Programming Problem Research Articles

Використання онтологій для розширення можливостей пошуку та навігації в онлайн-версії "Великої української енциклопедії"

The aim of the work is to analyze the means of semantic search in Wiki resources and to develop directions for expanding its capabilities through the use of modern tools of knowledge management. The article analyzes the benefits that the use of semantic markup of the Web information resources provides for users by more convenient and quick access to content. The techniques of application of ontological analysis for search and navigation in semantized Wiki resources are considered. The definition of Wiki ontology that formalizes the information about the structure of the knowledge base of information resource (both ordinary and semantized) based on Wiki technology is proposed. The theoretical foundations of determining the measure of semantic similarity between domain concepts based on ontologies and taxonomies are analyzed. Methods of design of navigation tools oriented on Wiki resources are proposed. These methods are based on retrieval of pages that use semantically related concepts. The implementation of the proposed approach in the online version of the Great Ukrainian Encyclopedia (e-VUE) is described. Such approach supports an extension of the functionality of the encyclopedic resource by providing means of access to content on a semantic level. The methodological principles of the organization of the e-VUE knowledge base and the categorization of its articles that ensure the use of semantic proximity estimations between domain concepts for discovery of such concepts are substanti­ated. Problems in programming 2019; 4: 11-27

Применение машинного обучения в программной инженерии: обзор

Today, software is one of the main technologies contributing to the development of society. Therefore, its quality is a major requirement for both the global software industry and software engineering, which deals with all aspects of improving the quality and reliability of software products at all stages of their life cycle. To solve software engineering problems, the use of artificial intelligence methods is becoming increasingly relevant. The article presents a brief description of machine learning methods such as artificial neural networks, support vector machine, decision trees, inductive logic programming and others. Also, examples of the application of these methods to solve some problems of forecasting and quality assessment in software engineering are presented, recommendations for applying machine learning algorithms to solving problems of software engineering are given. The review will be useful by researchers and practitioners as a starting point, because it identifies important and promising areas of research. This will ultimately lead to more effective solving of software engineering problems, providing better, more reliable and cost effective software products. Problems in programming 2019; 4: 92-110

Інноваційна педагогічна комп'ютерна технологія оптимізації шкільного колек-тиву в аспекті знань про біосоціальну структуру особистості його членів

The article discusses modern computer technologies to support the functioning of the school collective on the basis of an individual-typological approach to improve the efficiency of training and preserve the biosocial health of its members. From the standpoint of the principles of integrity, consistency, dynamism, rhythmology and interdisciplinary, the sociopsychophysiological dynamic portrait of the collective, its individual adaptation information space (IAIS) – a rational environment for life (design), was considered. The technological scheme offers for consideration fundamentally new service components: the biosocial of the student (knowledge of his adaptation capabilities), monitoring for the constant harmonization of the collective, a personologist – interdisciplinary, more responsible for the psychological climate of the environment. Individually typological approach to understanding the mechanisms of individual (rather than average) human adaptation, the tandem professional competence – biosocial culture together with active computerization can become a breakthrough moment in modern human knowledge and humanity, thereby significantly increasing the level of economic potential and of the country. Problems in programming 2019; 4: 121-131

Программный симулятор механизмов долговременной регуляции гемодинами-ки человека

A computer simulator (CS) of the physiological mechanisms of long-term control of the state of human cardiovascular system (CVS) is developed. The bases of CS are quantitative mathematical models (MM) describing: a) the effects of the central renin-angiotensin system on the characteristics of the CVS; b) the dynamics of the total blood volume. Test studies of MM in offline mode showed the adequacy of the models. It is planned to combine this model with the previously created model simulating the urgent regulation of CVS. Based on the integrated model, specialized software technology will be developed to support computer simulations on various aspects of the physiology of the healthy person’s blood circulation. A special simulation study should identify the causes of different scenarios for the development of hypertension. The program is written in C ++17. Problems in programming 2019; 4: 111-120

Використання тезаурусів для пошуку складних інформаційних об’єктів у Web на основі онтологій

