained: 1) theoretical studies and simulation modelling confirmed that by combining measurements from a two-antenna amplitude direction finder with narrow diagrams, a two-antenna direction finder with wide diagrams, and a two-antenna phase finder, it is possible to achieve both high accuracy and a wide range of unambiguous measurements; 2) a radar system based on a cheap and commonly available element base was developed; 3) antennas were developed that can be easily installed under the wings of UAVs; 4) experimental studies confirmed the performance of complex signal processing in an on-board six-antenna radio direction finder. The material of this work forms the basis for further experimental development of radio-direction finders for various purposes, opens up opportunities for overcoming the contradiction between accuracy and range of unambiguous measurements, and highlights an additional direction for increasing the autonomy of winged UAVs.

Selecting a priority criterion when forming optimal management of a production enterprise using digitalization tools

Relevance. At the present stage, economic and mathematical methods cannot be fully implemented without the use of digitalization tools. The center of many modern theoretical studies, both by foreign and Russian authors, is a simulation model that allows the most complete reflection of both the theoretical message under consideration and its nuances, to which a software package or modeling tools can be fully adapted. The activities of various production and technology companies may be influenced by external factors, which must be resolved not only strategically, but also operationally. Methodological problems lie in the choice of a priority criterion for the formation of optimal management of a manufacturing enterprise using digitalization tools.The purpose is to select a priority criterion for the formation of optimal management of a manufacturing enterprise using digitalization tools.Objectives. objective prerequisites for the construction of simulation models based on an optimization approach are given; the initial formulation of the convex programming problem is justified, an analysis of the priority of weight coefficients is given; the accuracy of calculation and the type of utility function is justified when the analysis of the prevailing normalized prices is assumed. In such initial conditions, the solution of the convex programming problem can be reduced to finding the optimum in the production planning problem.Methodology. The study was carried out using methods of logical and comparative analysis of existing simulation models of operational management of the company, as well as methods of mathematical modeling.Results. The paper proposes an algorithm for the phased implementation of the optimization task, taking into account three relevant responses of the system to the use of resource-saving technologies, determined by the use of a specific type of technological production.Conclusions. The priority of choosing a criterion in the formation of optimal management of a manufacturing enterprise using digitalization tools creates favorable conditions for the system's response to technology changes, depending on three possible states of production technology: ultra-efficient technology, extremely backward technology, medium or normal technology.

Addressing plastic pollution and waste flows: Insights from South Africa's experience.

The Pew Charitable Trust's 2020 report 'Breaking the Plastic Wave', indicates that existing technologies could support an 80% reduction in plastic leakage relative to business as usual by 2040. Therefore, South Africa became the first country to work with the Pew Charitable Trust and Oxford University to test and apply 'Pathways', a modelling framework and software tool which stemmed and evolved from the Pew report, at country level. The tool calculates the flows of plastics in the economy and the impact of various strategies to reduce future plastic pollution. The Scenario Builder within the Pathways tool allows the user to optimise flows in the plastics value chain to satisfy a set of defined objectives in order to achieve an optimal solution. Three major findings have emerged from the application of Pathways at country level for South Africa. Firstly, plastic pollution is set to almost double by 2040 if no interventions are implemented. Secondly, meeting the newly legislated extended producer responsibility (EPR) targets set for plastic packaging can avoid 33% of projected total pollution over the period of 2023-2040. Lastly, an optimal system change can avoid 63% of total plastic pollution over the period 2023-2040. Thus, applying Pathways at country level in South Africa has proven to be valuable by setting a baseline against which progress towards reducing plastic pollution can be measured; determining the outcome of meeting the legislated EPR targets over time, and informing policy decisions by allowing users to model different scenarios towards an optimal system change scenario.

An Interview with Martin Robillard - 2024 SIGSOFT Awardee

Martin Robillard received the 2024 SIGSOFT Influential Educator Award for his significant contributions to hands-on software design education, including a textbook (Introduction to Software Design with Java) and a learner-focused software modeling tool (JetUML). He is currently a Professor in the School of Computer Science at McGill University, Montréal, Canada, he is a Distinguished Member of the ACM and a Fellow of the Alexander von Humboldt Foundation. He received his Ph.D. in Computer Science from the University of British Columbia. His research interests fall within the area of software engineering, focussing on human-centred software development. He was awarded six ACM SIGSOFT Distinguished Paper Awards for his work on recommendation systems, software traceability, and software documentation. Recently, he has been working on software documentation generation, test suite quality, and information privacy.

A case study for optimization of power system load flow analysis using ETAP software

This research report explores the optimization of power system load current analysis by integrating Electrical Transient Analyzer Program (ETAP) software and Single Line Diagram (SLD) representation. Load current analysis is essential for the reliable and efficient operation of power grids, and the use of advanced software tools such as ETAP offers significant opportunities to improve analysis capabilities. The integration of SLD with ETAP enables more intuitive and comprehensive visualization of energy system elements and their connections, improving the modelling and analysis process. The article presents a case study that demonstrates the practical application of this integrated approach using a typical power system model to estimate load current characteristics under various operating conditions. The methodology involves building a powerful system model in ETAP and includes SLD representations to improve system visualization and analysis. The system simulation experiments evaluate the performance and accuracy of the integrated ETAPSLD approach, focusing on key parameters such as voltage profiles, current flows, enabling more efficient load current analysis and providing valuable information for power system engineers and operators. Overall, this study contributes to the field of energy system analysis by using advanced software tools for advanced modelling and optimization.

