bluuebunny/crossref_metadata_2025 huggingface dataset:
HARDWARE MODELS FOR AUTOMATED PARTITIONING AND MAPPING IN MULTI-CORE SYSTEMS USING MATHEMATICAL ALGORITHMS
Authors: Krawczyk Lukas , Kamsties Erik
Published: February 2021

Multi-core CPUs offer several major benefits in embedded systems. For instance, they usually provide higher energy efficiency and more computing power compared to single-core CPUs. However, these benefits do not come for free: A program has to be divided into tasks, which can be executed in parallel on different cores. Partitioning of software and mapping on cores are nontrivial activities that require detailed knowledge about the underlying hardware platform, e.g., the number of cores, their speed, available memories, etc. Such information is typically stored in handbooks. If this information would be available in a machine readable model, we call it hardware model, the partitioning and mapping activities can be automated. In this paper, we propose a hardware model and illustrate it using an example of a Freescale multi-core CPU. We then discuss a small case study situated in the automotive domain, which illustrates the use of the hardware model in partitioning, mapping, and code generation.
AGENT-BASED MODELING OF THE E-LEARNING USERS’ BEHAVIOR
Authors: Artemenko Viktor
Published: February 2021

In this paper the methodological and technical approaches are considered to construct the agent-based model (ABM) with built-in artificial neural networks. This model describes the user’s behavior of electronic or distance learning in a virtual environment of one of universities. Design of ABM aims to support a development of Web analytics (learning analytics) on the basis of computer experiments evaluating the trends of the knowledge creation and dissemination for e-Learning users. In research AnyLogic software, which is one of the most popular packages for agent-based modeling, is proposed for implementing the created model, and package STATISTICA Neural Networks is proposed for constructing the neural networks.
THE METHODS OF SELECTION OF THE PROJECT MANAGEMENT METHODOLOGY
Authors: Kononenko Igor , Kharazii Anna
Published: February 2021

The problem of selecting the methodology to manage the company’s projects or a specific project is reviewed. The authors suggest the methods to select methodology that are designated for application under different conditions of awareness of a decision-maker about the existing methodologies, their advantages and weaknesses and about the range of efficient use. As the methods are more precise, they require a more laborious analysis of the project and its environment. It is proposed to make the most substantiated choice resulting from solution of the task on optimizing the project’s scope to the following criteria: profit, time, cost, quality, risk, and a company’s maturity growth.
THE EFFECT OF USING HAMMING WINDOW AND LINEAR PREDICTIVE CODING MODEL IN EEG-P300 SIGNALS CLASSIFICATION
Authors: Momennezhad Ali , Shamsi Mousa , Ebrahimnezhad Hossein , Asgharian Lida
Published: February 2021

In this paper, Fisher linear discriminant analysis (FLDA) is used to classify the EEGP-300 signals which are extracted from brain activities. In this case, at first the preprocessing algorithms such as filtering and referencing are applied to the raw EEG signal. Then, in order to create a model out of the signal, a linear predictive coding model with 6 order is used. So that the signal is reconstructed by extracting linear predictive coding (LPC) model parameters of each single trial, and then every signal trial is passed through the Hamming window by length 9. At last Fisher Linear Discriminant Analysis is used for classifying. In this paper, classification accuracy, the maximum bit rate and the convergence time to achieve stability in maximum accuracy of classification are computed to compare performance of the proposed method, Fisher Linear Discriminant Analysis with Linear Predictive Coding Model and Hamming Window (LPC+HAMMING+FLDA), to FLDA and LPC+FLDA. The implementation results show that the efficiency of the proposed method in terms of classification accuracy and convergence time to achieve stability in maximum accuracy is better than the other two mentioned algorithms. As example, at the proposed algorithm with 8 electrode configuration the S2 converges to the maximum accuracy after eleventh Block while this happens for two other algorithms after fourteenth Block and the total classification accuracy for this person at proposed algorithm is improved as 2.2% and 4% than respectively LPC+FLDA and FLDA algorithms.
A ROBUST BINARIZATION AND TEXT LINE DETECTION IN HISTORICAL HANDWRITTEN DOCUMENTS ANALYSIS
Authors: Pach Jakub Leszek , Bilski Piotr
Published: February 2021

In this paper, we present a novel method of detecting text lines in handwritten documents based on the Block-Based Hough Transform. To maximize its efficiency, the robust binarization algorithm was applied. It is based on the Gaussian filtering and tackles the non-uniform luminance. The proposed technique consists of three steps: preprocessing, detecting of potential text lines and eliminating the false ones. The first step covers the image binarization, extraction of connected components and selection of supporting connected components based on the local maxima in the vertical histogram stripes. Secondly, the appropriate subset of connected components supplemented by one-point components is selected. Finally, the block-based Hough transform is applied to detect potential text lines and found the ones identified incorrectly. The proposed method is applied to the analysis of the fifteenth century Latin manuscripts. Our approach is more effective than the traditional ones, in the best cases by twenty percent.
PROCESS MODELING OF MESSAGE DISTRIBUTION IN SOCIAL NETWORKS BASED ON SOCIO-COMMUNICATIVE SOLITONS
Authors: Bomba Andrii , Kunanets Nataliia , Pasichnyk Volodymyr , Turbal Yuriy
Published: February 2021