An ontological model of interaction between objects and subjects of the Web semantic search is proposed, its basic elements are characterized, methods for its replenishment and use for filtering information that is pertinent to the personalized needs of users are considered. The types of relations between the instances and classes of this model and their characteristics that can have an influence on the time complexity of processing knowledge presented on the basis of this model, are analyzed. One of the important elements of the proposed model are thesauri that represent knowledge regarding tasks for which users are looking for information, and about information resources where such information can be contained. The expediency of using particular cases of ontology – thesauruses – to find semantically similar information objects is substantiated. The types of thesauruses that are used for semantic search are considered, methods for their replenishment and utilization are proposed, and their characteristics are analyzed. In this paper we proposes an algorithm for the automated construction of simple thesaurus, which is formed on the base of the domain ontology and a natural language description of the user’s problem, and methods for generating composite thesauri that are pertinent to new user tasks which are based on the set of simple thesauruses previously built by user. The expressiveness and computational complexity of the proposed methods which depend on the domain ontology characteristics and on the size of the problem description are estimated. Methods of use of the semantically marked Wiki resources as a source of knowledge for constructing ontologies of subject areas and associated typical information objects are considered. Problems in programming 2019; 4: 28-52

A resource limited parallel program model

Modern parallel programs run in a complex, resource-limited environment, and this raises the new requirements for resource consumption and execution stability of long running processes. In order to help with checking resource constraints for such parallel software a resource-limited parallel program formal model was developed. The model expresses the resource and time constraints and is suitable both for fine grained and coarse-grained parallelism in programs. For higher degrees of parallelism (at independent procedure level, bigger loop iterations, large computing blocks for graphics, video and neural network processing) the interpretation of formal model can be done in run-time and avoid dead locks and hangs during resource allocation. We are discussing several modern software frameworks that are able to integrate the functionality to interpret the model and check the feasibility of the set of parallel programs running on hardware simultaneously with resource and time limitations. Real world tasks – neural network inference, video processing, general purpose computing on GPU – which get benefits after enabling such models - are discussed. Problems in programming 2019; 4: 03-10

Модели оптимизации производства сельскохозяйственной продукции с экспертными оценками своевременности посева

The article proposes a parametric model of optimization of agricultural production using expert estimates characterizing the timeliness of sowing. It is proposed to use estimates obtained by one or a group of experts, which are agronomists, as coefficients of the influence of sowing dates on production parameters. The coefficients for the unknowns in the left-hand parts of the restrictions are described using trends and factor models based on time. One of the variants of the proposed problem of parametric programming was implemented for the CJSC «Irkutsk Seeds» of the Irkutsk District of the Irkutsk Region. The simulation results are given taking into account the expert estimates for two cases: timely and early (or late) sowing.

DYNAMIC PROBLEM OF FORMATION OF SECURITIES PORTFOLIO UNDER UNCERTAINTY CONDITIONS

The analysis of known methods for solving the problem of forming a portfolio of securities in the face of uncertainty is carried out. Traditionally, the problem is solved under the assumption that for each type of asset, the values of the main statistical characteristics of the random value of their profitability (mathematical expectation and variance) are known. At the same time, the variance of portfolio returns, which is minimized, is used as a criterion for portfolio optimization. Two alternative approaches to solving the formulated problem are proposed. The first of them provides a decision on the criterion of the probability that the random total portfolio return will not be lower than the given. It is assumed that the random return for each type of asset is distributed normally and the statistical characteristics of the respective densities are known. The original problem is reduced to the problem of maximizing the quadratic fractional criterion in the presence of linear constraints. To solve this non-standard optimization problem, a special iterative algorithm is proposed that implements the procedure for sequential improvement of the plan. The method converges and the computational procedure for obtaining a solution can be stopped by any of the standard criteria. The second approach considers the possibility of solving the problem under the assumption that the distribution densities of random asset returns are not known, however, based on the results of preliminary statistical processing of the initial data, estimates of the values of the main numerical characteristics for each of the assets are obtained. To solve the problem, a new mathematical apparatus is used – continuous linear programming, which is a generalization of ordinary linear programming to the case when the task variables are continuous. This method, in the considered problem, is based on solving an auxiliary problem: finding the worst-case distribution density of a random total portfolio return at which this total return does not reach an acceptable threshold with maximum probability. Now the main minimax problem is being solved: the formation of the best portfolio in the worst conditions. The resulting computational scheme leads to the problem of quadratic mathematical programming in the presence of linear constraints. Next, a method is proposed for solving the problem of forming a portfolio of securities, taking into account the real dynamics of the value of assets. The problem that arises in this case is formulated and solved in terms of the general theory of control, using the Riccati equation.

