bluuebunny/crossref_metadata_2025 huggingface dataset:
STEAM BOILER CONTROL SYSTEM USING TENSOR ANALYSIS METHODS
Authors: Sidletskyi Viktor
Published: February 2021

Approaches to the control of steam boilers are analyzed in the article. It is recommended to use the method of tensor analysis for identification of the current state of the heat-energy process for conducting regulating action. It is suggested that the vectors of the input and output variables of the technological process with a tensor are to be connected, which for orthonormal systems adopts a diagonal form that facilitates the calculation of regulating actions. This article presents the results of simulation when traditional methods of calculating the coefficients of the regulator are used and the calculation of the regulating action using a tensor model. The use of such a technique allows conducting the necessary regulating actions taking into account the operation of the individual apparatus. So, its operation is coordinated as a structural unit in the technological line in case of occurrence of deviations and transients.
ANALYSIS OF CLOUDINESS BY SEGMENTATION AND MONITORING OF SATELLITE MAP IMAGES
Authors: Melnyk Roman , Kalychak Yurii , Kvit Roman
Published: February 2021

The algorithm of the dynamic threshold segmentation of images using clipping plane in a three-dimensional XYZ image space is proposed. To build the clipping plane of the dynamic threshold the precession and nutation angles as the base threshold values are found. The developed algorithm is applied to the satellite map images to get cloudiness intensity. The satellite map images are transformed by segmentation and inversion. The segmented and inverted images are scanned to receive the distributed cumulative histograms. By the help of so-called cloudiness meter the statistical data is processed for calculation and monitoring of cloudiness in Ukraine. The formulas to create an image of the distributed cumulative histogram are considered. Formulas to reconstruct images of the rotated satellite map images are proposed. The satellite weather map images were taken from the Wunderground services. The clustering algorithm is used to classify the regions of Ukraine by cloudiness intensity, which were created distributed cumulative images. The clustering algorithm is based on the agglomerative procedure.
SHOPPING ASSISTANT APP FOR PEOPLE WITH VISUAL IMPAIRMENT: AN ACCEPTANCE EVALUATION
Authors: Ahmad Sabrina , Asmai Siti Azirah , Zaid Siti Zarah , Kama Nazri
Published: February 2021

Visual impairment refers to when someone lose part or all of the ability to see. People with visual impairment has many limitations including the freedom of doing grocery shopping independently. They will have difficulty to read ingredients or dietary information which usually returned in small font letters on the products. This information is deemed important to make informed decision in order to purchase products. Therefore, this research is conducted to investigate the need of grocery shopping assistant app for people with visual impairment and their acceptance level. An empirical investigation method is adapted and data was collected based on Technology Acceptance Model (TAM). The evaluation results indicate that the people with visual impairment positively inclined towards utilizing shopping assistant app caused by the technology is easy to use and therefore they can obtain benefit from the app, concluding that Perceived Ease of Use is a better indicator for the attitude towards using the shopping assistant app.
AN AUTOMATIC TRANSFORMATION METHOD FROM THE E3VALUE MODEL TO UML2 SEQUENCE DIAGRAMS: AN MDA APPROACH
Authors: Kharmoum Nassim , Ziti Soumia , Rhazali Yassine , Omary Fouzia
Published: February 2021

Since the Model Driven Architecture (MDA) approach appearance, model’s transformation has been considered as one of the main computing keys in the software industry, which grows exponentially to ensure competitiveness. For that, the Object Management Group (OMG) offers for the MDA approach three abstraction levels, which are Computation Independent Model (CIM), Platform Independent Model (PIM) and Platform Specific Model (PSM). Most researchers put much focus on the PIM to PSM transformation because these levels have multiple common points, but they disregard the CIM to PIM transformation. So, our defiance in this paper is to propose a disciplined method that generates the UML2 Sequence diagrams automatically from the E3value model. Therefore, we produce the UML’s behavior and interaction model in the PIM level, from the value-based requirements model in the CIM level. The transformations are done automatically using the Atlas transformation language (ATL). The purpose is to reduce the effort, time, and the development cost of projects as all transformations is automated, increasing the chance of being more competitive in the software industry.
AMBINET – AN ENVIRONMENT FOR AMBIENT-ORIENTED MODELING
Authors: Glushkova Todorka , Stoyanov Stanimir , Stoyanova-Doycheva Asya , Ivanova Vanya , Doukovska Lyubka
Published: February 2021

The concept of the Internet of Things (IoT) is closely related to the concepts of Cyber-Physical System (CPS) and Cyber-Physical-Social System (CPSS). A key feature of these technologies is the integration of the virtual and physical world. In this paper, an environment for ambient-oriented modeling called AmbiNet is presented. The environment AmbiNet is implemented as a component of the reference architecture known as Virtual Physical Space (ViPS) that can be adapted for CPSS applications in various domains, for example a smart city, a personal touristic guide, or education. The need for virtualization of things from the physical world in a formal way is also considered. In the paper, the usability of the environment is demonstrated by modeling of services delivered to tourists in an intelligent city. The architecture of ViPS is also briefly described. Furthermore, the virtualization and modeling of spatial aspects through the AmbiNet formalism is demonstrated by an example.
COMPUTER REALIZATIONS OF THE CUBIC PARAMETRIC SPLINE CURVE OF BÈZIER TYPE
Authors: Stelia Oleg , Potapenko Leonid , Sirenko Ihor
Published: February 2021

