Mathematical Criteria Research Articles

РОЗВИТОК КОРПОРАТИВНОЇ СОЦІАЛЬНОЇ ВІДПОВІДАЛЬНОСТІ БУДІВЕЛЬНИХ ПІДПРИЄМСТВ

It is determined that the formation of and acquires special significance use of corporate social responsibility as important factor in creating a socially oriented economy that is modern trend of counteraction to negative phenomena, impact of pandemic COVID-19. Achieved the purpose of the study to determine the directions of corporate development social responsibility of construction companies. Tasks solved of the presented research: definition of directions and features implementation of corporate social responsibility of construction enterprises; characteristics of strategic contours of corporate development social responsibility; determining the directions of level growth the effectiveness of corporate social responsibility construction companies. For the development of corporate social responsibility are proposed stages of economic and mathematical modeling: the formation of information-analytical support based on quantitative and qualitative indicators that determine the corporate social responsibility of enterprises; construction systems of indicators for assessing corporate social responsibility; assessment of the generalizing factor of the level of formation and use corporate social responsibility of enterprises; determining the degree the influence of factors on the generalized indicator of formation and use corporate social responsibility based on correlation coefficients and determination; assessment of economic and mathematical adequacy criteria models; interpretation of the obtained results. The results of the assessment of the integrated indicator of formation are presented and the use of corporate social responsibility for construction enterprises, which created a quantitative basis for the adoption of reasonable management decisions. To ensure the strategic contours of corporate development social responsibility of construction companies is proposed application of modern tools of geographic information systems, which allows you to build monitoring maps of CSR changes, taking into account spatial aspects of enterprise functioning. The application of organizational and economic mechanism is offered formation and use of corporate social responsibility construction companies, which allows you to determine the organizational and economic directions of its development as important factors of creation strategic contours.

Scientific research of the Institute of Nuclear Medicine and Diagnostic Radiology of the National Academy of Medical Sciences of Ukraine in 2020: hepatology, oncology and intellectual data processing

The main results of the scientific activity of the Institute in 2020 are presented: the study of the structural features of diagnostic images based on their heterogeneity for the purpose of differential diagnosis of malignant neoplasms; development of radiation diagnostic criteria for differential diagnosis of congenital and acquired liver diseases in children; development of urgent detailed ultrasound examinations for traumatic injuries of the human body, complex radiation examination of the wound channel in case of a gunshot injury; development of methodological foundations for the use of multiparametric high-field MRI of the brain to assess the state of the leading tracts and the functional capacity of the cerebral cortex. Methods for textural analysis of computed tomographic images, echograms of normal and tumor tissues based on the use of coefficients of one-dimensional heterogeneity, anisotropy coefficient, and verticality coefficient have been developed. For the first time in Ukraine, a mathematical system that provides in 93-98% of cases of recognition of fibrous (precision) liver changes based on ultrasound images (utility model patent No. 139916) has been developed; significant differences between the values of mathematical criteria for normal and damaged liver based on computer processing of echographic images allow solving the problem of recognizing diffuse liver diseases.

The media epistemic value of sonic analytics tools. A commentary

While automatized content identification of audio data, in critical discourse analysis, is bound to the symbolic order of monitoring, control, surveillance, censorship and copyright protection, the very tools and algorithms which have been developed for such purposes can be turned into instruments of knowledge production in the scientific sense. Audio content identification is not simply an extension of cultural taxonomies to machine listening, but an operation with its own eigen knowledge. Audio content identification is not simply a continuation of analog techniques for monitoring sonic objects. From a media-epistemological perspective, new forms of audio content identification open different orders of the sonic archive. What is practiced in the online domain has been preceded by experimental investigations of archival storage. The real l'archive, though, are the technological (hardware) and mathematical (software) criteria defining content identification. A media archaeology of audio content identification reveals the technological l'archive governing such forms of enunciation.

Modeling and Forecasting Saudi Stock Market Volatility Using Wavelet Methods

This empirical research aims to modeling and improving the forecasting accuracy of the volatility pattern by employing the Saudi Arabia stock market (Tadawul)by studying daily closed price index data from October 2011 to December 2019 with a number of observations being 2048. In order to achieve significant results, this study employs many mathematical functions which are non-linear spectral model Maximum overlapping Discrete Wavelet Transform (MODWT) based on the best localized function (Bl14), autoregressive integrated moving average (ARIMA) model and generalized autoregressive conditional heteroskedasticity (GARCH) models. Therefore, the major findings of this study show that all the previous events during the mentioned period of time will be explained and a new forecasting model will be suggested by combining the best MODWT function (Bl14 function) and the fitted GARCH model. Therefore, the results show that the ability of MODWT in decomposition the stock market data, highlighting the significant events which have the most highly volatile data and improving the forecasting accuracy will be showed based on some mathematical criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE), Root Means Squared Error (RMSE), Akaike information criterion. These results will be implemented using MATLAB software and R- software.