The article proposes a new class of models for distributing messages in social networks based on socio- communicative solitons. This class of models allows to take into account the specific mechanisms for transmitting messages in the chains of the network graph, in which each of the vertices are individuals who, receiving a message, initially form their attitude towards it, and then decide on the further transmission of this message, provided that the corresponding potential of the interaction of two individuals exceeds a certain threshold level. The authors developed the original algorithm for calculating the time moments of message distribution in the corresponding chain, which comes to the solution of a series of Cauchy problems for systems of ordinary nonlinear differential equations. A special continualization procedure is formulated, which makes it possible to simplify substantially the resulting system of equations and replace a part of the equations by the Boussinesq or Korteweg-de Vries equations. The presence of soliton solutions to the above-mentioned equations provides grounds for considering socio-communicative solitons as an effective tool for modeling the processes of distributing messages in social networks and investigating the diverse influences on their dissemination processes.
APPROACH TO THE SYNTHESIS OF NEURAL NETWORK STRUCTURE DURING CLASSIFICATION
Authors: Marakhimov Avazjon R. , Khudaybergenov Kabul K.
Published: February 2021

Evaluating the number of hidden neurons necessary for solving of pattern recognition and classification tasks is one of the key problems in artificial neural networks. Multilayer perceptron is the most useful artificial neural network to estimate the functional structure in classification. In this paper, we show that artificial neural network with a two hidden layer feed forward neural network with d inputs, d neurons in the first hidden layer, 2d+2 neurons in the second hidden layer, k outputs and with a sigmoidal infinitely differentiable function can solve classification and pattern problems with arbitrary accuracy. This result can be applied to design pattern recognition and classification models with optimal structure in the number of hidden neurons and hidden layers. The experimental results over well-known benchmark datasets show that the convergence and the accuracy of the proposed model of artificial neural network are acceptable. Findings in this paper are experimentally analyzed on four different datasets from machine learning repository.
PROGRAMMING STYLE ON SOURCE CODE PLAGIARISM AND COLLUSION DETECTION
Authors: Karnalim Oscar , Kurniawati Gisela
Published: February 2021

This paper utilises programming style on a source code plagiarism and collusion detection to both capture obvious attempts of such academic dishonesty (which characteristics are ignored on most detection techniques) and prioritise non-coincidental similarity to the coincidental one (as only the former can raise suspicion). The technique relies on pairwise programming style similarity to deal with the former and dishonesty probability (how significant is the programming style change between the author’s current submission and previous submissions) to deal with the latter. According to our evaluation, programming style similarity can increase precision since when a code is copied, the programming style can be unconsciously shared (especially for novice students). Dishonesty probability increases not only precision but also recall, f-score, and the resulted similarity degree of suspected pairs; the copied code commonly has different programming style in comparison with the student’s usual style (captured from previous submissions). Our detection technique is comparable to a common technique in academia except that it takes longer processing time as more hints are generated and considered.
COST EFFECTIVE ENERGY EFFICIENT SCHEME FOR MOBILE ADHOC NETWORK
Authors: Radhakrishnan Rathish , Karuppusamy Karpagavadivu
Published: February 2021

Clustering is defined as grouping of nodes based on their energy levels. In each cluster, a gateway node is set depending on the node that has the highest energy level. This phenomenon is majorly implemented using LEACH protocol. LEACH is abbreviated as Low Energy Adaptive Clustering Hierarchy. It is a time division-based Media Access Control (MAC) protocol. In order to make it energy efficient a new protocol is defined to hold the sensors as long as possible. It balances the network load in minimal time. A more energy efficient node transfer is possible by means of the above protocol which attains the high residual energy. The major advantage of implementing this protocol is to reduce the energy and power consumption that is needed to create and maintain the cluster. In Mobile Ad-hoc Network (MANET), the vast consumption of power can be literally minimized by utilizing this clustering scheme. The simulation of our protocol is carried out in Network Simulator-2.
BOTNET DETECTION APPROACH BASED ON THE DISTRIBUTED SYSTEMS
Authors: Savenko Oleg , Sachenko Anatoliy , Lysenko Sergii , Markowsky George , Vasylkiv Nadiia
Published: February 2021

The paper presents a botnet detection approach for the distributed systems. It is based on the developed three level model, which includes botnet’s components: command and control center, control centers, basic elements of the botnet (bots). The novel framework provides the ability to detect known and unknown botnets, and consists of the host and the network levels. At the host level, the detection procedure is based on the implementation of the Bayes classification. The network level extends the results obtained at the host level to the rest of the local area network. Proposed approach provides the exchange of the results obtained by the Bayes classification for further use by other program units of the distributed system. The results of the developed classifier show that representation of the botnets’ samples for different classes and subclasses is sufficient for efficient botnet detection. Proposed technique demonstrates promising results concerning botnet detection in the distributed systems.
USING THE TECHNICAL EXPERIMENT IN THE COMPUTER SIMULATION TRAINING FOR PROSPECTING SOFTWARE ENGINEERS
Authors: Litvinova Maryna , Dudchenko Oleg , Shtanko Oleksandr , Karpova Svitlana
Published: February 2021