This paper presents a new method for constructing a third degree parametric spline curve of C1 continuity. Like the Bèzier curve, the proposed curve is constructed and operated by control points. The peculiarity of the proposed algorithm is the assignment of some unknown values of the spline in the control points abscissas, which are based on the conditions of the first derivative continuity of the curve at these points. The position of the touch points, as well as the control points, can be set interactively. Changing of these points positions leads to a change in the curve shape. This allows the user to flexibly adjust the shape of the curve. Systems of algebraic equations with tridiagonal matrix for calculating the coefficients of a spline curve are constructed. Conditions for the existence and uniqueness of such a curve are presented. Examples of the use of the proposed curve, in particular, for monotone data sets, approximation the ellipse and constructing the letter "S" are given.
MULTI VEHICLE SPEED DETECTION USING EUCLIDEAN DISTANCE BASED ON VIDEO PROCESSING
Authors: Setiyono Budi , Sulistyaningrum Dwi Ratna , Soetrisno Soetrisno , Wicaksono Danang Wahyu
Published: February 2021

One component of smart city is smart transportation, known as Intelligent Transportation Systems (ITS). In this study, we discuss the estimation of moving vehicle speed based on video processing using the Euclidean Distance method. In this study, we examine the effect of camera angles on the video acquisition to speed estimation accuracy. In addition, Region of Interest (ROI) will be designed into three parts to determine which area is the most appropriate to be chosen, so that the estimated vehicle speed will be better. These approaches have never been studied by previous researchers. The separation between the background and foreground is conducted using Gaussian Mixture Models method. By comparing the displacement distance and the number of frames per second (fps), we obtain speed estimate for each vehicle. According to the experimental results, our system can estimate the speed of the vehicle with an accuracy of 99.38%.
COEVOLUTION PATTERNS TO DETECT AND MANAGE UML DIAGRAMS CHANGES
Authors: Rajabi Bassam Atieh , Lee Sai Peck
Published: February 2021

UML diagrams are divided into different perspectives in modelling a problem domain. Preserving coevolution among these diagrams is very crucial so that they can be updated continuously to reflect software changes. Formal methods such as Coloured Petri Nets (CPNs) are widely used in detecting and handling coevolution between software artifacts. Although ample progress has been made, it still remains much work to be done in further improving the effectiveness and accuracy of the state-of-the-art coevolution techniques in managing changes in UML diagrams. In this research, a set of 84 coevolution patterns for supporting coevolution among UML diagrams are proposed to trace the diagrams’ inconsistencies and to determine the change impact incrementally after updating diagrams elements. Coevolution patterns are applied to UML class, object, activity, statechart, and sequence diagrams to cover the different perspectives of UML diagrams. The researcher uses CPNs as a formal language of modelling case study models for the proposed patterns. CPNs tools simulation and monitoring toolboxes are used to validate and monitor the proposed coevolution patterns models and to collect quantitative data about the patterns.
RESEARCH OF DIAGNOSTIC PARAMETERS OF COMPOSITE MATERIALS USING JOHNSON DISTRIBUTION
Authors: Babak Vitaliy , Eremenko Volodymyr , Zaporozhets Artur
Published: February 2021

In this paper, it was proposed to carry out a preliminary normalization of diagnostic parameters using the Johnson distribution, which with three basic distribution groups (SL, SB, SU), covers a wide class of empirical distributions. The mathematical description of the family allows us to find the approximating probability density function in an explicit form, to determine the distribution parameters for obtaining the corresponding function (curve), as well as the inverse function for finding the quantiles of the specified levels. To assess the accuracy of the obtained normalized data, they were compared with the data obtained by replacing the resulting law with a Gaussian one. Percentages of values were compared in the implementation under study, which concentrated in the limits of estimated quantiles. Implementations were obtained using the simulation method. By the same method, the correctness (relative systematic error) of determining the quantile values of the specified levels was evaluated. The error value δ was estimated between the conditionally true quantile value calculated from the generated pseudo-general complex and the value estimated using the methods considered in the paper. Obtained data show that the relative error in the calculation of quantiles using the Johnson distribution does not exceed 0.07% and decreases in two orders of magnitude than the currently accepted procedure for replacing sample laws with Gaussian.
IMPROVING CLASSIFICATION PERFORMANCE OF NEURO-FUZZY CLASSIFIER BY IMPUTING MISSING DATA
Authors: Tarle Balasaheb , Akkalaksmi Muddana
Published: February 2021

In medical data classification, if the size of data sets is small and if it contains multiple missing attribute values, in such cases improving classification performance is an important issue. The foremost objective of machine learning research is to improve the classification performance of the classifiers. The number of training instances provided for training must be sufficient in size. In the proposed algorithm, we substitute missing attribute values with attribute available domain values and generate additional training tuples that are in addition to original training tuples. These additional, plus original training samples provide sufficient data samples for learning. The neuro-fuzzy classifier trained on this dataset. The classification performance on test data for the neuro-fuzzy classifier is obtained using the k-fold cross-validation method. The proposed method attains around 2.8% and 3.61% improvement in classification accuracy for this classifier.
A PRACTICAL PERFORMANCE INDEX FOR COMPARING OF OPTIMIZATION SOFTWARE
Authors: Attanasio Andrea , Beraldi Patrizia , Guerriero Francesca
Published: February 2021