Planning Tools for Decentralized Heat Supply: Modeling the Effects of Volatile Renewable Energies

An increasing share of decentralized feed-in is necessary for the transition of district heating networks but it comes with various challenges. Software tools for modelling, simulation and optimization allow a theoretical examination of those challenges and possible solutions. Some of these have been used and further developed in the research project ZellFlex. One selected examination is the flexibility of supply temperatures by varying setpoint temperatures for a decentral solar thermal system (500 m²) integrated into an existing district heating network. The analysis of the supply temperature distribution in the network showed: A decrease of the solar thermal feed-in set point temperature by 5 K compared to the supply temperature of the central heat producer seemed acceptable in terms of security of supply, while a 10 K reduction comes with a high risk of undersupply. Furthermore, it was discovered that the points of time with the lowest supply temperatures at the consumers were just before and after they were provided with solar heat due to specific effects concerning temperature loss of the fluid.

Groundwater Modelling of Jamwa Ramgarh using Visual MODFlow Flex

A steady state finite difference model, MODFLOW, is developed to quantify groundwater in Jamwa Ramgarh, Jaipur (Dt) Rajasthan, using Groundwater data from 06 observation wells. ArcGIS was used to generate various shapefiles required as input files in Visual MODFlow Flex. The findings indicate that the calculated contours of groundwater levels closely correspond to the observed contours. The sustainable utilization and management of groundwater resources pose significant challenges for many countries worldwide. In recent years, groundwater modelling has emerged as an effective approach to tackle these challenges. Various modelling software tools are available to simulate groundwater flow, with MODFLOW being widely used to investigate the interactions between surface water and groundwater and to develop models for specific study areas. MODFLOW, a renowned groundwater modelling software, enables researchers and water resource professionals to understand and analyze the complex dynamics of groundwater systems. By utilizing MODFLOW, it becomes possible to assess the interactions between surface water and groundwater, evaluate the impacts of pumping or recharge activities, and make informed decisions regarding the sustainable management of groundwater resources. The utilization of MODFLOW and similar modelling software plays a crucial role in advancing our understanding of groundwater systems and supporting effective groundwater resource management practices.

Software Platform Based on the hLARM Formalism for Modeling Complex Systems

The problem of defining, analyzing and reasoning behaviors, facts and uncertainties in complex systems asks for new modeling formal methods and software tools that can deal with managing such collections of heterogeneous and dynamical interacting entities. The purpose of this paper is to present in detail the implementation of a new software modeling platform which is based on the hLARM (Hybrid Logic-Algebraic Relational Modeling) formalism which aims to alleviate the process of designing and managing such systems. The development of the platform is thoroughly analyzed from its conceptual background and up to the algorithms which support all the inference procedures involved.

Deployment of a UAV swarm-based LiFi network in the obstacle-ridden environment: algorithms of finding the path for UAV placement

The subject of this study is unmanned aerial vehicle (UAV)-based wireless networks in an obstacle-ridden environment. The aim of this study is to develop methods and software to ensure reliable LiFi communication using swarm UAVs in an obstacle-ridden environment. The objectives are as follows: 1) to describe the problem of providing a reliable UAV swarm-based LiFi network, requirements for the composition and use of UAVs, and assumptions; 2) to develop the methodology for solving research tasks; 3) to develop the method and algorithms for solving the problem, considering the requirements, assumptions, and practical limitations; 4) to explore the algorithms by developing software for modeling and searching for rational UAV placement to ensure the required UAV-based LiFi network characteristics; 5) to provide experiments and illustrative examples of the developed tool’s application. The following results were obtained. 1) The requirements for the composition and use of UAVs for creating LiFi networks, as well as assumptions and limitations for the methodology development and research task solving. 2) An obstacle avoidance method using the left and right angles algorithm. 3) A method for obstacle avoidance using the controlled waterfall algorithm. 4) A software tool for modeling and searching for rational UAV placement to ensure the required LiFi network characteristics. The tool allows route construction under obstacles in 2D space and a comparison of the developed algorithms for various variants of obstacle placement. Conclusions. The main contribution of this research is a set of methods, algorithms, and software tools for providing communications between two points using LiFi technologies and a swarm of UAVs supporting these communications as transmitters in conditions of mechanical obstacles.