In present work, a new technology of the prospective software engineers training in computer simulation is described. The technology provides carrying out comparative analysis of opportunities, productivity, and the accuracy of the reproduction of different computer simulation packages (CSP) on the basis of direct performance of the technical experiment results. Training process includes the principal stages: carrying out of the independent technical experiment; its simulation using of various CSP; comparison of the result of the tested CSP to the results of the experiment; models of debugging; detection of advantages and shortcomings of each involved CSP. As an example, in Open Modelica and Mathcad packages analysis of simulation opportunities of a problem of the motion of the body thrown at an angle to the horizon is carried out. As a result, assessment of the efficiency of each CSP used for the solution of an objective is made. When training prospective software developers the offered technology is the basis for further development of the modern standard in the field of computer simulation.
EDITORIAL “COMPUTATIONAL ASPECTS OF CRITICAL INFRASTRUCTURES SECURITY”, “SECURITY AND POST-QUANTUM CRYPTOGRAPHY”
Authors: Kuznetsov Alexandr , Kalashnikov Vyacheslav , Brumnik Robert , Kavun Sergii
Published: February 2021

In the recent years, a large amount of literature on the computational aspects of critical infrastructures security has emerged, much of it focusing on cryptography, cyber, informational and economical security, theory, methods, approaches and algorithms associated with certain classes of such problems. The topic proposed to treat in this special issue goes one jump further in attempting to deal with computational aspects of critical infrastructures security. Such classes of critical infrastructures security problems often arise in engineering, computing and software applications: robotics, Internet of things, different environments control problems, approaches and techniques applied to all types of information and communication technologies, and so forth. Last but not least, a lot of new applied problems in the area of computational aspects of critical infrastructures security have recently arisen that can be efficiently solved only by the new scientific methods, approaches and algorithms. Among them there are informational and economical security problem, designing of encryption algorithms with consideration known attacks analysis problems, symmetric ciphers problems, highly practical and commercial importance of security, safety and protection Reasearch and Development, and so forth, even if we mention only part of such applications or approaches. Computational aspects of critical infrastructures security models to describe informational and economical processes are also the most popular new themes in the area of critical infrastructures security. The primary purpose of the special issue is to discuss these problems with the researchers working in this and in adjacent areas, scientific and practical problems of information and economic security of different countries.
DATA ERRORS CONTROL IN THE MODULAR NUMBER SYSTEM BASED ON THE NULLIFICATION PROCEDURE
Authors: Krasnobayev Victor , Koshman Sergey , Moroz Sergey , Kalashnikov Vyacheslav , Kalashnikov Vitaliy
Published: February 2021

A method for error control in the modular number system (MNS) based on the use of the zeroing procedure is proposed. Error control in the MNS is a non-positional operation and requires the development of special methods, designed to increase the efficiency of this procedure. This method is designed to verify the correct implementation of the computing process of computer systems and components. It is assumed that the error in one module remainder does not affect the residual values corresponding to other modules (bases) of the MNS. The essence of the method of error control is to use the procedure of pair number zeroing with the preliminary fetching of digits. This makes it possible to increase the efficiency of information control, presented in the modular number system. The practical significance of the results obtained is that, in comparison with the existing methods of error control in MNS, the error detection time is more than halved.
OPTIMIZATION OF LIFETIME IN WIRELESS MONITORING NETWORKS
Authors: Kovalova Yuliia , Babenko Tetyana , Oksiiuk Oleksandr , Myrutenko Larysa
Published: February 2021

Wireless network finds application in communal facilities monitoring and management systems. One of the basic requirements for the construction of a wireless monitoring network with autonomous power supply is the guaranteed network lifetime. Up-to-date challenges in the field of wireless monitoring networks are creation of universal hardware platforms that allow for usage of widespread proprietary transceivers of different manufacturers aiming at creating network topologies raising energy efficiency and lifetime of WMN. The article describes a model of a wireless network allowing evaluation of its lifetime by energy parameters and dynamic reconfigurations induced by external influence. On the basis of the represented test results one may conclude that energy consumption is defined by the level of the application stack of the protocol ZigBeе and doesn’t depend on PHY and MAC layers of the protocol 802.15.4. Considering energy consumption of the data transmission process, potential increase in the lifetime of the devices and network as a whole is mostly controlled by the sizes of useful messages.
A GUI TESTING STRATEGY AND TOOL FOR ANDROID APPS
Authors: Girgis Moheb R. , Abdel Latef Bahgat A. , Akl Tahany
Published: February 2021

The increasing popularity of Android and the GUI-driven nature of its apps have motivated the need for applicable automated GUI testing techniques. This paper presents a proposed strategy and a supporting tool for GUI testing of Android apps. The strategy employs a model-based approach to capture the event-driven nature of Android apps. It includes two phases: Modeling Phase and Test Evaluation Phase. In the modeling phase, an event sequence diagram (ESD) is created for each activity in the app under test (AUT), which depicts its events and possible transitions between them, and used to generate event sequences (test cases). In the test evaluation phase, certain event-based coverage criteria are employed to measure the adequacy of the generated test cases. The proposed tool analyses the AUT, creates an ESD for each activity, and generates event sequences. It handles the event sequences explosion problem and ensures the event sequences feasibility. For each event sequence, the tool generates a test script and a corresponding Robotium test class, adds it to the AUT and executes it. The paper also presents a case study that illustrates the use of the proposed strategy and tool for testing a simple Android app.
THE USE OF A GENETIC ALGORITHM FOR MUSIC HARMONIZATION OF TRANSITIONAL FRAGMENTS IN COMPUTER GAMES
Authors: Komarov Oleksandr , Galchonkov Oleg , Nevrev Alexander , Babilunga Oksana
Published: February 2021

