bluuebunny/crossref_metadata_2025 huggingface dataset:
SOSYAL AĞ ANALİZİ VE BİR UYGULAMASI
Authors: ÇELİK Şenol
Published: February 2021

Çalışmanın amacı, kanatlı hayvan yetiştiriciliği alanında 2002-2019 yılları arasında SCI-Expanded kapsamında yayımlanan makale başlığında “Poulty science” ibaresi olan 338 çalışmayı sosyal ağ analizi ile inceleyerek, son yıllardaki trendleri belirlemektir. Bu kapsamda, Web of Science Core Collection veri tabanında “poultry science” konu başlıklarında tarama gerçekleştirilmiş ve çalışmalara ait bibliyometrik verilere ulaşılmıştır. Kanatlı hayvan yetiştiriciliği konusunda çalışan akademisyen ve araştırmacılara katkı sağlamak amacıyla, poultry science kavramıyla ilgili güncel konular, bu çalışma ile birlikte ortaya çıkarılmıştır. Çalışmalar; yıllara göre yayın sayıları, yayın türleri, atıf analizleri, ülke işbirliktelikleri ve ortak atıf ağları bağlamında incelenmiştir. Ayrıca references, authors and keywords ile references, country and keywords yönelimlerinin belirlenmesinde sosyal ağ analizi kullanılmıştır. Analiz sonuçlarına göre, “poultry science” alanında en fazla yayın yapan dergiler sırasıyla Poultry Science, Animal Nutrition and International Journal of Food Microbiology dergileridir.
Musings on the legal framework for resolution of foreign investment disputes in Nigeria
Authors: Ajudua Princess Pat Ada
Published: February 2021

Resolution of dispute arising from foreign investments in Nigeria is achieved through non-judicial and judicial mechanisms, otherwise known as arbitration and litigation in courts. Foreign investors are expected to seek redress using one of the aforementioned mechanisms. Although the principles of public international law seem to be in contention with the business interests of an investor and the host country, there has been a rapid growth and development in investment arbitration as a trade dispute resolution mechanism in the past years, and the courts in Nigeria, through her decisions, have made pronouncements regarding the disputes from foreign investments. Consequent to this, it has become critically important for investors, solicitors, professional service providers and trainers, to understand the intricate legal elements involved in the resolution of disputes involving foreign investment. This study examines the legal framework for resolution of foreign investment disputes in Nigeria. Concepts such as nationalisation and expropriation of foreign investments, stability clauses and foreign investment disputes, renegotiating and the stability of contractual agreement as well as legal infrastructure were discussed and fully analysed.
Section 165(5)(b) of the Companies Act 71 of 2008: A discussion of the requirement of good faith
Authors: Subramanien Darren
Published: February 2021

In terms of s 165(5)(b) of the Companies Act 71 of 2008, ‘the court must be satisfied that the applicant is acting in good faith’; that ‘the proceedings involve the trial of a serious question of material consequence to the company’; and that it is ‘in the best interests of the company’ that the applicant(s) be granted leave. The legislature has chosen to provide guiding criteria that are vague and general rather than detailed legal steps for the exercising of judicial discretion. It would therefore be open to the courts to provide an interpretation of the words found in s 165(5)(b) especially regarding the good faith requirement. This article discusses the requirement of good faith. The interpretation and application of the good faith requirement found in s 165(5)(b) will ultimately determine the success or failure of the new statutory derivative action as an adequate remedy for aggrieved applicants who may seek redress on the company’s behalf, if the company or those in control of it improperly fail or refuse to do so. The comparable sections in the law of the United Kingdom will be evaluated in order to determine whether it is feasible to transplant selected rules and principles into South African law.
YETİŞKİN BİREYLERDE BİLİNÇLİ FARKINDALIK İLE YAŞAM DOYUMU ARASINDAKİ İLİŞKİNİN İNCELENMESİ
Authors: GÜLER Kahraman , USLUCA Muhammed
Published: February 2021

