Search

The paper discusses a mathematical model for describing heat distribution in the surface layer of soil from various sources of heat, or cold, which, together with seasonal climatic changes, form unsteady thermal fields in the soil. The developed algorithms are focused on high-performance computers and were used in the design of various oil and gas fields located in permafrost zone. The main attention is paid to adequate setting of boundary conditions and maximum consideration of various parameters, including technical characteristics of engineering objects, climatic conditions and soil lithology in the field of modeling thermal fields. The presented numerical calculations show the possibility of using these models and algorithms for forecasting of the development of thermal processes in the soil. Minimization of heat effect of the systems inserted into permafrost will avoid accidents, in particular, at oil and gas fields related to the changes in temperature of the soil, and increase the stability of the building with pile foundations. In the paper the possibility of the heat impact compensation in permafrost is discussed. [ABSTRACT FROM AUTHOR]

Defining the reliability parameters of power converters is a complex task which requires a detailed analysis of their design, elements and blocks used, as well as the functional connections between them. Each conversion system is likely to use a different circuit, different types of electronic elements, different operating modes of those elements and different ambient conditions. Therefore, the reliability analysis is difficult to do and it is hard to use only one reliability analysis method. In addition, it is difficult to give a clear and unequivocal answer regarding the number of failures, the time during which failures will occur, and the state in which the electronic equipment will be within a given period of time. The following probability states could be summarized for electronic converters: operability, failure, protection, availability and redundancy. To do that type of analysis, Markov used, which allows the design Analysis is of reliability analysis models that could be used for enhancing the reliability of power converters for wireless energy transfer systems. [ABSTRACT FROM AUTHOR]

The model is a system of two nonlinear ordinary differential equations (ODEs) with dependent variables: the number of bees working in the hive and the number of bees that work outside the hive referred here as foragers. The population dynamics is studied. In this small study we present an effective simple algorithm to solve the parameter identification problem of the model in [10]. The parameters are identified using a least square method combined with backward Euler approximation of the ODE system and a Newton method technique for optimization of the cost functional. Numerical results of the parameters, representing the solution to the inverse problem are provided. [ABSTRACT FROM AUTHOR]

The study aims to apply multicriteria mathematical model to determine the optimal honeybee colony's location in regions without overpopulation. The approach including two optimization criteria: 1) One criterion maximizes the beekeeper's desire to distribute bee colonies in certain places. 2) The other criterion minimizes the possibility some bee colonies not be able to be fully nourished. The optimal Pareto solutions have been found in the proposed multicriteria model. In the first decision, a higher value of the first criterion is observed, ie the beekeeper's wishes regarding the location of the hives are given priority over the non-fed hives. In the second solution, greater priority is given to the feeding of bee colonies, as a result of which the number of non-fed bee colonies has decreased. The model is also applied on a real apiculture example of experimental apiaries in Batishnica region (50 km far from Ruse) without overpopulation of the studied area. The optimal distribution of the hives in places has been found. From the fact that the area is without overpopulation, it follows that all beehives will be fed and practically the task is one-criteria, with priority given to the potential location of the hives. [ABSTRACT FROM AUTHOR]

Inverse, or coefficient identification problem for honey bee colony population model is considered. On the base of the numerical solution to a weakly coupled system of ordinary differential equations (ODEs) with initial conditions, specific constant parameters are found by minimization of a quadratic discrete functional, which expresses the difference between the computed and measured numbers of bees working in and outside the hive. The optimization procedure uses quasilinearization which assures second order of convergence. Numerical simulations with synthetic and real data are discussed. [ABSTRACT FROM AUTHOR]

We investigate a specific ill-posed nonlinear inverse problem that arise on the financial markets. Precisely, as a benchmark problem, we consider the simultaneous recovery of implied volatility and interest rate functions over a finite interval corresponding to call and put prices for idealized continuous European vanilla options over the same maturity. In order to find these time-dependent functions, we minimize the cost functional which is the sum of the squared error between the market values and the computed values, obtained by implicit difference scheme for the Black–Scholes model. Furthermore, results of numerical experiments are discussed. [ABSTRACT FROM AUTHOR]