The problem of musical accompaniment harmonization for adjacent transitional fragments in computer games is considered. A harmonization method based on a tonal model of the musical composition in conjunction with a genetic algorithm seeking the global extremum of the harmonic function is proposed. For the method under consideration, all operators of the genetic algorithm and fitness functions are defined. A scheme was developed for the formation of transitional musical compositions and a flowchart was proposed for using the genetic algorithm in its implementation. Using examples of well-known musical compositions, a study was conducted of the genetic algorithm features and its most appropriate parameters were found in the context of the problem under consideration. This allowed us to obtain expression for the computational costs of the proposed method, which are necessary for balancing the computational load in the computer between the game algorithm itself and the musical harmonization algorithm. Moreover, the study showed that using genetic algorithm allows even for a small number of iterations to achieve melody harmonization level no worse than professional composer achieved, and even exceed this level when performing extra iterations.
AUDIO SIGNALS CLIPPING DETECTION USING KURTOSIS AND ITS TRANSFORMS
Authors: Prodeus Arkadiy , Didkovska Maryna
Published: February 2021

This paper compares the results of subjective and objective assessments of the quality of speech and music signals distorted during clipping when large instantaneous signal values are replaced by a certain threshold constant or by values close to it. It was proposed in recent works to use kurtosis and some of its simple functional transforms such as reciprocal of kurtosis and square root of reciprocal of kurtosis as objective (instrumental) clipping value measures. This paper clarifies the results of a subjective assessment of the quality of speech and music signals distorted by clipping. A comparison of the obtained estimates allows one to conclude that the human auditory system is slightly more sensitive to the clipping of musical signals than to the clipping of speech signals, but this difference is small. Similarly, objective quality measures of clipped signals are almost equally sensitive to the clipping value of speech and music signals. An analysis of the variability of the kurtosis estimates, depending on the time of estimation, showed that the relative standard deviation of the kurtosis estimates is close to 10% for the analysis time interval of 1–40 s.
A GENETIC ALGORITHM-BASED APPROACH FOR THREE-PHASE FAULT EVALUATION IN A DISTRIBUTION NETWORK
Authors: Shambare Chikomborero , Sun Yanxia , Imoru OdunAyo
Published: February 2021

Standard IEC 60909 provides all the basic information that is used in the evaluation of three-phase short circuit faults. However, it uses numerous estimations in its fault evaluation procedures. It estimates voltage factors, resistance to reactance ratios (R/X), resistance to impedance ratios (R/Z) and other scaling factors. These estimates do not cater for every nominal voltage. Users often have to approximate these values. In this paper, adjustments were made to the genetic algorithm (GA) with regards to gene replacements and arrangement of scores and expectation. During fault computation, the GA was used to stochastically determine R/X and R/Z ratios with regards to the parameters of the power system. The GA was tested on a nominal voltage that is properly catered for by Standard IEC. The GA results and the IEC values were within an approximate range. This implies that the developed GA can be further used to determine these ratios for nominal voltages that are not sufficiently accounted for by Standard IEC. This leads to obtaining precise fault values in all instances.
DEVELOPMENT OF AN EVOLUTIONARY OPTIMIZATION METHOD FOR FINANCIAL INDICATORS OF PHARMACIES
Authors: Oliinyk Аndrii , Fedorchenko Ievgen , Donenko Vasyl , Stepanenko Аlexandеr , Korniienko Serhii , Kharchenko Anastasia
Published: February 2021

The work is devoted to the problem of optimizing the financial performance of pharmacies. To solve this problem, a genetic method of multicriteria optimization was developed with a mutation operator modification to study the degree of influence of factors on the financial performance of pharmacies and the choice of optimization model. The fundamental difference between the developed genetic algorithm and its existing counterparts is the ability to control the mathematical distribution of the values of the solution, which prevents premature convergence of the genetic algorithm and uses all proposed genes in fractions according to the chosen distribution model. A comparative analysis of the work of classical GA and modified versions shows that the best results are achieved in the cognitive-style determination. Three modifications of the mutation operator were developed. The application of the developed methods will lead to a more effective use of the pharmacy area, to reduce unmet demand and, ultimately, to reduce the retail cost of drugs by reducing the costs of storing and servicing the suboptimal loading of the pharmacy.
HETEROGENEOUS COMPUTING TO ACCELERATE THE SEARCH OF SUPER K-MERS BASED ON MINIMIZERS
Authors: Vera-Parra Nelson Enrique , López-Sarmiento Danilo Alfonso , Rojas-Quintero Cristian Alejandro
Published: February 2021

The k-mers processing techniques based on partitioning of the data set on the disk using minimizer-type seeds have led to a significant reduction in memory requirements; however, it has added processes (search and distribution of super k-mers) that can be intensive given the large volume of data. This paper presents a massive parallel processing model in order to enable the efficient use of heterogeneous computation to accelerate the search of super k-mers based on seeds (minimizers or signatures). The model includes three main contributions: a new data structure called CISK for representing the super k-mers, their minimizers and two massive parallelization patterns in an indexed and compact way: one for obtaining the canonical m-mers of a set of reads and another for  searching for super k-mers based on minimizers. The model was implemented through two OpenCL kernels. The evaluation of the kernels shows favorable results in terms of execution times and memory requirements to use the model for constructing heterogeneous solutions with simultaneous execution (workload distribution), which perform co-processing using the current search methods of super k -mers on the CPU and the methods presented herein on GPU. The model implementation code is available in the repository: https://github.com/BioinfUD/K-mersCL.
SEMANTIC GRAPH BASED TERM EXPANSION FOR SENTENCE-LEVEL SENTIMENT ANALYSIS
Authors: Maree Mohammed , Eleyat Mujahed
Published: February 2021