Finite-time stability and stabilisation of singular discrete-time linear positive systems with time-varying delay

ABSTRACTIn this paper, the problem of finite-time stability and stabilisation for positive singular discrete-time linear systems with time-varying delay is investigated. We first present novel delay-dependent sufficient conditions for positivity and finite-time stability of the unforced systems. We then apply the obtained results to solve finite-time stabilisation problem of the considered systems. The sufficient conditions for the positivity and finite-time stabilisable of such systems are formulated in terms of a standard linear programming (LP) problem. Numerical examples are provided to illustrate the effectiveness and advantages of our results.

Probabilistic inconsistency correction for misclassification in statistical matching, with an example in health care

ABSTRACTA recently proposed procedure for correcting inconsistent (i.e. incoherent) probability assessments is specifically tailored for the statistical matching problem with misclassification component. Such procedure is based on distance minimization encoded in mixed integer programming (MIP) problems and it results particularly apt to deal with assessments stemming from different sources of information. The statistical matching problem is one of those cases. The statistical matching problem has been recently studied also inside a misclassification setting. To proceed with a correction in such a framework, if marginal assessments on the conditioning event are wanted to remain fixed, the only possible solutions are the closest Fréchet–Hoeffding bounds for the misclassification probabilities. On the contrary, if also the marginal probabilities are allowed to be modified, the -based procedure can be applied by a straightforward translation in an MIP problem. Such procedure is applied to a healthcare expenditures and health conditions data example.

On partial calmness for bilevel programming problems with lower-level problem linear in lower-level variable

Communicated by Corresponding Member Valentine V. Gorokhovik In the paper the Lipschitz-like properties of solution mapping of lower-level problems for bilevel programs are studied and sufficient conditions for partial calmness are proved on the basis of these properties.

Generalized Benders Decomposition to Secure Energy-Efficient Resource Allocation for Multiuser Full-Duplex Relay Cooperative Networks

In this paper, we investigate the issue of resource allocation for secure energy efficient communication in a multiuser orthogonal frequency division multiplexing (OFDM) based full-duplex (FD) relaying network in the presence of a passive eavesdropper whose channel state information (CSI) is not perfectly known. Our goal is to maximize the overall secure energy efficiency (SEE), which presents the relationship between energy consumption and secrecy performance. In the context of multiuser communications, such a resource allocation strategy jointly combines subcarrier permutation, subcarrier pair allocation, as well as power allocation altogether. The considered optimization problem is formulated as a mixed integer nonconvex programming problem, which is generally NP hard. Analyzing the property of such a problem, we first use the Dinkelbach's method to eliminate the fractional form and then exploit Generalized Benders decomposition to decouple the original problem into a master problem for pure integer programming and a primal problem for nonlinear programming. More specific, given the nonconvexity of the primal problem, we accordingly transform it into an equivalent relaxed convex problem by applying dual decomposition, alternative convex search, and difference of convex function programming. The numerical results are provided to validate the theoretical analysis and to demonstrate the effectiveness of the proposed algorithm.

A Robust Optimal Coordinated Droop Control Method for Multiple VSCs in AC–DC Distribution Network

AC–DC hybrid distribution network is viewed as a featured system to efficiently connect to all kinds of power sources and loads. In order to improve the system robustness, adapting to random fluctuations of renewable energy sources, this paper proposed a robust optimal coordinated control method for multiple voltage source converters (VSCs) in AC–DC distribution network. A robust optimization model was established to co-optimize the slopes of active and reactive power droop control of VSCs with the aim to minimize the total network loss, while ensuring the system security. VSC capacity coupling and power flow constraints were both considered. Then, to enhance the computational tractability of the problem, based on the column-and-constraint generation algorithm, ${V^2} - P$ and ${V^2} - Q$ were implemented in the droop control schemes holding the linear feedback characteristic so that the non-convex max–min sub-problem can be transformed into a mixed integer second-order cone (SOC) programming problem. Furthermore, to increase the accuracy of SOC relaxation in the sub-problem, a current limit strategy was designed where the maximum possible network loss was pre-identified to restrain the feasible range of branch current. Numerical experiments suggest that the proposed coordinated control method can improve the system security with little extra economic cost, and the reliability of the results is enhanced by the proposed current limit strategy.