In this paper we propose a new practical performance index for ranking of numerical methods. This index may be very helpful especially when several methods are tested on a large number of instances, since it provides a concise and precise idea of the relative efficiency of a method with the respect to the others. In order to evaluate the efficiency of the proposed rule, we have applied it to the numerical results presented on previously published papers.
POSSIBILITIES OF INCREASING THE RELIABILITY BY METHODS OF SOFTWARE AND TIME REDUNDANCY
Authors: Siroky Peter , Hartansky Rene , Petrilak Jan
Published: February 2021

This paper includes some possibilities how to solve problems with the improvement of systems reliability on the field where traditional methods of EMC are not sufficient. Two basic types of methods will be introduced. First, methods of software redundancy and second methods of time redundancy.
РОЗВ’ЯЗУВАННЯ НЕЛІНІЙНО-ПОЛІНОМІАЛЬНИХ РІВНЯНЬ ГІЛЛЯСТИМИ ЛАНЦЮГОВИМИ ДРОБАМИ
Authors: Недашковський М.
Published: February 2021

пропонуються нові підходи до розв'язання поліноміально-нелінійних матричних рівнянь за допомогою матричними гіллястих ланцюгових дробів. Для запису розв’язків матричних поліномів пропонуються алгоритми, які дозволяють одержати розвинення шуканих невідомих у так звані фігурні J- дроби, Т-дроби та С-дроби, також періодичні матричні гіллясті дроби канонічного вигляду. Результати можуть використані у системах комп’ютерної алгебри таких як REDUCE, muMATH, MATHEMATICA, MAPLE, MatLab, MathCad і DERIVE.
ESTIMATION OF THE LYAPUNOV SPECTRUM FROM ONE-DIMENSIONAL OBSERVATIONS USING NEURAL NETWORKS
Authors: Golovko Vladimir
Published: February 2021

This paper discusses the neural network approach for computing of Lyapunov spectrum using one dimensional time series from unknown dynamical system. Such an approach is based on the reconstruction of attractor dynamics and applying of multilayer perceptron (MLP) for forecasting the next state of dynamical system from the previous one. It allows for evaluating the Lyapunov spectrum of unknown dynamical system accurately and efficiently only by using one observation. The results of experiments are discussed.
INTERVAL CALIBRATION MODEL OF MULTISENSOR SYSTEM
Authors: Voschinin Alexander , Skibitski Nikita
Published: February 2021

Problem of multisensor system calibration is of great importance in a number of applications. Most often the problem is solving by means of statistical methods using data of calibration controlled experiment. However, in many cases uncertainty and inaccuracy of experimental data more reasonably to express not in terms of random errors but in terms of known bounded absolute errors. For this case based on the introduced definition of “interval readings” interval calibration model is suggested. Within interval paradigm all calibration subproblems are reasonably solved including sensor sensitivity test, most accurate sensors subset selection and aggregate estimation of measurable variable uncertainty interval. There are given a numerical examples.
DSP-ALGORITHMS FOR CARDIAC SYMPTOMS INVESTIGATIONS
Authors: Kalchev Ivan
Published: February 2021

The achievements of the advanced medicine are not possible without the use of technical sciences. The aspiration for perfect instrumentation and for high precision of the technical systems for analysis of cardiac activity are still a challenge to engineers. The invention of more effective and with better quality indexes systems will permit a fast diagnostics, therefore a better medical treatment. In the present paper the main cardiac-vessel symptoms are described and an possible algorithm for program assurance of µP-system for cardiac investigations is proposed. The system is based on ADU 824 type of microprocessor, but the programs are compiled in MATLAB 4.2 environment.
CLASSIFICATION OF PRODUCTS AND SERVICES TO SUPPORT BUSINESS PROCESS ENGINEERING AND E-COMMERCE
Authors: Reusch Peter J. A. , Reusch Pascal
Published: February 2021

Decades ago individual approaches to classify products and services had been introduced within companies to unify products and to reduce stocks and costs. Other approaches had been introduced to support international trade and tariff systems. Today new approaches are introduced to support e-commerce and improve business processes. All these approaches are different in the way how to classify, what to classify, and what results to get – and the language they use. The harmonization of all these approaches is very difficult. But especially companies that want to take part in B2B-business need bridges between the different approaches. In this paper we first present a new XML-based system to remove the language barrier within classification systems and to improve data exchange. In the second part we present an implementation of classification systems based on topic maps according to the XTM standard to implement single classification systems and establish mappings between corresponding classes of different classification systems.
A GRAPH-BASED MODEL FOR THE INFECTION PHENOMENON
Authors: Bulancea Catalin , Craus Mitica
Published: February 2021

A graph-based model is proposed for studying interactions and evolution in infection process. There are defined and tested mutational and decisional structures for pathogen agents and a reaction mechanism for the host. MPI and C# implementations were used to make some simulations. The results have shown that artificial system evolution is closed to the evolution of the real system.
AN APPROACH FOR DETERMINING THE PERIODICITY OF REGULATION WORK OF RISK TECHNICAL SYSTEMS
Authors: Petrov Nikolay
Published: February 2021