The semantic orientation (also referred to as prior polarity) of a word plays an important role in automatic sentence-level sentiment analysis. Several approaches have been proposed wherein a lexicon of words marked with their polarities is exploited to infer the meaning of sentences. However, relying on prior word polarity may produce inaccurate decisions. This is because we may find negative-sentence sentiments that include words with positive prior polarities or vice versa. In this article, we propose an approach to sentence-level sentiment analysis that exploits knowledge encoded in heavy-weight semantic graphs to assist in discovering the meaning of a word in the context of the sentence where it appears. In this context, we build contextual semantic networks for indexing sentences and expand them with semantically/lexically-relevant terms in an attempt to disambiguate the meanings of word mentions in sentences. In order to verify the effectiveness of the proposed approach, we have developed a prototype system using a real-world dataset that contains 46830 sentiment sentences along with a gold-standard that comprises 10000 movie reviews that are labelled under five sentiment categories (very negative, negative, neutral, positive, very positive). Findings indicate that enriching the semantic graphs of sentiment sentences with NOUN-based synonyms and hypernyms has improved the overall quality of baseline sentiment analysis techniques.
GROUP VELOCITY AND DISPERSION COEFFICIENT IN THE DISTRIBUTED SENSOR OF VIBRATION IN FIBRE OPTIC MICHELSON’S INTERFEROMETER CONFIGURATION
Authors: Kizlik Bogdan , Nichoga Vitalij , Dub Petro
Published: February 2021

The problem of determination of group velocity and dispersion coefficient in the distributed sensor of vibration in fibre optic Michelson’s interferometer configuration is considered in the report. Influence of acoustic wave on optical wave in a Bragg modulator is described. It is shown that such interferometer can be used as a distributed highly sensitive sensor of mechanical values (vibration, acoustic wave, pressure, displacement).
INTERVAL PARAMETER’S IDENTIFICATION OF THE LINEAR DYNAMIC SYSTEM ON THE BASIS OF INTERVAL DATA
Authors: Dyvak Mykola , Stakchiv Petro , Kalishchuk Iryna
Published: February 2021

The task of interval parameter’s identification of linear dynamic system is considered. Possibility of application of calculation procedures of parameter’s interval identification of the static system for the decision of this task is shown. The method of parameter’s set identification of the linear dynamic system in form of multidimensional ellipsoids is proposed.
SYNTHESIS OF SELF-ORGANIZING MAP AND FEEDFORWARD NEURAL NETWORK FOR BETTER FORECASTING
Authors: Hodych Oles , Shcherbyna Yuriy , Zylan Michael
Published: February 2021

In this article the authors propose an approach to forecasting the direction of the share price fluctuation, which is based on utilization of the Feedforward Neural Network in conjunction with Self-Organizing Map. It is proposed to use the Self-Organizing Map for filtration of the share price data set, whereas the Feedforward Neural Network is used to forecast the direction of the share price fluctuation based on the filtered data set. The comparison results are presented for filtered and non-filtered share price data sets.
MULTI-CHANNEL MAGNETOCARDIOGRAPH: CONTROL AND SOFTWARE
Authors: Voytovych Igor , Primin Myhailo , Vasyliev Valery , Sutkovyy Pavlo , Budnyk Mykola , Nedayvoda Igor , Rusanov Anatoly , Ryzhenko Tetyana
Published: February 2021

Purpose of the work was to present algorithms and software developed for working with multi-channel magneto-cardiograph. Such software is intended for control of operation and computer processing of magnetocardiographic (MCG) data obtained from the human heart. Magnetocardiograph is controlled as “virtual device” from PC mouse/keyboard, so as manually from electronic unit and all that through the control microprocessors embedded into hardware units. Software processing is performed both in on-line mode during process of data acquisition and in off-line manner during post-processing. Software allows preliminary processing, reconstruction and analysis of magnetic maps, and also inverse problem solution. Package is intended both for scientific studying of the heart electric activity and studying of MCG informative indexes for clinical diagnostic of cardiology diseases. Above software is planned to use at Strazhesko Institute of Cardiology (Kyiv) within framework of project supported by Science and Technology Center in Ukraine (STCU).
EFFICIENCY ANALYSIS OF PARALLEL ROUTINE USING PROCESSOR TIME VISUALIZATION
Authors: Turchenko Volodymyr , Demchuk Viktor
Published: February 2021

The coarse-grain parallel algorithm of modular neural networks training with dynamic mapping onto processors of parallel computer is described in this paper. Parallelization of the algorithm is done on parallel computer 300 using MPI technology. The efficiency of this algorithm is estimated using modification of MPE visualization library, which measures processor executing time of parallel routines.
FAST DETECTION OF MASSES IN MAMMOGRAMS WITH DIFFICULT CASE EXCLUSION
Authors: Takacs Gabor , Pataki Bela
Published: February 2021