Automated Decision Support System in the Energy- and Resource-Efficiency Management of a Chemical-Energy Engineering System for Roasting Phosphorite Pellets

Mathematical and computer-based models of a complex chemical-engineering roasting process as an interdependent plurality of three processes—drying, calcining, and sintering of moving, tight, and multilayered mass of phosphorite pellets in conveyer roasting machine, differing in attention to the intensity of processes of internal moisture transfer within the pellet and overwetting processes of separate horizons in heated pellet layer, have been developed, making it possible to the determine engineering parameters of the roasting mode. The adequacy of the mathematical model is checked from the comparative analysis data of calculated values of the moisture content and the temperature of pellets and parameters of heat-transfer gas, as well as moisture-transfer intensity in pellets when they are dried in the moving tight layer, were compared with the data of industrial testing. Numerous calculated experiments to determine the relative extent of drying, the moisture content, the intensity of pellet drying, and the moisture content of heat-transfer gas are carried out, in which crude pellets and the engineering data of the operating mode of a roasting machine have different parameters. An informal and mathematical statement of the problem of optimizing the chemical-energy engineering process (CEEP) for roasting the moving tight multilayered mass of phosphorite pellets within the complex chemical-energy engineering system (CEES) of the conveyer roasting machine is developed as the problem of discrete dynamic programming in light of spatiotemporal multistage processes for roasting the moving multilayered pellet mass, the intensity of the internal moisture transfer processes within the pellet, processes of overwetting the separate layers of pellets, and variables of the control stream of the heat-transfer gas; this makes it possible to enhance energy efficiency by means of intensifying heat-and-mass transfer processes of multilayered drying, calcining, and sintering. The performance criterion is the minimum cost of electrical and heat energy expended on the CEEP for roasting. The results were used to calculate energy efficient pellet roasting in CEES of the conveyer roasting machine. It has been found that, under the optimum mode of multilayered pellet roasting, there is no overwetting zone, processes of heat and moisture transfer are intensified, energy consumption decreases, and the quality of the end product increases. The problem of pellet overwetting in separate layer horizons of the drying zone of the roasting machine has been studied. The actual theoretical and practical problem of energy and resource saving in roasting pelletized crude ore in the tight layer has been solved. The mathematical model of heat-mass exchange in the pellet layer and testing its adequacy have been presented. The problem of optimizing power inputs based on the intensification of roasting processes has been solved.

Economic and Environmental Optimisation Framework for Carbon Capture Utilisation and Storage Supply Chain

Carbon capture utilisation and storage (CCUS) is widely recognised as a key mitigation technology that can significantly reduce carbon dioxide (CO2) emission. This study develops an optimisation framework focused on the economic and environmental aspects of Northeast China CCUS supply chain. The overall network is economically optimised over a 20 years’ time horizon to provide the geographic location and scale of capture and sequestration sites as well as the most convenient transport routes. The resulting problem is a multi-objective mixed integer linear programming (MILP) problem, whose objectives include minimising its total annual cost and minimising life cycle greenhouse gas (GHG) emission. The economic and environmental performances are optimised by e-constraint method. To demonstrate the application of the proposed model, a realistic case study from Northeast China involving 16 sources and 3 sinks is illustrated. The results provide valuable insights to adopt more sustainable strategic alternatives in the design of CCUS supply chain.

Comparison of various solution techniques in dispatching coupled electricity‐heat system with independent thermal energy storage

Notable benefit can be brought by combined operation of coupled electricity-heat system (CEHS) and be enhanced by introducing independent thermal energy storage (ITES). With prevalent constant-flow variable temperature (CF-VT) control strategy of heat network, explicitly formulating CEHS with ITES leads to mixed-integer non-convex programming. Although the problem can be reformulated as a mixed integer second-order cone programming (MISOCP) problem and solved by commercial solvers, improving the computation efficiency still needs more effort. Here, several alternative solution techniques, based on either reformulation or approximation methods, are studied and compared with the original MISOCP formulation. The computation efficiencies as well as on the solution accuracies of various solution techniques or a combination of them are investigated and analysed based on two constructed systems. Simulation results reveal that appropriately selecting formulations of electric and heat networks can effectively improve the performance of solving the original problem.

Day-ahead Resource Scheduling in Distribution Networks with Presence of Electric Vehicles and Distributed Generation Units

In this paper a new framework for scheduling of available resources in the distribution networks is developed. In this respect attempts are focused on interactions between charging/discharging profiles of electric vehicles (EVs) and output power of distributed generation units. To reach this goal, the proposed framework is designed as a two-stage optimization procedure. In the first stage, the charging/discharging schedules of EVs are extracted running a linear programing optimization problem taking into account the EV users' constraints and requirements. The usage profiles of the DG units, strategy of buying electricity from the market and also the final charging/discharging patterns of the EVs are set running the second stage of this scheduling framework. The attained mixed-integer non-linear programing optimization problem is linearized and a procedure is organized to check the technical aspect of network. The results show that the proposed energy resource scheduling method satisfies financial and technical goals of network.