The estimation of the regulation work periodicity of the risk technical systems is an extremely important moment for its technical service. Many scientific publications concern this problem but most of them deal with a service process for an infinite technical exploitation period. In the present paper a solution of the problem for a limited interval of technical exploitation is suggested. A reliability model of the observed process is developed as the intensity of the failure flux is chosen for a reliability criteria.
DSP BASED MEASURING LINE-SCAN CCD CAMERA
Authors: Fischer Jan , Radil Tomas
Published: February 2021

A simple, flexible and programmable line-scan CCD camera is presented in this paper. This camera is designed for measurement purposes such as dimension and position measurements. Camera enables implementation of various signal-processing algorithms as well as usage of various types of CCD sensors.
A NEW HYBRID SYSTEM FOR RECOGNITION OF HANDWRITTEN-SCRIPT
Authors: Saeed Khalid , Tabedzki Marek
Published: February 2021

A new method for object recognition and classification is presented in this paper. It merges two well-known and tested methods: neural networks and method of minimal eigenvalues. Each of these methods answers for a different part of recognition process. Method of minimal eigenvalues makes preparatory stage of analysis – of coordinates of characteristic points we get the vector describing given image. Next, it is recognized and classified with neural network. Gathering of characteristic points we perform with our view-based algorithm, but other methods should also do. In this work, method was applied for words in Latin alphabet – handwritten and machine-printed. The obtained results are promising.
A COMPARATIVE STUDY BETWEEN A MULTI-MODELS BASED APPROACH AND AN ARTIFICIAL NEURAL NETWORK BASED TECHNIQUE FOR NONLINEAR SYSTEMS IDENTIFICATION
Authors: Thiaw Lamine , Rybnik Mariusz , Malti Rachid , Chebira Abdennasser , Madani Kurosh
Published: February 2021

Recently, a number of works propose multi-model based approaches to model non-linear systems. Such approach could also been seen as some “specific” approach, inspired from ANN operation mode, where each neurone, represented by one of the local models, realizes some higher level transfer function. In this paper we present two different neural based approaches to such multiple models concept: one issued from conventional structure and the other based on self-organizing dynamic architecture. A comparative study between a multi-model based architecture and an ANN based one, in the frame of nonlinear system identification is reported.
NETWORKING PARADIGM FOR DISTRIBUTED SENSOR NETWORKS
Authors: Sitharama Iyengar S. , Wu Qishi , Rao Nageswara S. V.
Published: February 2021

An increasing number of distributed sensor networks are being deployed in a wide spectrum of scenarios for both military and civilian applications. The design of such systems requires the integration of many methods for solving various problems ranging from sensor deployment, through data communication, information fusion to environmental inference and hypothesis testing. This paper is focused on the network aspects in support of data communication services. We present some recent developments in networking techniques for multiple sensor systems in three topics: efficient mobile agent routing in mobile agent-based distributed sensor networks, bandwidth aggregation using multiple paths in wide-area wireline networks, and connectivity enhancement using node movements in small-area wireless mobile ad-hoc networks.
REMOVAL OF IMPULSE BURSTS IN SATELLITE IMAGES
Authors: Tsymbal Oleg , Lukin Volodymyr , Koivisto Pertti , Melnik Volodymyr
Published: February 2021

Characteristics of impulse bursts in satellite images are analyzed and methods for burst removal are consid- ered. Artificial compact burst model is proposed and test images are created. An advanced multipass algorithm for the detection and removal of compact bursts in the presence of both additive and multiplicative noise is proposed. The efficiency of the algorithm is evaluated quantitatively using the artificial test images and visually using the artificial test images and real radar and optical satellite images. It is shown through experiments that the proposed method removes impulse bursts efficiently while preserving information.
THE ALGORITHM OF SUPPLEMENTARY ARGUMENTS INCLUSION FOR INTERVAL MODELS STRUCTURAL IDENTIFICATION OF THE STATIC SYSTEMS
Authors: Dyvak Mykola , Manzhula Volodymyr
Published: February 2021

The problem of structural identification of static models of interval systems. Showing getting a unique solution for the problem of structural identification for different initial given structure models based on the complexity of the proposed algorithm sequential structures. An adaptive iterative procedure, which reduces the dependence of the result of structural identification of the magnitude interval error data.
USING BOUNDARY SCAN IN DIGITAL SYSTEMS
Authors: Kaminskaya Marina
Published: February 2021

Proposed fault control method in digital systems. He was developed with deductive simulation. Was proposed to use standard IEEE 1149.1 Boundary scan for control additional virtual outputs.
NEURAL-BASED RECOGNITION OF MULTI-PARAMETER SENSOR SIGNAL DESCRIBED BY MATHEMATICAL MODEL
Authors: Turchenko Iryna , Kochan Volodymyr , Sachenko Anatoly
Published: February 2021

The possibility of artificial neural network usage for recognition of a signal of a multi-parameter sensor is described in this paper. The general structure of data acquisition channel with usage of neural networks as well as mathematical model of output signal of a multi-parameter sensor is studied in this article. The model of neural network, training algorithm and achieved results of simulation modeling of a multi-parameter sensor signal recognition using MATLAB software are presented at the end of this paper.
OPTIMIZATION VIA SIMULATION: SOLUTION CONCEPTS, ALGORITHMS, PARALLELCOMPUTING STRATEGIES AND COMMERCIAL SOFTWARE
Authors: Ghiani Gianpaolo , Legato Pasquale , Musmanno Roberto , Vocaturo Francesca
Published: February 2021