Breast cancer is one of the most common forms of cancer among women. Currently mammography is the most efficient method for early detection. A simple and fast mammographic mass detection system and two different methods for difficult case exclusion are presented in this paper. The mass detection system uses a modified version of a known algorithm for small masses and a new algorithm for large masses. The first difficult case filtering method is based on tissue density estimation, the second one on mass candidate count. The system was tested with 600 mammographic cases, each containing 4 images. Case-level performance was measured for malignant mass detection first without and then with difficult case exclusion.
ISLAND MIGRATION MODEL WITH PARALLEL MUTATION STRATEGIES FOR COMPUTING THE TRAVELING SALESMAN PROBLEM ON MULTICOMPUTER PLATFORM
Authors: Borovska Plamenka I. , Bahudaila Subhi A. , Lazarova Milena K.
Published: February 2021

This paper investigates the efficiency of a model of parallel genetic computation of the traveling salesman problem with circular periodic chromosomes migration. The parallel model is verified by MPI-based program implementation on a multicomputer platform. The correlation of the application and architectural spaces has been investigated by exploring the impact of the scalability of the application and the parallel machine size over the efficiency of the parallel system. Performance profiling, evaluation and analysis have been made for different numbers of cities and different sizes of the multicomputer platform. The paper also investigates the impact of the mutation strategy on the solution quality of coarse-grained parallel genetic algorithm with circular periodic migration for the traveling salesman problem. We propose an approach to improve the quality of solution by applying parallel variable mutation rates for the local evolutions in the concurrent processes. A series of experiments has been carried out with parallel fixed and variable mutation rates in order to estimate the efficiency of the suggested approach. The best quality solutions have been obtained for the strategy with parallel fixed mutation rates.
NANOTECHNOLOGY PRINCIPLES OF OPTOELECTRONIC MODULE REALIZATION FOR RECORDING, PRESERVATION AND DISPLAY OF THE INFORMATION
Authors: Kozhemyako Volodymyr P. , Yarovyy Andriy A. , Novytsky Ruslan M.
Published: February 2021

In given article use of the approaches, developed by the authors, is offered at designing separate structures of computing systems, which is based of optoelectronic principle of eye - processor information processing on the basis of dynamic multifunctionality, with the purpose of maintenance of development and application of nanotechnology optoelectronic high-performance elements and devices for their further integration in general structure of computing, laser and optoelectronic systems, and also systems of artificial intelligence.
EFFICIENT PREPROCESSING FOR WEB LOG COMPRESSION
Authors: Deorowicz Sebastian , Grabowski Szymon
Published: February 2021

Web log files, storing user activity on a server, may grow at the pace of hundreds of megabytes a day, or even more, on popular sites. They are usually archived, as it enables further analysis, e.g., for detecting attacks or other server abuse patterns. In this work we present a specialized lossless Apache web log preprocessor and test it with combination of several popular general-purpose compressors. Our method works on individual fields of log data (each storing such information like the client’s IP, date/time, requested file or query, download size in bytes, etc.), and utilizes such compression techniques like finding and extracting common prefixes and suffixes, dictionary-based phrase sequence substitution, move-to-front coding, and more. The test results show the proposed transform improves the average compression ratios 2.70 times in case of gzip and 1.86 times in case of bzip2.
IDENTIFICATION OF MONOD-IYERUSALIMSKII SYSTEM WITH LOOPBACK CONTROL
Authors: Pasichnyk Roman M. , Pigovsky Yuriy R.
Published: February 2021

Methods for structural and parametric identification of Monod-Iyerusalimskii system with loopback control are researched.
AHP METHOD APPLICATION FOR THE EVALUATION OF INTERNET WEBSITES – COMPUTER SHOPS’ CASE
Authors: Chmielarz Witold
Published: February 2021

The main objective of this paper is an analysis of possibilities of using Saaty’s AHP method in the evaluation of internet websites. The evaluation range is limited to selected websites of the computer shops which are most frequently visited by customers. In the beginning of the article basic assumptions of AHP method are presented. Next, the author shows AHP application in the dimensioning of websites as well as implications resulting from this approach. The last part of this article contains conclusions related to the analysed approach and claims for further research.
A NEW APPROACH TO SHAPE-BASED IMAGE RETRIEVAL
Authors: Amirani Mehdi Chehel , Sadeghi Gol Zahra , Beheshti Shirazi Ali Asghar
Published: February 2021

Content-based image retrieval (CBIR) is very active research topic in recent years. This paper introduces a new approach to shape-based image retrieval. At first, feature points are determined at the boundary of the shape as the extremums of a new version of the curvature function and the initial features are calculated at these points. The proposed method utilizes a supervised system for nonlinear combination of initial features for extraction of efficient and low dimensional feature vector for each shape. The retrieval performance of the approach is illustrated using the MPEG-7 shape database. Our experiments show that the proposed method is well suited for object indexing and retrieval in large databases.
PARADIGM SEMANTIC WEB IN THE CONTEXT OF DIGITAL LIBRARY: SERVICES AND INFORMATION INTEGRATION
Authors: Novytskyi O.
Published: February 2021

This paper presents a several of theoretical ideas and applied technology that can be embodied in the creation of Semantic Digital Library (SDL). In particular, considerable attention paid to how the Semantic Web technology is used in various aspects of DL. A basic level in the DL that may be carriers of semantic description. Described the advantages of this approach. It also highlights issues that arise during the integration of classical electronic libraries and Semantic Web a place in these processes. Made a brief overview of the world’s leading projects to create DL using Semantic Web.
DESIGN MODELS FOR EMBEDDED SYSTEMS AND SENSOR NETWORKS
Authors: Karakehayov Zdravko
Published: February 2021