Bu çalışma; yaşam doyumu ile bilinçli farkındalık arasındaki ilişkinin ortaya konulması ve ek olarak yaş, medeni durum, cinsiyet, öğrenim düzeyi gibi sosyodemografik özelliklerin bilinçli farkındalık ve yaşam doyumu değişkenleri üzerindeki etkisini araştırmak üzere yapılmıştır. Araştırmaya İstanbul’da yaşayan 146’sı kadın olmak üzere 18 yaş üstü toplamda 350 kişi katılım göstermiştir. Araştırmada sosyodemografik veri formu, Yaşam Doyumu Ölçeği, Bilinçli Farkındalık Ölçeği kullanılmıştır. Veri toplama araçlarının uygulanabilmesi için sosyodemografik form, Yaşam Doyumu Ölçeği ve Bilinçli Farkındalık Ölçeği; Google Formlara geçirilmiş ve basit seçkisiz yöntemle seçilmiş 18 yaş üstündeki 350 katılımcıya dağıtılmıştır. İki veya daha fazla değişken arasındaki ilişki için Pearson Korelasyon analizi uygulanmıştır. Bilinçli Farkındalığın Yaşam Doyumu üzerine etkisini analiz etmek için Çoklu Doğrusal Regresyon uygulanmıştır. İki bağımsız grup arasındaki farkın analizi için Bağımsız Örneklemler T-Testi, Çoklu gruplar arasındaki farkın analizi için Tek Yönlü Varyans Analizi(ANOVA) uygulanmıştır. Araştırma sonucunda yaşam doyumu ile bilinçli farkındalık arasında anlamlı bir ilişki elde edilmiştir. Bilinçli farkındalık ölçeği puanları, cinsiyete göre anlamlı farklılık göstermektedir. Erkeklerde kadınlara göre daha yüksek olarak bulunmuştur. Yaşam doyumu ölçeğinden alınan puanların ise; medeni durum değişkeni ve öğrenim düzeyi değişkenlerine göre farklılık gösterdiği anlaşılmıştır. Sonuçlara göre evli bireylerin bekâr bireylere göre yaşam doyumu düzeyleri daha yüksek olarak bulunmuştur.
CASE STUDIES IN WEB-CONTROLLED DEVICES AND REMOTE MANIPULATION
Authors: Sobh T. , Mihali R. , Rosca A. , Ghimire B. , Vovk K. , Gosine G. , Batra P. , Singh A. , Singh S.
Published: February 2021

The concept of distance learning has been more and more articulated during the past few years and is expected to shortly turn into a practical education system within current high level learning institutions. The chances are that distance learning would transparently extend colleges and institutes of education, and could plausibly overtake and turn into a preferred choice of higher education, especially for adult and working students. In a supportive effort towards faster distance learning implementation and consideration, we are presenting through this material a sequence of projects that have been developed at University of Bridgeport and can serve very well in the process of distance learning education ranging from simple “hobby” style training to professional guidance material. The projects have an engineering / laboratory flavor, are part of an ongoing work of the faculty and students of the Computer Science and Engineering Department of the university, and are being presented in an arbitrary order, topics ranging from vision and sensing to engineering design, scheduling, remote control and operation.
COMPUTATIONAL GRIDS TO SOLVE LARGE SCALE OPTIMIZATION PROBLEMS WITH UNCERTAIN DATA
Authors: Triki Chefi , Grandinetti Lucio
Published: February 2021

In this paper we discuss the use computational grids to solve stochastic optimization problems. These problems are generally difficult to solve and are often characterized by a high number of variables and constraints. Furthermore, for some applications it is required to achieve a real-time solution. Obtaining reasonable results is a difficult objective without the use of high performance computing. Here we present a grid-enabled path-following algorithm and we discuss some experimental results.
ОБРОБКА СИГНАЛІВ ТА МАТЕМАТИЧНЕ МОДЕЛЮВАННЯ ДИНАМІЧНИХ ОБ’ЄКТІВ ЗА ДОПОМОГОЮ ЇХ ПРЕДСТАВЛЕННЯ ЯК ДИСКРЕТНИХ ДЖЕРЕЛ ІНФОРМАЦІЇ
Authors: Муль О.В. , Сегін А.І.
Published: February 2021