Simulation optimization (or optimization via simulation) is defined as the optimization of performance measures based on outputs from stochastic simulations. Although several articles on this topic have been published, the literature on optimization via simulation is still in its infancy. In this paper the research in this field is reviewed and some issues that have not received attention so far are highlighted. In particular, a survey of solution methodologies is presented, followed by a critical review of parallel computing strategies and commercial software packages. A particular emphasis is put on problems with discrete decision variables.
NEURAL NETWORK BASED MICROCALCIFICATION DETECTION IN A MAMMOGRAPHIC CAD SYSTEM
Authors: Lasztovicza László , Pataki Béla , Székely Nóra , Tóth Norbert
Published: February 2021

This document presents the computer aided diagnosis system being developed to help experts in screening mammography. It is a very important project because about 8 % of women develop breast cancer in her lifetime therefore global screening is necessary. It means that reliable diagnosis of huge number of images must be solved. The basic architecture of the system and the information processing needed is presented. One of the most important tasks in mammographic diagnosis systems is microcalcification detection. It is solved by a hierarchical neural architecture. The original suggestion of that structure was improved by two ways. The image features used as inputs to the neural networks were analyzed and the feature set was extended. The neural architecture was embedded in a neural ensemble context for improving the quality of the solution further. Results of the tests of that detection procedure show that the false detection ratios are acceptable.
A PARALLEL MULTIRATE ALGORITHM FOR THE NUMERICAL INTEGRATION OF SYSTEM OF NONLINEAR DIFFERENTIAL EQUATIONS
Authors: Stakhiv Petro , Rendzinyak Serhiy
Published: February 2021

The new approach to calculate dynamic behavior of large-scale systems, separated on subsystems is presented. Parallelization efficiency of computing process is described.
SMART SILICON SENSOR – MAGNETIC COMPASS ON THE BASE OF A 3-D HALL STRUCTURE
Authors: Dimitrov Konstantin
Published: February 2021

In this paper is discussed some of the trends in the industrial designs of smart sensor systems. High performance sensor systems have been implemented by combining the sensing and signal processing functions on the same chip. A very promising magnetic compass for Earth magnetic field measurement is created on the base of a 3-D Hall structure.
NUMERICAL METHOD OF VIBRATIONS RESEARCH IN LARGE FLEXIBLE SYSTEMS
Authors: Mul Olena , Torres Delfim
Published: February 2021

The mathematical model of the real flexible elastic system is considered with the distributed and discrete parameters, which presents the equation at derivative parts with non-classical maximum terms. Complication of maximum terms makes impossible finding of exact analytical decision of such maximum task, in connection with what for researches the numerical method of the normal fundamental systems of decisions is used. Dependence of frequencies of possible vibrations is explored on different physical parameters of system. It is shown, that introduction to reverse communication network after speed with the defined values of the reverse communication coefficient allows controling the frequency spectrum in which excitation of vibrations are possible.
THE PERSPECTIVE TECHNOLOGIES OF IDENTIFICATION AND AUTHENTICATION OF FINANCIAL TRANSACTIONS
Authors: Golovashych Sergiy
Published: February 2021

In the article comparative description of modern technologies of authentication on the basis of smart cards is presented, the lacks of each of the considered technologies are noticed and the chart of dynamic authentication which allows removing the basic exposed failing is offered. The ground of expedience of NFC-technology application for construction of authentication systems, providing maximal defense of user from abuses of attendants is shown also.
METHOD OF CONSIDERATION A CHANGEABILITY OF EXTERNAL ENVIRONMENT AS AN ALTERNATIVE METHOD OF SOCIO-ECONOMIC PROCESSES MODELING
Authors: Belz Oleksandra
Published: February 2021

The method of design of economic dynamics in a variable environment, which enables to carry out arbitrary nonlinear transformation and describe the moments of change of properties of the system without the problem of attachment of models to the time factor.
CONSIDERATIONS FOR E-FORENSICS: INSIGHTS INTO IMPLICATIONS OF UNCOORDINATED TECHNICAL, ORGANISATIONAL AND LEGAL RESPONSES TO ILLEGAL OR INAPPROPRIATE ON-LINE BEHAVIOURS
Authors: Broucek Vlasti , Turner Paul
Published: February 2021

The growing incidence of e-crime and computer misuse has increased demand for effective defensive and offensive solutions. Most responses have tended to focus on discrete sets of technical, organisational or legal challenges, but there is increasing recognition of the need for more integrated solutions that balance security, individual privacy and the generation of legally admissible digital evidence. More importantly, there is also proof to indicate that these fragmented approaches are impairing their own effectiveness due to the inter-relatedness of challenges faced. This research paper adopts an e-forensic approach to examine the links between technical, organisational and legal responses to the challenges posed by illegal or inappropriate on-line behaviour. The paper acknowledges some of the numerous challenges that remain unresolved in each approach and argues that future developments must be focused on integrated and balanced solutions that are calibrated to address the dynamic and multi-faceted nature of the forensic computing domain.
AGENT-BASED SIMULATION OF DDOS ATTACKS AND DEFENSE MECHANISMS
Authors: Kotenko Igor , Ulanov Alexander
Published: February 2021