An entropy-based initialization method of K-means clustering on the optimal number of clusters

Clustering is an unsupervised learning approach used to group similar features using specific mathematical criteria. This mathematical criterion is known as the objective function. Any clustering is done depending on some objective function.K-means is one of the widely used partitional clustering algorithms whose performance depends on the initial point and the value of K. In this paper, we have combined both these parameters. We have defined an entropy-based objective function for the initialization process, which is better than other existing initialization methods of K-means clustering. Here, we have also designed an algorithm to calculate the correct number of clusters of datasets using some cluster validity indexes. In this paper, the entropy-based initialization algorithm has been proposed and applied to different 2D and 3D data sets. The comparison with other existing initialization methods has been represented in this paper.

Structural and mathematical models of software and hardware platform of the training complex

The article discusses the problem of formalizing the structure of software and hardware platform training complex based on a controlled treadmill. The general structure of the platform components is formulated. A mathematical model is developed for an omnidirectional platform in notation of set theory. The criteria for optimizing the software and hardware platform were selected: economic costs, compliance with structural characteristics, energy efficiency; quality indicators. Structural and mathematical models and criteria will allow the design and optimization of the hardware and software platform for the training complex.

ВЕРОЯТНОСТНАЯ МОДЕЛЬ РАСЧЕТА УРОВНЯ БЕДНОСТИ ПРИ РАЗНЫХ ФОРМАХ ПОДОХОДНОГО НАЛОГООБЛОЖЕНИЯ

The article highlights a probabilistic model constructed for calculating the number of poor and the total income tax levied on all taxpayers under different income tax systems. There is considered the proportional income tax system adopted in the Russian Federation, as well as single-stage systems with both fixed and variable tax rates, in which individuals with low incomes are exempted from income tax. For these tax systems there have been found the dependences of the expected value of the number of the poor and the total income tax on the tax rate, tax-free minimum, and also on the laws of probabilities distribution of total income and the living wage of an individual. A numerical simulation of the found dependences was carried out. The conditions under which the abolition of income tax for individuals with low incomes reduces the number of poor were determined. Mathematical criteria are formulated with the help of which it is possible to assess the feasibility of moving from a proportional system to single-stage income tax systems.

Backward extrapolation technique: analysis of different criteria after supramaximal exercise in cycling

Backward extrapolation technique (BE) was used to estimate V̇O<inf>2</inf> from postexercise measuring, eliminating oronasal mask (OM) during the efforts. Despite its advantage, literature presents discrepancy in applied methods. Thus, the first aim of this study was to compare different mathematical criteria to estimate values of V̇O<inf>2</inf> during a supramaximal effort (V̇O<inf>2PEAK</inf>), while the second aim was to verify the effects of OM on cycling performance. Twenty-four male cyclists (35±6 years, 81.3±8.9 kg, 180±6 cm) performed three days of tests, with at least 24 h of interval between each test. Firstly, a graded exercise test was applied to determine V̇O<inf>2max</inf> and your correspondent intensity (MAP). The second and the third day were destined to supramaximal efforts at 120% of MAP, performed with (Supra<inf>mask</inf>) and without (Supra<inf>be</inf>) oronasal mask (OM) in a randomized order. After Supra<inf>be</inf>, OM was coupled, and BE was applied. Sixty-six values of V̇O<inf>2</inf> were obtained based on a linear regression fitting. V̇O<inf>2peak</inf> can be estimated using different curve lengths. However, only curves between 20 and 60 s with extrapolation to 3 s or lesser shows at least one consistent criterion. The 60 s curve extrapoled to -3 s was the most accurate criteria (P=0.723; ES=-0.055; r=0.824; Bias=-0.36 and LoA=7.72 mL.kg.min-1). Performance was not impaired with OM and was similar in both condition (P=0.84, ES=0.04). We conclude that it was possible to accurately estimate V̇O<inf>2</inf> values of a supramaximal effort without any respiratory apparatus with a time-efficient analysis. Therefore, we recommended the use of a 60 seconds V̇O<inf>2</inf> curve analysis with a negative extrapolation for 3 seconds.