This paper introduces a hierarchical design model for embedded systems which includes models of the application, the embedded system and the resources. The application model deals with locations to better describe distributed architectures. A location-driven method for design of distributed embedded systems is proposed as a direct extension of the design model. The method allows to benefit from fuzzy relationships between I/O variables and locations. An example shows a 29% reduction of the hardware complexity measured in number of pins. In case of wireless links the model allows sensor networks to gradually emerge as a class of embedded systems.
PKM LEAN MANAGEMENT PADA USAHA DAGANG PERTANIAN DALAM MEMILIKI VALUE ADDED SERVICE
Authors: Amrussalam Amrussalam , Supriatuti Eko
Published: February 2021

Khalayak sasaran pada program kemitraan masyarakat (PKM) ini adalah masyarakat yangproduktif secara ekonomi dengan permasalahan pokoknya adalah kurangnya pemahaman Mitrapada manajemen untuk menghilangkan adanya pemborosan (waste) pada kegiatanperdagangannya dan juga untuk pelayanan Mitra dalam menyediakan pelayanan pelengkap masihsangat kurang dalam memberikan kepuasan kepada pelanggan/petani. Tujuan pelaksanaanprogram ini adalah untuk memberikan pengetahuan dan kemampuan Mitra melalui pelatihan danmelakukan penerapan konsep lean management dengan menggunakan konsep 5S untukmenghilangkan pemborosan (waste) dalam memiliki value added service. Metode pelaksanaandalam program ini dilakukan dengan 2 (dua) tahap, yaitu tahap persiapan dan tahap pelaksanaan.Hasil dan luaran pelaksanaan kegiatan program kemitraan masyarakat (PKM) adalahmeningkatnya kemampuan manajemen untuk Mitra terhadap konsep lean management dalammenghilangkan pemborosan (waste) pada kegiatan perdagangannya dan meningkatnya pelayananMitra dalam memberikan value added service kepada pelanggan/petani, sehingga dapatmemberikan kepuasan kepada petani/pelanggan tersebut.
PROSES BALLASTING DAN DEBALLASTING DI PELABUHAN OTORITAS BATAM BERBASIS BOW TIE EVIRONMENTAL RISK ASSESSMENT
Authors: Basuki Minto , Lukmandono Lukmandono , Zau Beu Maria Margareta
Published: February 2021

Kegiatan ballasting dan deballasting dalah proses memasukan air laut dalam tangki balasa kapaldalam rangka menjaga stabilitas kapal dalam pelayarannya. Pada saat kapal kosong dilakukanballasting, yaitu memasukan sejumlah air laut ke dalam tangki balas. Sesampainya dipelabuhantujuan pada saat kapal memuat muatan, air balas dikeluarkan dari tangki balas. Pada saat air balasdikeluarkan dari tangki balas dan dibuang keperairan diduga banyak spesies ikutan yang bersifatinvasive ikut terbuang. Tujuan penelitian ini melakukan penilaian risiko menggunakan metode BowTie Environmental Risk Assessment. Data yang dipakai untuk analisis diperoleh dari pelabuhan diOtoritas Batam. Dari hasil pembahasan pelabuhan Otoritas Batam belum menjalankan Regulasi IMOMEPC 56/23 Annex 2 yang sudah diberlakukan. Otoritas pelabuhan Batam perlu melakukanpenyesuaian terhadap aturan Regulasi IMO tersebut dalam pengelolan air balas kapal. Pengelolan airbalas kapal dengan pendekatan terhadap perlindungan lingkungan (Evironmental Risk Assessment
DIAGNÓSTICO INESPERADO DE HANSENÍASE EM PROFISSIONAIS DE SAÚDE DURANTE CAPACITAÇÂO EM PETROLINA-PE
Authors: ARAÚJO Andrea Maia Fernandes de , PINHEIRO Ingrid Geovanna Bezerra , PEIXOTO Marlene Leandro dos Santos , SILVA David Souza , BARBOSA Danila dos Santos , COSTA Icaro Farias , ALBUQUERQUE Magnilde Alves Cavalcante
Published: February 2021

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COMPARAÇÃO DOS RESULTADOS DA BACILOSCOPIA PARA HANSENÍASE NOS PERÍODOS ANTERIOR E POSTERIOR À CAPACITAÇÃO DE PROFISSIONAIS DE SAÚDE
Authors: NARDI Susilene Maria Tonelli , ARAUJO Tania Maria , DUO-FILHO Valter Batista , MARTINS Laísla Zanetoni , LEMOS Ana Paula , PATINE Flávia dos Santos , BELOTTI Naiara Cristina Ule , BINHARDI Fernanda Modesto Tolentino , PASCHOAL Vania Del´Arco , PEDRO Heloisa da Silveira Paro
Published: February 2021

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BUSCA ATIVA DE HANSENÍASE EM POPULAÇÃO RESIDENTE EM ÁREA DE EX-ASILO COLÔNIA DO ESTADO DE SÃO PAULO
Authors: BERTOLUCI Daniele Ferreira de Faria , TAVARES Samara Costa , DIORIO Suzana Madeira , SILVA Eliane Aparecida , FACHIN Luciana Raquel Vincenzi , BELONE Andrea Faria Fernandes , SOARES Cleverson Teixeira , BARRETO Jaison Antônio , PINHEIRO Luiza , SILVA Karem Christine Corrêa e , ROSA Patrícia Sammarco
Published: February 2021