The paper considers an approach to modeling and simulation of cyber-wars in Internet between the teams of software agents. According to this approach, the cybernetic opposition of malefactors and security systems is represented by the interaction of two different teams of software agents – malefactors’ team and defense team. The approach is considered by an example of modeling and simulation of “Distributed Denial of Service” (DDoS) attacks and protection against them. The paper also describes the software environment for multi-agent simulation of defense mechanisms against DDoS attacks developed by the authors and different experiments. The main components of the software environment are outlined. One of the numerous experiments on protection against DDoS attacks is described in detail. The environment developed is based OMNeT++ INET Framework.
PRIVACY PRESERVING PATTERN MATCHING ON SEQUENCES OF EVENTS
Authors: Oleshchuk Vladimir A.
Published: February 2021

We propose to use pattern matching on data streams from sensors in order to monitor and detect events of interest. We study a privacy preserving pattern matching problem where patterns are specified as sequences of constraints on input elements. We propose a new privacy preserving pattern matching algorithm over an infinite alphabet A where a pattern P is given as a sequence { pi , pi ,..., pim } 1 2 of predicates pi j defined on A . The algorithm addresses the following problem: given a pattern P and an input sequence t, find privately all positions i in t where P matches t. The privacy preserving in the context of this paper means that sensor measurements will be evaluated as predicates ( ) pi ej privately, that is, sensors will not need to disclose the measurements ( ) ( ) ( j )
VOICEXML-APPLICATIONS FOR E-COMMERCE AND E-LEARNING
Authors: Reusch Peter J. A. , Stoll Bastian , Studnik Daniel , Swade Joerg
Published: February 2021

VoiceXML is a language of the W3C to create voice-user interfaces, particularly for the telephone. It uses speech recognition and touchtone (DTMF keypad) for input, and pre-recorded audio and text-to-speech synthesis (TTS) for output. The text-to-speech synthesis feature of advanced VoiceXML tools like WebSphere opens new perspectives for e-commerce and e-learning. We are no longer restricted to pre-recorded audio but can bring any text to the ear of the user – a user that could be visually impaired and needs a voice channel to communicate – or a user who can read but who prefers to listen. VoiceXML-applications have been implemented by the authors to support e-commerce (selection of commodities from catalogues) and user guides for hardware (mobile phones, etc.) and software systems (MS project, etc.). New contributions to e-learning are offered.
HIERARCHICAL DECOMPOSITION OF PETRI NETS FOR ANALYSIS AND DESIGN OF DIGITAL MICROSYSTEMS
Authors: Karatkevich Andrei , Andrzejewski Grzegorz
Published: February 2021

The paper is dedicated to hierarchical Petri nets with application to design of control devices. It consists of two parts. The first part introduces a concept of simplifying analysis of flat Petri nets (we discuss analysis of reachability and liveness) by means of hierarchical decomposition. We present a class of subnets which can be replaced by the macroplaces. Further we describe properties of such decomposition and show, that analysis of the mentioned properties of a net can be reduced to the corresponding analysis of the elements of decomposition. A method allowing to obtain the decomposition is presented. The second part presents an approach to specification of a digital control system behavior by means of hierarchical Petri nets. We describe a model, called HPN, which has some of important properties, simplifying description of strongly reactive systems.
MODULAR AND SELF-ORGANIZING CONNECTIONIST SYSTEMS: TOWARD HIGHER LEVEL INTELLIGENT FUNCTIONS
Authors: Madani Kurosh
Published: February 2021

Recent advances in “neurobiology” allowed highlighting some of key mechanisms of animal intelligence. Among them one can emphasizes brain’s “modular” structure and its “self-organizing” capabilities. The main goal of this paper is to show how these primary supplies could be exploited and combined in the frame of “soft-computing” issued techniques in order to design intelligent artificial systems emerging higher level intelligent behavior than conventional Artificial Neural Networks (ANN) based structures.
NEW METHOD FOR CONSTRUCTION OF OPTIMAL SCALAR QUANTIZERS FOR LAPLACIAN SOURCE
Authors: Peric Zoran , Nikolic Jelena , Pokrajac Dragoljub
Published: February 2021

In this paper we consider methods for computing the necessary parameters when constructing the optimal scalar quantizers for Laplacian source. We investigate two approaches to the problem of finding the sets of optimal parameters. The first approach requires solving the transcendental equations, but provides nearly optimal values of the scalar quantizers’ parameters on successive manner. The proposed approach is an approximation method that linearizes transcendental equations providing simple and fast computing of scalar quantizers’ parameters. We demonstrate that the proposed technique provides parameters values that are very close to the optimal ones.
AN MPI-BASED FRAMEWORK FOR PARALLEL PROCESSING OF INTEGRATED CIRCUITS LAYOUT IMAGES
Authors: Otwagin Aleksej , Doudkin Alexander
Published: February 2021

We consider basic algorithms and processing technologies for integrated circuit layout images. The images represented as a set of frames can regard as a dataflow and the processing are perfectly suited for parallel implementation. We propose a framework architecture for designing parallel systems of image dataflow processing. The framework uses the algorithm of a virtual associative network for increasing processing speed and system throughput during runtime.
REVIEW OF INDUSTRIAL APPLICATIONS OF COMPUTATIONAL INTELLIGENCE
Authors: Frayn Colin M.
Published: February 2021