We enrich the known applications of coupled best proximity points theorems for ordered pair (F; G) of cyclic contraction maps. We present a procedure to construct such pairs of cyclic contraction maps that will give the best possible rate of convergence, when solving linear systems. We give numerical computations for the a priori and a posteriori error estimates, obtained by a sequence of successive iterations. We give an upper bound for the best possible rate of convergence if coupled best proximity points theorems are used to solve these linear systems. We illustrate some newly obtained generalizations about coupled best proximity points with a number of example. [ABSTRACT FROM AUTHOR]

We deal in this paper with functions of the type f (t , x) = ∑ k = 0 ∞ a k (t) x k where t ∈ T, x ∈ X. In what follows we shall consider different types of spaces T it supposed to be a separable metric space of different kinds and X, which suppose to be some kind of a topological algebra. Next suppose that a k (t) k ∈ ℕ + is a partition of unity. More generally c α (t) α ∈ N + n we consider here a complex - valued (if necessary) partition of unity in ℝn with multi-indexes if n > 1. A partition of unity is locally finite hence the function f (t, x) is a polynomial concerning the variable x which should explain the name of this note. Note that x it may belong to various algebras, Banach one, operator algebras, functional algebras one etc. The aim of this note is to see how this point of view may help to solve some problems of mathematical physics in non-standard way. It may be Banach of different types, some Lie algebra etc. Here is our basic stock of examples: 1) Consider a topological space T and countable partition of unity {ak (t)}, (k ∈ N+) in it. Clearly that there is a locally finite open (or even point finite) cover U = {Uk} (k ∈ N+) for which supp (ak) ⊂ Uk. Because ordtU < ∞ we have ak ≡ 0 for almost all k and thus f (t , x) = ∑ k = 0 ∞ a k (t) x k is a polynomial of x ∈ X for every point t ∈ T. Note that we suppose here that X admits algebraic structure a field or a module or a ring, and it is not necessary to be loaded with some topology. 2) In addition, we can consider some structures on T or X. For example, if T = ℝn and ak(t) ∈ C∞(ℝn) then one may consider derivatives ∂tαf(t, x), so ∂ α f (t , x) = ∑ k = 0 ∞ ∂ t α a k (t) x k where α = (α 1 , α 2 , ... , α n) ∈ ℕ + n is a multi-index. Moreover, if X is an n-dimensional Euclidean space ℝn one can consider the function f (t , x) = ∑ | α | = 0 ∞ a α (t) x α where as usual x α = x 1 α 1 x 2 α 2 ⋯ x n α n follows next then for an arbitrary differential operator D we have D f (t , x) = ∑ | α | = 0 ∞ D (a α (t) x α) ; (1) note that we deal here with finite sums. In the following text we discuss some properties and examples of "analytical" functions of polynomial type. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new method for solving fuzzy partial differential equation (FPDE) using double fuzzy Natural transform (DFNT). We provide fundamental results of the double fuzzy Natural transform for fuzzy partial derivatives of the m-th order. By using them we construct the solution of fuzzy partial differential equation. We show that DFNT method is a simple and reliable approach for solving such equation analytically. Finally, we give illustrative example to show the ability of the proposed method. [ABSTRACT FROM AUTHOR]

Many prognosis studies have been conducted for a long time. There are many established and widely accepted prediction methods, such as linear extrapolation and SARIMA. However, their performance is far from perfect, especially when the time series is highly volatile. In this paper, we propose a hybrid prediction scheme that combines the classical SARIMA method and the wavelet transform (WT). Wavelet transform (WT) has emerged as an effective tool in decomposing time series into different components, which allows for improved prediction accuracy. However, this issue has so far been insufficiently tested and tried to predict different time series. Our goal is therefore to integrate modeling approaches as a decision support tool. The results of an empirical study show that this method can achieve high accuracy in prediction. Based on the results of the created model, it can be stated that the hybrid WSARIMA model overperformed the SARIMA model. [ABSTRACT FROM AUTHOR]