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Health Policy Immersion Experience of Doctoral Nursing Students: A Phenomenological Study
Authors:   South Shore University Hospital, Bay Shore, NY, USA, Baglietto Janice , Bono-Neri Francine ,   Long Island University, Post Campus, Brookville, NY, USA, Infante Elizabeth ,   Hospice Care Network, Woodbury, NY, USA, Lowers-Roach Maureen ,   New York Presbyterian Medical Center, New York, NY, USA, Walsh Denise ,   Long Island University, Post Campus, Brookville, NY, USA
Published: February 2021

Background: In today’s political environment, there is a significant need for healthcare professionals to be aware of health policy and its impact on practice and the population. Nursing, a respected and trusted profession, has a responsibility to increase its awareness and advocacy efforts to ensure practice and execution of responsible and ethical health policy. Objectives: The purpose of this study was to describe the lived experience of doctoral nursing students' (PhD and DNP) engagement in a week-long immersion trip to Washington, D.C. as a requirement of their mandatory health policy course. This immersion trip encompassed participation in numerous activities that focused on health policy, nursing's role in research, and its presence in the political arena. In addition to describing doctoral nursing students' lived experience, the researchers sought to discover how this experience impacts doctorally-prepared nurses’ political awareness and future interest in health policy. Methods: Data were gathered using Google Forms to obtain doctoral nursing students’ experiences after participating in a week-long Washington, D.C. immersion as part of their mandatory doctoral coursework at a Mid-Atlantic college in the United States. The survey was emailed to 43 PhD and DNP students, of which 30 met the inclusion criteria. Demographic data analysis, in addition to thematic analysis of survey responses with the aid of NVivo, were performed. Results: Four themes emerged from the analysis to describe the experience and impact that the week-long Washington, D.C. immersion had on doctoral nursing students: Knowledge and Understanding of the Political Process, Recognition of the Role Professional Nursing Organizations Play in the Political Arena, Empowerment Through Increased Awareness, and Nursing’s Role as an Advocate for the People Conclusion: Through increased knowledge and awareness of health policy, doctorally-prepared nurses may be more inclined to seek and engage in the political arena and actively participate in advocacy efforts to improve health policy and the healthcare system. Keywords: advocacy, doctoral nursing students, health policy, healthcare system, political process
Asociación del sobrepeso y caries dental en niños de 3 a 6 años
Authors: Ayala-Escandón Carmen de la Luz , Zambrano-Palencia Olga Raquel , Franco-Trejo Christian Starlight
Published: February 2021

Antecedentes: En los últimos años de nuestro país, los cambios en los patrones de alimentación han incrementado los casos de obesidad y sobrepeso en los niños. Objetivo: determinar si la prevalencia de caries dental se asocia al sobrepeso y obesidad en preescolares de la Zona Metropolitana Zacatecas-Guadalupe. Materiales y Métodos: Se realizó estudio observacional de cohorte retrospectivo, en dos grupos de estudio: niños con peso normal (n=108) y niños con sobrepeso u obesidad (n=54). Para determinar el sobrepeso o peso normal, se utilizó un estadiómetro y una báscula digital, los datos se analizaron de acuerdo a los puntos de corte de IMC para cada edad según género con tablas de percentiles del Center for Diseases Control (CDC). Para el registro de la enfermedad caries dental se realizó examen clínico de las superfi dentales bajo luz artifi espejo dental plano, sonda de la OMS y barreras de protección, utilizando los criterios del Sistema Internacional de Evaluación y Detección de Caries Dental (ICDAS II). Los datos recopilados se procesaron en el paquete estadístico SPSS 17 para la obtención de tablas y fi Para determinar la asociación entre las variables de estudio se utilizó las pruebas X2 y riesgo relativo (RR). Resultados: En los niños con peso normal la prevalencia de caries fue de 77.8% mientras que en los niños con sobrepeso fue de 69.1%. Conclusiones: Este estudio no encontró evidencia de asociación entre caries dental y sobrepeso.
Relación de caries dental y el índice de masa corporal en niños de edad preescolar
Authors: García-Padilla Mónica Vianey , Sanín-Rivera Ingrid Patricia
Published: February 2021

La caries dental sigue siendo un problema con alta prevalencia así como el sobrepeso y la obesidad en los preescolares de México. Objetivo: determinar la relación de Caries Dental y el Índice de Masa Corporal en los preescolares. Material y métodos: se realizó un estudio transversal con una muestra de 348 preescolares del municipio de Tepatitlán Jalisco, midiéndose el Índice de masa corporal, Índice de caries dental, el índice de higiene oral simplificado y los momentos de azúcar/día. Resultados: se observó que en los 348 niños se encontró una prevalencia de caries del 75.3% con solo un 0.4 ±0.05 de dientes obturados; el 56.3 % estuvieron dentro del peso normal y 43.7% se encontraron con problemas de nutrición. Los niños que presentaron índice de caries más alto fueron los eutróficos y los de obesidad grave presentaron más lesiones cariosas. Sin embargo, los niños en sobrepeso y obesidad son los que tuvieron menores porcentajes de lesiones cariosas. Conclusiones: no existe una relación significativa entre la caries dental y el índice de masa corporal en el grupo estudiado, sin embargo, la prevalencia de caries y problemas nutricionales en los niños de edad preescolar son altos. Observándose que con un aumento del índice de higiene oral existe un aumento en el índice de caries siendo así de gran importancia fomentar cuidados orales preventivos y una atención dental temprana.