Application of Lyapunov's Methods for Analyzing the Stability of a Tubular Chemical Reactor with Recycle

AbstractThe first and second Lyapunov methods were adapted to analyze the stability of a tubular chemical reactor with recycle. The criterion of local stability in the form of inequalities was derived using Lyapunov's first method. It is an explicit algebraic form, despite the fact that the mathematical model of the reactor is a partial differential problem with a boundary condition. As part of the second Lyapunov method, a mathematical criterion for non‐local stability was derived in the form of an increase of Lyapunov's function. Both criteria are presented on graphs.

Methodology of selective metallic thin film ablation from susceptible polymer substrate using pulsed femtosecond laser.

Electronic devices on flexible polymeric substrates allow new fields of applications. A maskless and flexible structuring process for such systems is offered by ablation using ultra-short pulse laser irradiation. Hereby, certain areas of a functional thin film coating (e.g. nickel-chromium) are locally removed from a substrate (e.g. polyimide) to yield the needed device structures. Micro laser patterning quality is influenced by the beam properties (beam profile, fluence) as well as by the pulse overlap, the substrate material and many other factors. A clear distinction must be made between the material ablation at the surface of a bulk material and the substrate selective removal of a thin metallic film. For the latter, general rules for the prediction of ablation results especially in the case of areal ablation, which were not known from the literature so far, are derived here in the form of mathematical criteria. A methodology for the parameter finding in different cases of ablation (dot, line, areal) is presented and exemplified using a practical example, but is also applicable to other flexible thin film based systems.

A method for faster application of process integration techniques in retrofit situations

Numerous process integration techniques were proved to be highly effective for identifying and estimating potential energy savings in the industry. However, they require high time and effort to collect and analyse process data. As a result, they do not constitute the common practice in the industry and opportunities for increasing the energy efficiency of industrial processes are missed.The paper presents a method, termed the “Energy-Saving Decomposition”, which is based on Process Integration techniques. It is intended for expeditiously outlining and promoting energy efficiency in the industry. Two screening tools, based on mathematical criteria and engineering experience, are employed for reducing the problem dimension before applying conventional design procedures. The first step disregards streams based on their contribution to the overall energy-saving potential, calculated utilising a novel energy-saving decomposition technique. The most promising network is then selected based on its energy-saving potential and size. The second step reduces the problem complexity further, employing economic considerations.This novel method was exemplified by application to a dairy factory: the outcomes and the method itself were compared to conventional Pinch Analysis techniques. The results showed that the developed method can simplify and reduce the time consumption of conventional Process Integration methods significantly, while identifying the most encouraging saving opportunities. The automatic algorithm allowed for reducing the problem size from 62 process streams of the existing plant to 22 streams requiring a computational time of only 135 s. The final retrofit design proposed was the same obtained with conventional Pinch Analysis, achieving a 23% reduction in the plant final energy consumption.

Mechanistic insights into NO‒H2 reaction over Pt/boron-doped graphene catalyst

This work presents a systematical experimental and density functional theory (DFT) studies to reveal the mechanism of NO reduction by H2 reaction over platinum nanoparticles (NPs) deposited on boron-doped graphene (denoted as Pt/BG) catalyst. Both characterizations and DFT calculations identified boron (in Pt/BG) as an additional NO adsorption site other than the widely recognized Pt NPs. Moreover, BG led to a decrease of Pt NPs size in Pt/BG, which facilitated hydrogen spillover. The mathematical and physical criteria of the Langmuir-Hinshelwood dual-site kinetic model over the Pt/BG were satisfied, indicating that adsorbed NO on boron (in Pt/BG) was further activated by H-spillover. On the other hand, Pt/graphene (Pt/Gr) demonstrated a typical Langmuir-Hinshelwood single-site mechanism where Pt NPs solely served as active sites for NO adsorption. This work helps understand NO-H2 reaction over Pt/BG and Pt/Gr catalysts in a closely mechanistic view and provides new insights into roles of active sites for improving the design of catalysts for NO abatement.

Analysis of Dynamics Targeting CNT-Based Drug Delivery through Lung Cancer Cells: Design, Simulation, and Computational Approach.