Моделювання процесів в динамічних системах різної фізичної природи є важливою проблемою, яка може бути успішно вирішеною за допомогою їх представлення як дискретних джерел інформації та злиття сигналів різних сенсорів в систему візуального контролю характеристик об’єкта. Зроблено спробу об’єднати математичний апарат для опису динамічних об’єктів на основі системи диференційних рівнянь з їх описом за допомогою статистичних, кореляційних, ентропійних, логічно­статистичних моделей, що дозволить провести паралелізацію обчислювальних процедур та підвищити точність моделей.
A SELF-ORGANIZING MAP FOR MIXED CONTINUOUS AND CATEGORICAL DATA
Authors: Rogovschi Nicoleta , Lebbah Mustapha , Bennani Younès
Published: February 2021

Most traditional clustering algorithms are limited to handle data sets that contain either continuous or categorical variables. However data sets with mixed types of variables are commonly used in data mining field. In this paper we introduce a weighted self-organizing map for clustering, analysis and visualization mixed data (continuous/binary). The learning of weights and prototypes is done in a simultaneous manner assuring an optimized data clustering. More variables has a high weight, more the clustering algorithm will take into account the informations transmitted by these variables. The learning of these topological maps is combined with a weighting process of different variables by computing weights which influence the quality of clustering. We illustrate the power of this method with data sets taken from a public data set repository: a handwritten digit data set, Zoo data set and other three mixed data sets. The results show a good quality of the topological ordering and homogenous clustering.
EDUCATION INTELLIGENCE SOFTWARE AS A TOOL OF INCREASING THE EFFECTIVENESS OF CREATIVE LEARNING
Authors: Hryshachov Victor , Zamyatin Denys , Kebkalo Olexy , Mykhailiuk Anton , Ohnivchuk Lesya , Tarasenko Volodymyr
Published: February 2021

A mathematical model of learning in the way of self information-educational activity of a student is developed in his article. A method for constructing and optimizing of individual educational trajectories is proposed. The impact of the use of specialized information and analytical systems on quality scores of the learning process is analyzed. This paper introduces the concept of Education Intelligence systems and shows that their use in an education process is a powerful tool of the intensification of the training activities.
SEGMENTATION OF VESSELS IMAGES ON ANGIOGRAMS IN SPACE OF TRANSFORMATION COEFFICIENTS WITH COMMON WAVELET FUNCTIONS
Authors: Polyakova Marina
Published: February 2021

The method of vessel segmentation on angiogram is elaborated. It includes the analysis of own values of Hessian for every pixel of image. The elements of Hessian calculated from the image convolution by the common wavelet functions with a compact support. This decreases the conputational complexity of method of segmentation of angiograms due to replacement of a few levels of data processing by one.
GAME-THEORETICAL MODEL APPLICATION’S TO PLANNING AND CONTROLLING OF THE MATERIAL RESOURCES IN MINE INDUSTRY
Authors: Kałuski Jan
Published: February 2021

The game-theoretical approach to the planning and management of materials needed for the mining enterprise is presented. The hierarchical two-person game with non-zero-sum was developed and justified. For the pure strategies of two persons-players (a government and its laws from one side, and a mining enterprise from another side) a game – decision was selected in a form of the Stackelberg optimal strategies. A scenario of the proposed game has been verified on the example of real data from the coal mine.
DEVELOPMENT OF THE GUARANTEED ESTIMATION ROBUST ALGORITHM OF LINEAR CONTROLLED SYSTEM STATES
Authors: Sholokhov Aleksey V.
Published: February 2021

Ellipsoidal approximation of the ellipsoid and hyperlayer crossing has been considered as a basis of the algorithm of states estimation of the linear controlled system whose set of possible states is represented with an ellipsoid, and observations – with a hyperlayer. This representation is considered as an analogue of Kalman filter. The conditions of a priori system state and a posteriori measurement information compatibility and sensitivity of the algorithm to a choice of its parameters have been investigated. Dependence of the system state estimate improvement on a relative width of the hyperlayer of a set of observations has been shown. The obtained algorithm in comparison with the known solutions at minor degradation of accuracy is much easier in realization and stabler in operation from the standpoint of prior guesses violation.
FACE RECOGNITION SYSTEM FOR MACHINE READABLE TRAVEL DOCUMENTS
Authors: Tulyakov Sergey , Sadykhov Rauf Kh.
Published: February 2021