Interference-Aware Subcarrier Allocation for Massive Machine-Type Communication in 5G-Enabled Internet of Things.

Massive machine-type communication (mMTC) is investigated as one of three typical scenes of the 5th-generation (5G) network. In this paper, we propose a 5G-enabled internet of things (IoT) in which some enhanced mobile broadband devices transmit video stream to a centralized controller and some mMTC devices exchange short packet data with adjacent devices via D2D communication to promote inter-device cooperation. Since massive MTC devices have data transmission requirements in 5G-enabled IoT with limited spectrum resources, the subcarrier allocation problem is investigated to maximize the connectivity of mMTC devices subject to the quality of service (QoS) requirement of enhanced Mobile Broadband (eMBB) devices and mMTC devices. To solve the formulated mixed-integer non-linear programming (MINLP) problem, which is NP-hard, an interference-aware subcarrier allocation algorithm for mMTC communication (IASA) is developed to maximize the number of active mMTC devices. Finally, the performance of the proposed algorithm is evaluated by simulation. Numerical results demonstrate that the proposed algorithm outperforms the three traditional benchmark methods, which significantly improves the utilization of the uplink spectrum. This indicates that the proposed IASA algorithm provides a better solution for IoT application.

Development and Implementation Problems of scientific and Technological Progress strategic Programs in the Russian Federation Regions: social and Organizational Barriers Part 2

If the general purpose of all work is to study problems of development and implementation of strategic programs of STD in regions of the Russian Federation with different level of modernization, at the first stage the question of organization of work in regions with external, infocommunicative side was raised, and at the second stage from subjective position, on the basis of assessment of the situation from the social and organizational side. Hence the similarities and differences in methodology, methods and outcomes at each stage. Each of them is of interest in assessing the work in this direction, but the comparison of the data obtained is of particular importance. If the first phase involved work to inform the public and potential participants about the forthcoming work on the STD and, Accordingly, on the readiness of the authorities and management to implement it on the materials of remote analysis of official sites of the regions, The second phase focused on finding out: How it is perceived by specialists in terms of creating a favourable social and organizational environment in the regions for the implementation of the adopted strategies.Purpose: obtaining an assessment of the readiness of regional authorities to create favorable social and organizational conditions for successful activities according to certain criteria and elements of innovative and technological systems.Methods: the methodology of the study takes into account the logic and content of the elements of the first stage of the program, but it is markedly different from them. General is the setting of the problem, the presence of related elements of the program (problem, object, subject, hypotheses, goal and tasks, nevertheless there is a difference in methods and procedures), in terms of using empirical scales and interpreting the results. However, if at the first stage the main method was remote (in this sense anonymous) scanning and analysis of data from official sites of authorities and administrations in the selected regions according to the criterion of the level of their sociocultural modernization, at the second stage the main method was personal remote interviews of qualified specialists about the real situation and potential to solve the outstanding issues in the social and organizational plan.Results: the tasks set by the Decrees will be difficult to solve positively without the organization of systematic sociological support for the implementation of the innovation policy of the SSTD of the Russian Federation in the regions as a link of feedback and corresponding organizational outputs on the materials of such studies.Conclusions and Relevance: at the first stage we concluded that the implementation of the Strategic Documents on the Implementation of Innovation Policy of the SSTD of the Russian Federation requires taking into account the state of affairs in regions with different levels of sociocultural modernization and proved this situation on the materials of remote analysis of official sites of their management and the allocation of various barriers as a subject of research and practice. At the second stage, we have shown that the problem is not only the differences between regions and barriers, but also the ability of authorities and administrations to adequately assess their contribution to the process of modernization of the country, and to overcome barriers by creating a favorable social and organizational environment. Today in the surveyed regions the orientation not on the case, as experts note, but on "good reporting".

Global method for learning an integrated temperature prediction model in a slab reheating furnace

Temperature prediction in a slab heating furnace is an important problem for steel production processes. However, the problem is complicated owing to process complexity and industrial noise. These factors make it difficult to obtain precise prediction results by a mechanism model in practical production. In this article, an integrated modelling approach is proposed through combining mechanism and data-driven models. This method constructs a generalized-kernel support vector regression (SVR) on new search space to improve the predictive performance of a mechanism model, in which the kernel matrix is a combination of multiple single kernels. The learning problem can be solved globally by a semi-definite programming (SDP) problem. Numerical experiments using actual data from an iron and steel enterprise in China are performed to illustrate the effectiveness of the proposed integrated method.