Nowadays, carbon nano (CN) structures and specifically carbon nanotubes (CNTs), because of the nanotube’s nanoscale shape, are widely used in carrier and separation applications. The conjugation of CNTs with polysaccharide, proteins, drugs, and magnetic nanoparticles provides a chance for smart targeting and trajectory manipulation, which are used in the crucial field of life science applications, including for cancer disease diagnostics and treatments. Providing an optimal procedure for delivering a drug to a specific area based on mathematical criteria is key in systemic delivery design. Trajectory guidance and applied force control are the main parameters affected by systemic delivery. Moreover, a better understanding of the tissue parameters and cell membrane molecular behaviour are other factors that can be indirectly affected by the targeted delivery. Both sides are an essential part of successful targeting. The lung is one of the challenging organs for drug delivery inside the human body. It has a large surface area with a thin epithelium layer. A few severe diseases directly involve human lung cells, and optimal and successful drug delivery to the lung for the treatment procedure is vital. In this paper, we studied functionalized CNTs’ targeted delivery via crossing through the lung cell membrane. Molecular dynamics (MD) software simulated all the interaction forces. Mathematical modelling of the cell membrane and proposed delivery system based on the relation of velocity and force has been considered. Dynamics equations for CNTs were defined in the time and frequency domain using control theory methods. The proposed delivery system consists of two main parts: crossing through the cell membrane and targeting inside the cell. For both steps, a mathematical model and a proper magnetic field profile have been proposed. The designed system provides criteria for crossing through the cell membrane within 30 s to 5 min and a translocation profile of 1 to 100 Å.

Implementing QVT-R via semantic interpretation in UML-RSDS

The QVT-Relations (QVT-R) model transformation language is an OMG standard notation for model transformation specification. It is highly declarative and supports (in principle) bidirectional (bx) transformation specification. However, there are many unclear or unsatisfactory aspects to its semantics, which is not precisely defined in the standard. UML-RSDS is an executable subset of UML and OCL. It has a precise mathematical semantics and criteria for ensuring correctness of applications (including model transformations) by construction. There is extensive tool support for verification and for production of 3GL code in multiple languages (Java, C#, C++, C, Swift and Python). In this paper, we define a translation from QVT-R into UML-RSDS, which provides a logically oriented semantics for QVT-R, aligned with the RelToCore mapping semantics in the QVT standard. The translation includes variation points to enable specialised semantics to be selected in particular transformation cases. The translation provides a basis for verification and static analysis of QVT-R specifications and also enables the production of efficient code implementations of QVT-R specifications. We evaluate the approach by applying it to solve benchmark examples of bx.

Analysis of Mathematical Communication Capabilities in Completing Problems in Matrix Materials Based on Solo Taxonomy

The purpose of this study is to describe the mathematical communication skills based on SOLO Taxonomy in students of class XI of Mathematics and Natural Sciences Muhammadiyah 3 Batu in solving problems on matrix material. This type of research is descriptive qualitative, where the subject is 17 students of class XI MIPA. The method of collecting research data uses test instruments. Based on the results of data analysis, it can be concluded thatas many as 4 students with very good mathematical communication skills criteria, 6 students with good mathematical communication skills criteria, 7 students with sufficient mathematical communication ability criteria and students. Whereas for students with written mathematical communication skills criteria lacking none. Students are in very good criteria, able to solve Unistructural - Relational level problems in SOLO Taxonomy. Meanwhile, students with good written mathematical communication skills are able to solve Unistructural level questions and Multistructural levels in SOLO Taxonomy. Then students with written mathematical communication ability criteria are quite capable of solving Unistructural level problems in SOLO Taxonomy.The average of written mathematical communication skills is in good criteria with the average value of written mathematical communication skills, namely 61.95, so that the average student is able to solve problems at a level Unistructural - Multistructural on SOLO Taxonomy.

Optimal Testing in Semiconductor Manufacturing

We present an algorithm and discussion for minimizing processing and testing costs of a semiconductor manufacturing line. The core concept is that the testing at each process step has a nonzero cost. We derive the mathematical criteria to choose optimally, based on all future processing and testing costs and test failure probabilities, whether or not to perform testing at each process step. The formulation and implementation of the algorithm is necessarily an “engineering-side” activity. Yet, as the goal is the optimization of the business pertaining to processing step costs, the Chief Financial Officer has a critical role to play. Both Finance and Engineering must collaborate in the optimal testing platform we propose. Finance, rather than Engineering, bears the fiduciary and management responsibility to estimate and report processing and testing costs in the financial statements.

Hub-Periphery Hierarchy in Bus Transportation Networks: Gini Coefficients and the Seoul Bus System

Bus transportation networks are characteristically different from other mass transportation systems such as airline or subway networks, and thus the usual approach may not work properly. In this paper, to analyze the bus transportation network, we employ the Gini coefficient, which measures the disparity of weights of bus stops. Applied to the Seoul bus system specifically, the Gini coefficient allows us to classify nodes in the bus network into two distinct types: hub and peripheral nodes. We elucidate the structural properties of the two types in the years 2011 and 2013, and probe the evolution of each type over the two years. It is revealed that the hub type evolves according to the controlled growth process while the peripheral one, displaying a number of new constructions as well as sudden closings of bus stops, is not described by growth dynamics. The Gini coefficient thus provides a key mathematical criterion of decomposing the transportation network into a growing one and the other. It would also help policymakers to deal with the complexity of urban mobility and make more sustainable city planning.