This paper presents an upright frontal face recognition system, aimed to recognize faces on machine readable travel documents (MRTD). The system is able to handle large image databases with high processing speed and low detection and identification errors. In order to achieve high accuracy eyes are detected in the most probable regions, which narrows search area and therefore reduces computation time. Recognition is performed with the use of eigenface approach. The paper introduces eigenface basis ranking measure, which is helpful in challenging task of creating the basis for recognition purposes. To speed up identification process we split the database into males and females using high - performance AdaBoost classifier. At the end of the paper the results of the tests in speed and accuracy are given.
RECONFIGURABLE CELL-ARRAY (RCA) BASED COMPUTER SYSTEM WITH CELL SPECIALIZATION
Authors: Bilenko Anatoliy , Sitnikov Valeriy
Published: February 2021

Reconfigurable system based on cell specialization of reconfigurable cell-array computer system is presented. Analysis of specialized reconfigurable cell-array hardware and methods of specialized cell inclusion are given.
FREQUENCY SYMBOLIC METHOD OF ASSESSMENT OF ASYMPTOTIC STABILITY OF LINEAR TIME-VARIABLE CIRCUITS
Authors: Shapovalov Yuriy , Mandziу Bohdan , Smal Dariya
Published: February 2021

The method of assessment of asymptotic stability of linear time-variable circuits by frequency symbolic approach is considered in this paper. The method consists of the replacing in criteria of stability the necessity of formation of bifrequency transfer function of circuit on the formation of a normal parametric transfer function in its inertial part. This leads to significant simplification of the method of assessment of a stability.
SPATIAL DATA PROCESSING TOOLS AND APPLICATIONS FOR BLACK SEA CATCHMENT REGION
Authors: Gorgan Dorian , Bacu Victor , Mihon Danut , Rodila Denisa , Stefanut Teodor , Abbaspour Karim , Cau Pierluigi , Giuliani Gregory , Giuliani Gregory , Ray Nicolas , Lehmann Anthony
Published: February 2021

The enviroGRIDS project has developed and provides through the BSC-OS portal a set of tools, applications and platforms concerning with the processing of huge spatial data for the Black Sea catchment region. The paper highlights the main issues of interoperability between Geospatial and Grid infrastructures, and between different platforms supporting the Earth Science oriented tools and applications. The BSC-OS portal provides end user applications for spatial data management, hydrological model calibration, environmental scenario development and execution, workflow based satellite image processing, data reporting and scenarios visualization, and development of Earth Science oriented training materials.
NOVEL CHATTERBOT SYSTEM OF ESTIMATING CURRENT USER INTERESTS BY MEANS OF WEB INFORMATION
Authors: Ueno Miki , Mori Naoki , Matsumoto Keinosuke
Published: February 2021

Human like conversation systems are one of the most important target of computer engineering. To achieve natural conversation, estimating current user interests is the essential issue. In this paper, we proposed the novel chatterbot which can estimate current user interests by means of Web information to solve above problem. In proposed chatterbot, interests are represented by interest vectors that were created by Bulletin Board System (BBS) data. To show the effectiveness of the proposed method, the computational experiments are carried out taking several BBS data as examples.
FUSION OF RECIRCULATION NEURAL NETWORKS FOR REAL-TIME NETWORK INTRUSION DETECTION AND RECOGNITION
Authors: Kachurka Pavel , Golovko Vladimir
Published: February 2021

Intrusion detection system is one of the essential security tools of modern information systems. Continuous development of new types of attacks re quires the development of intelligent approaches for intrusion detection capable to detect newest attacks. We present recirculation neural network based approach which lets to detect previously unseen attack types in real-time mode and to further correct recognition of this types. In this paper we use recirculation neural networks as an anomaly detector as well as a misuse detector, ensemble of anomaly and misuse detectors, fusion of several detectors for correct detection and recognition of attack types. The experiments held on both KDD’99 data and real network traffic data show promising results.
MODIFIED PROBABILISTIC NEURO-FUZZY NETWORK FOR TEXT DOCUMENTS PROCESSING
Authors: Bodyanskiy Yevgeniy , Pliss Irina , Volkova Valentyna
Published: February 2021