Inverse or identification problem for subsurface flow in unsaturated soil is considered. On the base of the numerical solution of Richards' equation with initial and boundary conditions, material parameters on the constitutive relations of the exponential model are restored. It is done by minimization of a quadratic functional, which express the sum of differences between the computed and experimental values of the pressure potential at finite number of times. The optimization uses Levenberg-Marquardt method which provides fast convergence. Numerical results are discussed. [ABSTRACT FROM AUTHOR]

In this paper we propose a numerical method for solving regime-switching problem with power utility function. The model is a system of parabolic equations with non-linear gradient term and weakly coupled by exponential non-linearity. First, we approximate the gradient term, involving an auxiliary non-linear function, then we construct implicit-explicit finite difference discretization. We prove discrete comparison principle and on this base we establish minimum principle, i.e. we prove that the numerical solution has the same lower bound as the exact solution. Convergence result in maximal norm is obtained. Numerical results, confirming the theoretical statements are provided. [ABSTRACT FROM AUTHOR]

Contemporary digital world is based on information and communication technologies for remote access to distributed resources located in different nodes of the global network. Many of these resources are virtual and include technical equipment, program tools, data and other information objects, including personal data. In this respect, the protection of the information resources must be very important task for all organizations. The paper deals with an organization of a secure business system with implementation of protected access to different types of information resources, united in a global virtual space. Supported resources are determined as a public information (without strong protection, including stored in the cloud) and private information (which must be protected by special procedures and tools). A general structure is proposed and the algorithmic scheme for activation is developed. The goal of the article is to investigate the effectiveness of the proposed procedures for regulated access to protected information by using analytical modelling. In this reason a discrete model based on the theory of Petri nets is designed and used to evaluate the functionality of the proposed approach. The execution of the analytical model is made by constructing the tree of reachability. [ABSTRACT FROM AUTHOR]

In this paper, we find approximate solution of the nonlinear Volterra-Fredholm fuzzy integro-differential equation (NVF-FIDE) by using Adomian decomposition method (ADM). We convert this equation to a nonlinear system of Volterra-Fredholm integro-differential equations in crisp case and find an approximate solution of this system. Hence, we obtain an approximation for the fuzzy solution of the nonlinear Volterra-Fredholm fuzzy integro-differential equation. A numerical example is given to demonstrate the validity and applicability of the proposed technique. [ABSTRACT FROM AUTHOR]

In this work, we investigate two-dimensional nonlinear Hammerstein-Fredholm fuzzy functional integral equation (2D-NHFFFIE. We propose an efficient iterative method of successive approximations by using fuzzy variant of the cubature rule of the rectangle for classes of fuzzy number-valued functions of Lipschitz type for two-dimensional case to approximate the solution. We prove the convergence and numerical stability of the presented method with respect to the choice of the first iteration. Finally, some numerical experiment confirm the theoretical results and illustrate the accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

It is well known that a necessary condition for the existence of an integer order derivative at a given point is that a left-side derivative exists at that point, that a right-side derivative exists at the same point, and that they coincide. The aim of the present paper is to analyze the possibility of coincidence of the left-side and right-side Caputo fractional derivatives on an interval. We prove, that a function whose left-side and right-side Caputo fractional derivatives coincide on an given interval, can be only a constant. As a consequence we point out why some "results" obtained under this assumption are wrong. [ABSTRACT FROM AUTHOR]

In the present work we obtain existence of positive solutions for a class of third order equations with parameter depen- dence. The exact expression of the related Green's function is given and some of its properties are proven. Although the Green's function is not positive, the obtained solutions are still positive. The results are based on the classical Krasosel'skii's fixed point theorem in cones. [ABSTRACT FROM AUTHOR]