Distinct neocortical mechanisms underlie human SI responses to median nerve and laser-evoked peripheral activation

Abstract Magneto- and/or electro-encephalography (M/EEG) are non-invasive clinically relevant tools that have long been used to measure electromagnetic fields in the somatosensory cortex evoked by innocuous and noxious somatosensory stimuli. Two commonly applied stimulation paradigms that produce distinct responses in the primary somatosensory cortex (SI) linked to innocuous and noxious sensations are electrical median nerve (MN) stimulation and cutaneous laser-evoked (LE) stimulation to the dorsum of the hand, respectively. Despite their prevalence, the physiological mechanisms that produce stereotypic macroscale MN and LE responses have yet to be fully articulated, limiting their utility in understanding brain dynamics associated with non-painful and/or painful somatosensation. Through a literature review, we detailed features of MN and LE responses source-localized to SI that are robust and reproducible across studies. We showed that the first peak in the MN response at ~20 ms post-stimulus (i.e., MN N1) corresponds to upward-directed deep-to-superficial electrical current flow through the cortical laminae, which is followed by downward-directed current at ~30 ms (i.e., MN P1). In contrast, the initial LE response occurs later at ~170 ms (i.e., LE N1) and is directed downward and opposite the direction of the MN N1. We then examined the neocortical circuit mechanisms contributing to the robust features of each response using the Human Neocortical Neurosolver (HNN) neural modeling software tool (Neymotin et al., 2020). Using HNN as a hypothesis development and testing tool, model results predicted the MN response can be simulated with a sequence of layer-specific thalamocortical and cortico-cortical synaptic drive similar to that previously reported for tactile evoked responses (S. R. Jones et al., 2007; Neymotin et al., 2020), with the novel discovery that an early excitatory input to supragranular layers at ~30 ms is an essential mechanism contributing to the downward current flow of the MN P1. Model results further predicted that the initial ~170 ms downward current flow of the LE N1 was generated by a burst of repetitive gamma-frequency (~40 Hz) excitatory synaptic drive to supragranular layers, consistent with prior reports of LE gamma-frequency activity. These results make novel and detailed multiscale predictions about the dynamic laminar circuit mechanisms underlying temporal and spectral features of MN and LE responses in SI and can guide further investigations in follow-up studies. Ultimately, these findings may help with the development of targeted therapeutics for pathological somatosensation, such as somatic sensitivity and acute neuropathic pain.

Математическая модель для проектирования линейных асинхронных электродвигателей и ее программная реализация

Mathematical models are the main tool for the layout design of linear asynchronous electric motors. Existing design models of linear asynchronous electric motors assume that the device is powered from a source of multiphase symmetrical positive sequence current, which excludes from consideration the asymmetry of the inductor phase currents and the associated reduction in traction force. This approach is not flexible enough, since the operation of linear asynchronous electric motors in a wide range of movement speeds assumes a functional relationship between the current asymmetry coefficient and the movement speed. The study developed a mathematical model for design purposes that implements the functional relationship between the current asymmetry coefficient and the speed of movement. The mathematical model represents 13 linear equations linking geometric dimensions, current loads, electromagnetic field characteristics and mechanical forces with the speed of the secondary element of the electric motor. The current load of an electric motor has a variable degree of ellipticity depending on the speed of movement. An algorithmic study of the mathematical model was carried out and corresponding software modeling tools were developed. The proposed program algorithm, containing two subroutines, is implemented using the Maple symbolic computing software package. In order to expand the range of users, the software model is additionally implemented in C++. In this case, the functional dependence of the asymmetry coefficient of the exciting current wave on the speed of movement is implemented in the form of an iterative procedure for the case of connecting the winding of the linear asynchronous electric motors inductor to a source of symmetrical three-phase voltage according to the “triangle” circuit. Using the example of a three-phase linear asynchronous electric motors, the electromagnetic and mechanical characteristics of the electric motor were simulated. It was stated that the influence of current asymmetry on the mechanical characteristics of the linear asynchronous electric motors is small and is expressed in the region of high speeds. This makes it possible, in design tasks for the layout of an electric motor, to use models that involve powering the linear asynchronous electric motors from a symmetrical current source or to introduce a fixed asymmetry coefficient into them.

MV-Checker: A software tool for multi-valued model checking intelligent applications with trust and commitment

Intelligent applications are highly susceptible to uncertainty and inconsistency due to the intense and intricate interactions among their autonomous components (or agents), making their verification theoretically and practically challenging. This paper presents the design and implementation of a new open-source and scalable software tool for modeling and verifying intelligent applications with commitment and trust protocols under both uncertainty and inconsistency settings, using reduction-based multi-valued model checking techniques. The proposed tool is equipped with original and novel algorithms that transform our logics of multi-valued commitment (mv-CTLC) and multi-value trust (mv-TCTL) that we recently introduced to their classical two-valued commitment (CTLC) and trust (TCTL) logic versions as well as to Computational Tree Logic (CTL). Moreover, the tool transforms the mv-CTL to CTL, and it is applicable for the classical model checking by transforming the classical logics of trust and commitment to CTL. To demonstrate the practicality and applicability of the proposed tool in real settings, we present and report experimental results over two blockchain-based applications in the healthcare domain. Finally, we provide discussions and comparisons between the proposed approaches regarding scalability and efficiency. Moreover, we provide packages of more than 11 experiments, including the ones we conduct in this paper and enhanced experiments from previous works. Our findings ensure that the proposed approaches and the software tool that implements them are highly efficient and scalable, giving accurate results under varying conditions.