New methods and equipment for the machining of cross-axes parts- Case study

The processes and equipment for manufacturing, assembly, and control operations, adapted to the needs of modern industry, shall be determined according to the volume of production and the technical conditions imposed, at a level which ensures economic effects on the recovery of costs for their design and execution. The design-optimization algorithm, with the four working steps, applied on the case study presented, allows the determination of the optimal number and succession of technological processes, but also of new processing methods, based on a technological graph and optimization criteria. In the second step, determine for each technological operation the optimal orientation and fixation scheme of the analyzed part, combining elements of the set theory and the global utility method, with a method of simultaneous optimization of the orientation and fixation fundamentals for two different transformation areas with distinct quotas and conditions that need to be achieved. In the third step, is identified and analyzed several construction variants of structures for the equipment. By formulating a technologically adapted graph to describe structures of orientations, but also other structures, is obtained an associated mathematical model and optimization criteria for the optimum design variant of the orientation and fixation at the analyzed operation. When is desired a complete appreciation of all the technological operations, the fourth step of system optimization is proposed, which is also based on a technology graph and an associated mathematical model adapted to the evaluation of the analyzed types of equipment.

Quality Management of Educational Activities in the Training of Specialists in the Field of Health Care: the Case of Ukrainian Medical HEIs

The paper addresses the current background, shortcomings and improvement perspectives for the quality management system in training nurses, paramedics and midwives in HEIs of Ukraine. To reach the aim of the study, the authors analysed the legal and regulatory documents, website documentation and electronic resources of 23 medical HEIs. The methods of mathematical data processing and criterion analysis were used to analyze the effectiveness of the quality management system implementation medical HEIs. The survey of the managerial and administrative staff (n=398) was conducted. The aim of the survey was to gain insight into the internal quality management principles and procedures in medical higher educational institutions of Ukraine, to identify the main tools used for internal auditing of educational quality, the measures taken to assess the education quality at the institutional level. The research findings are discussed with due regard to the surveyed managerial staff needs and quality assurance guidelines in medical education. The results of the article have a few significant implications for practice of quality management system in medical colleges and its perspectives for enhancing Ukrainian higher education system. The conclusion was made that with introducing an effective quality management system in medical HEIs, continuous monitoring of quality assurance by HEI leaders, commitment to quality as an organizing factor in education management, future medical specialists will be competitive, demonstrating a sustainable growth in academic performance, developing relevant practical skills and professional mindset. https://doi.org/10.26803/ijlter.19.8. 20

Framework of model selection criteria approximated genetic programming for optimization function for renewable energy systems

Abstract For the realization of complex renewable energy systems (such as nano-fluids based direct absorption solar collector), an evolutionary system identification method such as genetic programming (GP) can be applied to develop mathematical models/functional relationships between the process parameters. The system complexity is attributed to interaction among the design variables influencing the outputs. There are also uncertainties in the system due to random and unknown variations in the design and response variables. GP suffers from the higher complexity structure of its solutions and non-optimal convergence, which leads to poor fitness values. Therefore, to address these uncertainties and problems, the framework based on the model selection criteria approximated genetic programming (MSC-GP) is proposed for the formulation of geometry design based thermal efficiency and entropy generation optimization function for direct absorption solar collector (DASC) system. In this proposed method, the four mathematical model selection criteria are used as an approximation for objective functions in GP framework for the evaluation of fitting degree and structure of the model. The results based on statistical measures (best fitness, mean fitness, standard deviation of fitness, number of nodes) show that models obtained from the mathematical selection criteria, Predicted Residual error sum of squares (PRESS), have performed the best. Based on Pareto front analysis of PRESS function, it is found that the best objective values and the number of nodes of models (complexity) follows more or less gradually slow increasing trend which is a good symbolic desirable sign of minimal increase of complexity of model with a decrease in objective values as the values of generation increases. The results of the sensitivity analysis show that the main factor affecting the efficiency of DASC is its geometry of the structure. 3-D interaction analysis shows that increasing the thickness, length and reducing the width of the collector can make the system maintain its higher thermal efficiency and a smaller entropy generation, which is useful for the optimized operation of DASC. Non-dominated sorting genetic algorithm-II (NSGA-II) is applied in the acquisition of the optimal geometric settings of DASC system based on the selected models. The optimal settings achieved is 5 cm in length, 5 cm in width, and 2 cm in thickness. Systems when operated using these settings results in a satisfactory performance with 77.8117% in thermal efficiency and 6.0004E+3 in entropy generation).