In this work, we extend and complement some results in the field of fixed point theory in view of general and wider structures, such as b−spaces (respectively b−metric and b−metric-like spaces). Considering existing classes of Z− contractions and Ψ− simulating functions with a solid impact in database results of fixed point theory (can see [1]-[3], [8]-[16], [18]-[21]), we introduce a new general class of simulating functions called as Ψ− s simulation functions, and also types of KΨ−s − contractions in a more general framework. This approach covers, extends and unifies several work considered in the existing literature. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is a very promising field of development, in many directions. It is widespread in computer technology (biotechnology, nanotechnology, Internet of Things, etc.) as well as in robotics, 3D printing, quantum computing, and many more. Using it to predict and defend from cyber attacks is another of its many applications. In conduct of a project to study the security of cyber-physical connections in the context of next-generation computer networks, an overview of AI methods and their application in Industry 4.0 has been made. More attention has been given to the application of AI as a mean of protecting technologies such as SCADA, industrial Internet of Things, and in general cyber- physical connections. The aim of this study is to present and compare different methods of AI for fighting cyber attacks, or rather their application in systems for detecting and preventing intrusions in the field of the technology mentioned. [ABSTRACT FROM AUTHOR]

This paper aims to present an approach which automates electronic circuit design. It is based on index matrices with real number elements and their software implementation. Both they are developed by the authors as an example of universal tool on a wide class of electrical devices, and this approach is performed for complex components which have more than two terminals (functioning of PID-regulators is implemented). Designed programming classes are used in a.NET application in order to handle electronic circuits, and simulation on power converters functioning is presented. [ABSTRACT FROM AUTHOR]

Regression is a powerful technique for predicting a single scalar value with a high degree of certainty. A regression model requires a dataset that consists of only numeric features. However, datasets frequently contain both numeric and categorical features. This paper sets out to study several different text encoding techniques, which can solve this problem by transforming a certain text value into a corresponding numerical value that is statistically sane in relation to the dataset. The scenario we study is a neural network regression model predicting support case durations. Many of the dataset's features are indeed categorical such as issue description, team, username, severity and impact among others. The most challenging aspect of the encoding is the resulting change of the dimensionality of the dataset. Every encoding method affects the dimensionality in various degrees depending on the feature cardinality. This result is the main challenge for the tuning of the neural network hyperparameters. We must make such a setup that can robustly handle the altered dataset. The paper compares five different approaches for encoding: one-hot, hashing, binary, target and entity embeddings. The hyperparameter settings for each approach are presented by using common neural network performance metrics and a baseline neural network setup. We can conclude that a moderately increased dimensionality can enhance the model's predictive power as observed in the case of the binary and the hashing encoder [ABSTRACT FROM AUTHOR]

Human resource management is the strategic approach to effectively managing people in a business or organization so that their business contributes to gaining competitive advantage. Many human resource management tasks are based on finding and matching individuals to positions. In this paper an ontology-based approach is presented for effectively matching job seekers and job positions over multiple criteria by making use of different skills ontologies, for discovering a set of profiles that best fits the job description criteria and ranking applicants. The general architecture of the framework is outlined and ontologies operations are described. [ABSTRACT FROM AUTHOR]

The article aims to explore the relationship between readability of texts from instructions (assignments texts, technical documentation, law/regulation texts) and the corresponding source code (task solution) from a particular education resource for programming on the topic with neural/positive sentiment 'identity documents'. The article examines two types of studies: one of applying software metrics and second one from empirical research of text understanding for a target group of 15 years old students (on texts and programming source code). The results are a strong foundation for continuing research in order to receive objective methodology for readability for the people of this age. This has both research and also publishing companies' business added value as objective recommendations for the authors of the textbooks and also for teachers in Computer Science and languages for general teaching practices. [ABSTRACT FROM AUTHOR]

Fuzzy logic is successfully used in the area of control systems where different problems are decided in flexible way leading to more efficient systems' performance. Such approach is suitable when the modeled system is complex and some parameters cannot be defined precisely. In this paper a fuzzy model of improved cooling water control system utilized in plastic pipes production is proposed. Its aim is more effective regulation of the freon compressor load to be achieved that influences on economy in energy consumption. The developed model is verified through simulation in FisPro environment where the knowledge base, fuzzy membership functions and inference engine are modeled. [ABSTRACT FROM AUTHOR]