Bringing cutting-edge natural computation research into industry is a challenging task, with numerous obstacles to overcome. In this paper I describe a few selected projects that we have developed at the Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA) and I discuss the promising future of Computational Intelligence techniques in industry.
MATHEMATICAL MODEL OF PHOTOPLETYSMIC SIGNAL AS THE BASE FOR INFORMATIONAL PARAMETERS IDENTIFICATION
Authors: Martchenko Borys , Mlynko Bogdana , Fryz Mykhaylo
Published: February 2021

Taking into account the biophysical genesis of researched signal and its rhythmic nature the new mathematical model of photopletysmic signal as a linear periodical random process is developed; characteristic functions analysis of signal, experimental informational parameters estimating are possible with this model.
COMPARATIVE ANALYSIS OF NEURAL NETWORKS AND STATISTICAL APPROACHES TO REMOTE SENSING IMAGE CLASSIFICATION
Authors: Kussul Nataliya , Skakun Serhiy , Kussul Olga
Published: February 2021

This paper examines different approaches to remote sensing images classification. Included in the study are statistical approach, in particular Gaussian maximum likelihood classifier, and two different neural networks paradigms: multilayer perceptron trained with EDBD algorithm, and ARTMAP neural network. These classification methods are compared on data acquired from Landsat-7 satellite. Experimental results showed that to achieve better performance of classifiers modular neural networks and committee machines should be applied.
PREDICTION OF FATIGUE CRACK GROWTH PROCESS VIA ARTIFICIAL NEURAL NETWORK TECHNIQUE
Authors: Nechval Konstantin N. , Nechval Nicholas A. , Bausova Irina , Skiltere Daina , Strelchonok Vladimir F.
Published: February 2021

Failure analysis and prevention are important to all of the engineering disciplines, especially for the aerospace industry. Aircraft accidents are remembered by the public because of the unusually high loss of life and broad extent of damage. In this paper, the artificial neural network (ANN) technique for the data processing of on-line fatigue crack growth monitoring is proposed after analyzing the general technique for fatigue crack growth data. A model for predicting the fatigue crack growth by ANN is presented, which does not need all kinds of materials and environment parameters, and only needs to measure the relation between a (length of crack) and N (cyclic times of loading) in-service. The feasibility of this model was verified by some examples. It makes up the inadequacy of data processing for current technique and on-line monitoring. Hence it has definite realistic meaning for engineering application.
HOLISTIC SELF-REPROGRAMMING OF NEURAL NETWORKS: BETWEEN SELF-ORGANIZATION AND SELF-OBSERVATION
Authors: Mariage Jean-Jacques
Published: February 2021

Neural networks (NNs) are inspired – at least metaphorically –from biological solutions nature selected by evolution. On one hand, learning algorithms' efficacy has been widely demonstrated experimentally, even if the mathematical proof of their convergence is not always very easy to establish (SOM). On the other hand, biological mechanisms like brain wiring or embryology remain partly understood and how life or the bases of consciousness are related to the underlying biological substrate remains a total mystery. The same goes for memory. We don’t really know how information is stored in and recovered from biological neural structures. We therein paradoxically use complex systems, the hard core of which we still don't always fully understand, both regarding the models we build, as well as their former roots in the leaving world. In this theoretical paper, we resort to a few biological encoding schemata that bring insights into neural structures' growth, plasticity and reorganization, and we suggest reconsidering the metaphor in an adaptive developmental view.
HOW MANY PARACHUTISTS WILL BE NECESSARY TO FIND A NEEDLE IN A PASTORAL - WHO IS A LUCKY ONE?
Authors: Imada Akira
Published: February 2021

This article is a consideration on computer network intrusion detection using artificial neural networks, or whatever else using machine learning techniques. We assume an intrusion to a network is like a needle in a haystack not like a family of iris flower, and we consider how an attack can be detected by an intelligent way, if any.
ICT IN INSTRUMENTATION AND MEASUREMENT: EDUCATION AND SCIENTIFIC PUBLICATIONS
Authors: Rak Remigiusz J.
Published: February 2021

The article gives a review of reasons for developing and adopting the new ICT tools in teaching and scientific research in the field of Instrumentation and Measurement. It includes a description of the Internet- and multimedia-based educational model (e-learning). Then follows a description of the structure and tools of the modern scientific electronic book (e-book). The last part is oriented on Virtual Instruments, remote experiments and Virtual Laboratory.
EXPLORING THE MOBILE DEVICES AS A NEW FRONTIER FOR THE E-LEARNING IN INSTRUMENTATION AND MEASUREMENT
Authors: Cmuk Drago , Grimaldi Domenico , Rapuano Sergio
Published: February 2021

The mobile-learning establishes a new frontier for the research of the e-learning in the electrical and electronic measurement and instrumentation. Indeed, the reduced functionalities of the mobile devices must be integrated with the typologies of the services delivered to the student. By referring to the Remote Didactic Laboratory Laboratorio Didattico Remoto – LA.DI.RE. “G. Savastano” the delivered services taken into account are: experiment visualization, experiment control, and experiment creation. In order to enable the user of the mobile device to view, control and create the experiment application, several software architectures have been considered. Finally, the description of the solution adopted is given in the framework of the LA.DI.RE. “G. Savastano”.
HAPTIC HUMAN INTERFACES FOR ROBOTIC TELEMANIPULATION
Authors: Petriu Emil M. , Payeur Pierre , Cretu Ana-Maria
Published: February 2021