Utilization of machine learning in electronics and in computer-aided design is in progress, giving an opportunity the electronic circuits to be studied in a new way that also contributes to automation of some engineering tasks. In this paper, a novel methodology for analysis and design of Gm-C filters is presented. It is based on applying classification machine learning algorithm Random Forest on theoretically gathered data sets and on published scientific results. The tree-based algorithm is chosen, because of its capability not only to identify the correct class for every training sample and to point out the decision, but also to give explanation related to this decision and to outline a set of rules. The proposed methodology is verified through creation of several data models. Gm-C filters are chosen for exploration because of their extensive usage in computer and communication systems, medical devices and sensors. [ABSTRACT FROM AUTHOR]

Data analysis, processing and visualization determine the main features of Business Intelligence (BI). BI technologies track and present a large amount of structured and unstructured information in relational tables. They create complex visual reports using customized tools and calculations. The end user of the visual pays attention not only to the included slicers, charts and tables in the dashboard, but also to the speed of the query by which the current dataset is processed. The last factor is crucial to the performance of such interactive data visualizations. In this paper we will consider different techniques for optimization of data reports which can derive to fast and meaningful representation of data. Also, some useful practices will be suggested which cover important aspects such as model structuring, relationship management and syntax complexity. [ABSTRACT FROM AUTHOR]

In the field of interactive reporting, the application of information technology has a place in both analysis algorithms and data presentation techniques. Processing and visualization of certain collected information is a process in which it is of particular importance to rely on a clear structure for sharing information through different visual components. Often the analyzed client data is unstructured, which in turn is a prerequisite for customized solutions. The development of such visualizations gives the opportunity each report to represent the provided data in the most optimum and understandable way. In this paper, several technologies will be considered for building custom components for visuals. Additionally, an optimal service-based option for developing visuals, which can be used for different data structures, will be suggested. By the help of a particular test visual it will be conducted a comparative analysis to weigh the advantages and disadvantages of the most popular technologies. [ABSTRACT FROM AUTHOR]

Deferential Drive Mobile Robot (DDMR) is being used in many applications as it is easy to be modeled and controlled. This research presents the idea of using DDMR turning motion behavior to develop an algorithm that calculate all the circular trajectories. This can be used to navigate DDMR in a curvature paths instead of linear ones. In this research we design and simulate Differential Drive Mobile Robot (DDMR) model. Then we use the simulated model to calculate all the possible trajectories that DDMR can follow with each left and right wheel velocity configurations. Results are saved in a navigation look-up table that can be implemented in DDMR navigation's approach. [ABSTRACT FROM AUTHOR]

The triangle meshes are often used to approximate smooth or piecewise smooth surfaces. Improving the uniformity of the approximation error distribution is crucial for the mesh quality. In order to achieve such improvement it is often necessary to increase the mesh resolution (by introducing new mesh vertices and triangles) where needed depending on a local estimator for the error distribution. Usually such estimators work per triangle producing an estimation for the local mesh curvature or the local deviation from the target surface. Many methods for subdivision of triangle meshes have been developed in the recent decades. The major flaw in most of them is the tendency to produce poor quality subdivided meshes when working on (starting from) irregular meshes. Even starting from a regular mesh which unevenly approximates the target surface, most methods tend to produce poor quality result (bad triangles aspect ratios and/or highly irregular mesh connectivity in some regions). Our research shows that the main problem with most of the methods is that they don't control the aspect ratios of the newly produced triangles and their close vicinity during the subdivision. Another flaw in most of the existing approaches is that the interpolant they construct doesn't behave well on highly irregular meshes (highly constrained and/or low quality) which often produces bumpy meshes as a result. Here we take advantage of the 2.5D type of the meshes that we process which allows us to simplify the interpolant and make it more stable in the irregular cases. In this paper we present a smooth interpolating subdivision approach for refinement of irregular 2.5D triangle meshes. It combines an edge-splitting subdivision with a Hermite-based smooth interpolation of the triangle mesh. Working on 2.5D meshes (defined in 2D domains) makes the task simpler so that the only thing required from the interpolant is to calculate the elevations on the target interpolation surface for the new mesh vertices introduced by the subdivision. The interpolant provides the data for the estimation of local approximation error at each subdivision step used to decide whether the target surface is locally well approximated (which is the stop criteria for the subdivision process). At the same time, the method estimates how well the local mesh quality is being maintained after each subdivision step, analyses the possibilities to improve the triangles aspect ratios and applies them whenever possible which also speeds up the convergence of the overall process. The described approach produces multiresolution triangle mesh which uniformly approximates the smooth interpolation surface while maintaining the mesh quality. [ABSTRACT FROM AUTHOR]

In this report we propose a new steganographic method that allows to be transmitted through social networks stego information. The basis of the method is pre-grouping and classifying a large number of graphical images based on the type of their histograms. By selecting of images with suitable histogram and placing them in the appropriate place in the series of the published album, the formation of the hidden message is achieved. Since no changes are made to the images, the resulting stego channel has a high level of undetectability. The results of the experiments show that the appropriate selection of image classification criteria achieves good resistance of stego channel regardless of the impact of social networks. The proposed method is suitable for transmitting crypto and stego keys. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel hash function based on Zaslavsky chaotic map. Exact study has been provided on the novel algorithm using distribution, sensitivity, statistic analysis of diffusion and confusion, and collision analysis. The experimental data shows that the proposed hash function satisfied a high level of data security. [ABSTRACT FROM AUTHOR]

We present a novel double Ikeda map based source of pseudorandom numbers. Exact study has been presented on the novel generator using seed value calculation, linear complexity measurement, and statistical analysis with PractRand and ENT applications. The result proves that the generated bytes have excellent characteristics of pseudorandomness and resistance to different statistical attacks. [ABSTRACT FROM AUTHOR]

We propose a novel shrinking pseudorandom byte generator based on Ikeda functions with 128 bit computational precision. The result of the analysis shows that the novel scheme ensures a high security in the data encryption process. The computation is based on a GNU portable C library for arbitrary-precision binary floating-point computation with correct rounding, based on GNU Multi-Precision Library. [ABSTRACT FROM AUTHOR]

Big data transform all kinds of businesses, including property management. Although the application of big data has great potential, it also presents challenges. The purpose of this paper is to investigate the big data capabilities and to identify some of the obstacles and opportunities associated with them in the context of property management. The applied approach of the research is content analysis of scientific publications, practical examples and case studies, concerning the present applications of big data in the property management sector. The findings show that big data have an increasing impact on the assessment and understanding of property markets. The study is useful for other researchers, who work in the field of big data, including property management professionals and practitioners. The main conclusion of the study is that big data provide better decision-making and greater transparency in the property management industry, ensuring a more efficient experience for both professionals and customers. [ABSTRACT FROM AUTHOR]

The paper presents a novel steganographic algorithm. It is based on a least significant bit method and a chaotic random system. The designed scheme is realized by the Raspberry Pi hardware. It is proved that the novel algorithm shows good statistical results. [ABSTRACT FROM AUTHOR]

The three-dimensional Cauchy problem for the heat conduction equation with a fractional Jeffreys-type constitutive law is studied. Two different cases are distinguished: diffusion and propagation regimes. In the diffusion regime the three-dimensional fundamental solution is shown to be a spatial probability density function evolving in time. In the propagation regime the solution can have negative values, and therefore, does not allow a probabilistic interpretation. Explicit integral representation for the three- dimensional fundamental solution is derived and used for numerical experiments. [ABSTRACT FROM AUTHOR]

In the present paper we study the stability properties of nonlinear perturbed neutral fractional autonomous linear differential systems with distributed delay. It is shown that if the zero solution of the linear part of the nonlinear perturbed system is globally asymptotically stable, then the zero solution of the perturbed nonlinear system is globally asymptotically stable too. The results are based on a formula for the integral presentation of the general solution of a linear autonomous neutral system with distributed delay which was proved by the authors in a previous work. [ABSTRACT FROM AUTHOR]

This paper investigates the stability with respect to manifolds of general type of fractional-order reaction-diffusion neural networks with time-varying delays under impulsive control. First, the impulsive control fractional reaction-diffusion neural- network model is designed and the manifold technique is adapted to it. Then, the Lyapunov function method is applied to derive new stability sufficient conditions. [ABSTRACT FROM AUTHOR]