Recent investigation in haptic man-robot interaction suggests that there are ultimately only two topical tactile feedback generation modalities for haptic human interfaces. These allow the human operator to handle either (i) temporary virtual reality-based material replicas of the local geometric and/or force profile at the contact areas of an unlimited set of generic objects that could virtually be handled during the manipulation, or (ii) permanent material replicas of a limited set of typical objects. In this paper, the two modalities are analyzed and examples of tactile human interfaces developed by the authors for telerobotic blind tactile exploration of objects, and for telerobotic hapto-visual stylus-style tool manipulation are presented to illustrate the proposed approaches. The necessary modelling of the elastic properties of 3D objects from experimental tactile and range imaging data is also presented using a neural network architecture that becomes an important component of the haptic interface.
MANAGEMENT OF E-LABORATORIES – DEVELOPMENT THROUGH BUSINESS PERSPECTIVE
Authors: Mutapčić Tarik , Cmuk Drago , Malarić Roman
Published: February 2021

This paper presents a design of a future Web based measurement laboratory, by applying new architectural approach considering the state of art of advanced technology as well as the strategy for the future business perspective. Such approach also provides a lot of solutions and applications under the real conditions covering different areas of industrial research, operational analysis and system research methods. The paper discusses the results of preliminary testing using Appreciative Inquiry methodology, that are the basis for conceiving, designing and preparing marketing aspects of an e-laboratories and m-laboratories, considering its cost-effectiveness and multifunctionality of the applied model for a wide range of users. The result of this new approach will completely optimize current “e” and “m” laboratory solutions [1]. Management through business perspective is not only technical development, it also includes educational, humanitarian, and commercial aspects.
ANALYSIS OF THE MEDICAL DATA STRUCTURE USING SELFORGANISING MAPS
Authors: Hodych O. V. , Nikolsky Yu. V. , Pasichnyk V. V. , Scherbyna Yu.Scherbyna M.
Published: February 2021

In this article the authors discuss several approaches to high dimensional data structure analysis using Self- Organising Maps. The describe approaches utilise graphical images for the purpose of data structure interpretation. The evaluation of the discussed techniques has been performed using the real medical data from cardiology. The research, results of which are outlined in this paper, is a continuation of the earlier work related to the analysis of the same medical data. It is envisaged that results obtained in this and earlier research work will form a foundation for creation of a robust technology to be used for automation of diagnostic tasks in medicine.
CLASSIFICATION DATA EXPLORATION METHODS IN MODERN REALTIME DATA WAREHOUSE
Authors: Chłapiński Jakub , Mazur Piotr , Murlewski Jan , Kamiński Marek , Sakowicz Bartosz
Published: February 2021

The goal of this article is to introduce problems that may arise during analysis of classification methods used in data mining applications. In the following sections some of the most common classification techniques are described along with several proposed extensions which allow these methods to be used in incremental data warehouses. The primary focus was aimed at the problem of performing incremental learning methods that may be used in near realtime data warehousing applications.
VISUAL PATTERN STRUCTURE INVESTIGATION BY CLUSTERING PACKAGE
Authors: Melnyk Roman , Roman Yuriy
Published: February 2021

The paper contains research results of graphic file format influence on image structure, quantitative changes in structuring coefficients of clustered images, influence of deformation changes caused by destruction processes on image quality. Clustering package for visual black-white and grey patterns was taken as the main instrument for investigation.
THE APPROACH TO OPTIMAL DISTRIBUTION OF TASKS IN THE COMPUTING SYSTEM
Authors: Yurich Mary
Published: February 2021

In given article the approach to statement of a problem of optimal distribution of tasks in the computing system consisting of computers of various capacity and streams of tasks with different total duration various, leaning on the basic mathematical positions of a classical transport problem is considered, but considering thus specificity of a problem that will allow to find further more effective decision for such problems. It is proved, that the problem of distribution of tasks in the computing system can be considered as the modified transport problem.
CLASSIFICATION OF METHODS OF THE SIGNAL SEMANTIC WAVELET TRANSFORM FOR IMAGE CONTOUR SEGMENTATION
Authors: Polyakova Marina , Krylov Victor
Published: February 2021

In this paper the methods of signal semantic wavelet transform which underlines the edges of image in the edge detector task are analyzed and classified.
PROGRAM MODELS FOR INTERACTIVE DESIGN OF FAULT-TOLERANT SYSTEM WITH MIXED STRUCTURAL REDUNDANCY TAKING ACCOUNT MAINTENANCE SERVICE STRATEGIES
Authors: Mandziy Bohdan , Volochiy Bohdan , Ozirkovskyy Leonid
Published: February 2021

The problem of development of program models of the fault-tolerant system with the mixed structural redundancy is solved. For designing of program models an advanced technology of analytical modeling of the systems is used. This technology takes into account all features of structure and behavior of the system under the action of refusals and two variants of realization of maintenance service strategy. It provides possibility of multiple analysis at the small expenses of time. The results of researches of the fault-tolerant system, which illustrate possibilities of decision of tasks of reliability analysis and reliability synthesis, are resulted in the article.