Bessel functions and their generalizations with more indices are considered in this paper. Studying the properties of these Bessel type functions, some special cases of the fractional order Erdélyi–Kober integrals of them are calculated and interesting relations are proved. It turns out that usually these integrals are expressed in terms of the Bessel type functions with the same or more number of indices, up to a matching power function. [ABSTRACT FROM AUTHOR]

The aim of this work is to analyze the application of fractional derivatives in time for the mathematical modeling of complex processes. As an example, a bioprocess is considered and the related distribution of nutrients, bacteria and bioproduct in multiphase fluid systems. The mathematical model under investigation includes convection, diffusion, bioreaction and boundary conditions at the interfaces: interface mass-transfer and adsorption. Different approaches of time-fractional modeling of a biopro- cess are discussed. To evaluate the ability of a fractional order model to correctly reproduce the behavior that the underlying process must exhibit, numerical procedures are developed and computer simulations are performed. [ABSTRACT FROM AUTHOR]

Linear Riemann-Liouville fractional differential equations with a constant delay and non-instantaneous impulses are studied. Both cases are considered: the case when the lower limit of the fractional derivative is fixed on the whole interval of consideration and the case when the lower limit of the fractional derivative is changed at any point of impulse. The initial conditions as well as impulsive conditions are defined in an appropriate way for both cases. The explicit solutions are obtained and applied to study finite time stability. [ABSTRACT FROM AUTHOR]

The technologically advanced learning implies the adaptation of the recommendation systems to the specific wishes and capabilities of the users. The present document proposes an intelligent system designed for the encompassing education of students with special educational needs. The system integrates the capabilities of intelligent agents, the recommendation systems, and the game based learning in order to provide a personalized learning content. A Bayesian Classifier recommends educational games depending on the interests and the preferences of the users, and a multi-agent system provides individual needs by analyzing users' behavior and by determining the need of acquisition of certain knowledge and skills appropriate for the level of learning. [ABSTRACT FROM AUTHOR]

The current paper examines the ways of integration of the distance and online education into a single mixed system of education as well as the impact of COVID-19 upon the organization of the educational process in both the Bulgarian universities and the national security system. [ABSTRACT FROM AUTHOR]

The paper presents and analyzes teachers' views and attitudes on their participation in continuous professional development (CPD) training courses and their usefulness for the improvement of digital knowledge and skills which are part of teacher digital competence – so much necessary for meeting the educational challenges of the 21st century. The findings discussed in this paper were obtained within a national research project carried out with the support of the Ministry of Education and Science at the end of 2019. The analysis of some of the research findings shows a relatively contradictory picture in terms of the relation between continuous professional development of teachers and the development of teachers' digital competences. On the one hand, a positive tendency is observed related to a very active participation in CPD training of Bulgarian teachers in the field of ICT implementation in the educational context for the past 5 years. On the other hand, the educators themselves give positive but not very high evaluations of the degree to which they have developed basic aspects of their digital competence as a result of the training courses. The way the Bulgarian students evaluate different aspects of their own digital competence developed as a result of the learning experience at school is also not markedly positive. The comparison between the teachers' self-evaluations of their discrete digital competences and the self-evaluations of students regarding their skills for using ICT acquired in the learning process is an adequate research approach through which an authentic idea could be construed about the efficiency of the CPD trainings of educational specialists in the field of digital and technological competence as well as about the existing challenges in this respect in Bulgaria. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has become an accelerator for the shift of many everyday human activities from all sectors of social and economic life from traditional face-to-face to online mode. Education, despite of its conservative nature, was most strongly influenced by this trend. This paper discusses a pedagogical experiment of integrating a system for ongoing assessment of students in a university course, which was transformed from face-to-face to online as a result of the forced transition to distance learning during the pandemic. The goal of this experiment was to motivate the permanent involvement in the learning process of students who have no experience as online learners. The study is aimed at seeking the effectiveness of the applied approach of integrated continuous assessment as a 'soft" transition from face-to-face to distance learning. [ABSTRACT FROM AUTHOR]

The ubiquity of technology in the last decades has transformed education, accelerated the development of e-learning and has placed a lot of challenges to the higher education institutions in terms of students' assessment. These potential challenges of e-assessment slowed down the process of its proliferation to some extent but the COVID-19 pandemic forced the introduction of e-assessment in all educational stages, and in most cases institutions had to "switch, almost overnight, to online teaching and virtual education" [1]. This study aims to identify the impact of students' experience from one of the leading Bulgarian universities – Sofia University (SU) in forced introduction of e-assessment on their views and perspectives about it. The research method is an online survey, conducted at the end of the semester in academic year 2019/2020 and students from all 16 SU faculties were invited to take part. The paper focuses on three main aspects – 1) students experience in e-assessment during pandemic; 2) students' views on e-assessment; and 3) the impact of their experience in e-assessment on their views. Findings from data analysis reveal that students were mostly summative assessed through course works (artefacts) submissions and tests, and the use of different types of formative assessment was very limited. The technologies utilised for the assessments by academic staff were also very deficient. These results demonstrate that most of the teachers transferred their experience and approaches to students' assessment from face-to- face to the online environment without adaptation and modification to specifics of the latter. This decreased to a certain extent the trust of students in e-assessment and reinforced their preference to face-to-face assessment. Conclusions impose the need for advanced training of academic staff in the field of e-learning and e-assessment design. [ABSTRACT FROM AUTHOR]

The widespread expansion of electronic information technologies in education leads to continuous processes of modernization and sometimes a complete change in the content, methods, organization of training, the learning space, and the goals of the educational system. The ever-increasing amount of information needs to be understood, processed, and restructured. Comprehensive educational reform is underway, including a change in human thinking. This paper focuses on enhancing critical thinking of Ph.D. engineering students through ICT use in Academic writing classes. A model has been proposed and elaborated. [ABSTRACT FROM AUTHOR]

Machine learning proposes innovative methods for students' learning analysis and new ways for modeling the learning process and its realization. Learning analytics takes advantage of this fact and processes data according to accepted or emerging algorithms that leads to creation of analytical and predictive models. Learning performance is connected to a set of behavioral activities in educational environment concerning improvement of knowledge and skills. It is a very important criterion for students' progress and for the formation of the final students' outcomes. For achieving better learning performance, the activities should lead to the learning optimization in context of time duration, educational tasks organization, content presentation and management. Activities that support learning are oriented to self-dependent and self-regulated learning as well as socially-oriented and group-driven learning. The aim of the paper is to present an exploration focusing on the influence of self-dependent activities in the form of self- assessment on learning performance. An experiment is conducted with students who have had the possibility to direct and organize their self-assessment activities in the learning management system. Self-assessment activities are not graded and they are not included in the formation of the final course mark. The students' behavior is traced during one semester and machine learning algorithms are utilized to analyze the quality and quantity of the taken self-assessment activities. On this base analytical and predictive models regarding learning performance and the achieved academic results are created. The patterns and anomalies are outlined and they are used to point out the directions for learning performance and final outcomes improvement. [ABSTRACT FROM AUTHOR]

The collaborative approach has been applied for years in a number of distance learning courses, but they are relatively few in foreign language learning. The context of this research is an online distance learning course of French for specific purposes, delivered through the platform UNIV-Rст (Strasbourg University). Based on the online collaborative learning perspective, we have carried out a study analyzing 25 students' opinions in context of a distance learning French language course. By analyzing the students' perceptions of the online collaborative course in which they took part, we have tried to understand the processes that guide the development of a sense of belonging to an online learning community and see to what extent it contributes to reducing the sense of isolation in an online learning environment. [ABSTRACT FROM AUTHOR]

This study examines the student teachers' satisfaction with e-learning science courses "Ecological education" and "Didactics of natural sciences in primary school" in a public university in Bulgaria. Richard R. Aman's satisfaction questionnaire was used to obtain data, regarding quality factors of satisfaction. These factors were integrated in the Quality concept for development of student teachers' satisfaction, based on building of their professional competencies. The results of analysis reveal that professional-competent student teachers feel satisfy with science courses, because they are successful. However, some of students would feel more satisfied, if they could get additional technological help and support. [ABSTRACT FROM AUTHOR]