We consider the problem of text processing (classification problem) using the modification of the probabilistic neural network proposed by D. Specht. Since classes often overlap during texts processing, there were introduced the modification that implements a procedure of fuzzy inference. For this into the network were introduced two additional layers. The results of the outputs of the network are levels of belonging each text document to each of the possible classes.
REASONING UNDER UNCERTAINTY WITH BAYESIAN BELIEF NETWORKS ENHANCED WITH ROUGH SETS
Authors: Kornecki Andrew J. , Wierzchon Slawomir T. , Zalewski Janusz
Published: February 2021

The objective of this paper is to present a new approach to reasoning under uncertainty, based on the use of Bayesian belief networks (BBN’s) enhanced with rough sets. The role of rough sets is to provide additional reasoning to assist a BBN in the inference process, in cases of missing data or difficulties with assessing the values of related probabilities. The basic concepts of both theories, BBN’s and rough sets, are briefly introduced, with examples showing how they have been traditionally used to reason under uncertainty. Two case studies from the authors’ own research are discussed: one based on the evaluation of software tool quality for use in real-time safety-critical applications, and another based on assisting the decision maker in taking the right course of action, in real time, in the naval military exercise. The use of corresponding public domain software packages based on BBN’s and rough sets is outlined, and their application for real-time reasoning in processes under uncertainty is presented.
FOUNDATION FIELDBUS: FROM THEORY TO PRACTICE
Authors: Viegas Vítor , Pereira J. M. Dias
Published: February 2021

This paper describes the main characteristics of the Foundation Fieldbus (FF) technology considering both communication levels, namely H1 and H2, which have bit rates of 31.25 K and 1 00 Mbit/s, respectively. Several details about the physical layer, communication stack and user layer will be highlighted. Topics related with the configuration of instruments, as well as the design and implementation of supervision software, based on a LabVIEW interface, will be presented. A pilot plant that includes temperature, pressure, level and flow variables will be used to test and validate the capabilities of FF systems. Experimental results will be analyzed, their meaning discussed and the overall performance evaluated.
PEDESTRIAN ROBOT
Authors: Shut’ Vasilij
Published: February 2021

In the paper there are analyzes the major drawback of pedestrian crossings, namely, interruption of vehicles moving flow on the highway. It is given a calculation of economic losses in the conflict “pedestrian-vehicle” on a controlled pedestrian crossing. It is proposed a radical solution of this problem by setting the bus system “Walking Robot”, which quickly and safely move pedestrians to the opposite side of the highway with minimal disruption of a highway traffic flow.
ALGORITHMIC AND SOFTWARE IMPLEMENTATION OF E-TEXTBOOK “FUNDAMENTALS OF THEORY OF ELECTRONIC CIRCUITS”
Authors: Bobalo Yuriy , Mandziy Bogdan , Stakhiv Petro , Shakhovska Natalya
Published: February 2021

The paper presents the experience of developing electronic textbook “Fundamentals of the theory of electronic circuits”. The concept and development principles of electronic text book are discussed. The procedure of knowledge control and evaluation is described in details. The algorithm of automatic control the test tasks with possibilities of entering mathematical expressions is developed.
THE CHALLENGE OF MANAGING AND ANALYZING BIG DATA
Authors: Heßling Hermann
Published: February 2021

The amounts of data produced in science are growing exponentially. Traditional methods for storing and maintaining the enormous flood of data seem to be no longer sufficient anymore. The complexity of the data that will be distributed more and more worldwide, is going to constitute a considerable challenge for their analysis. According to Alex Szalay there soon will be produced so many data that they cannot even be stored and maintained anymore. The data have to be analyzed in real time in order to extract the relevant information. An outline of the project Large Scale Management and Analysis (LSDMA) is given. The status of our research group on distributed real-time computing is reviewed. Finally, a novel approach to time-dependent image processing based on local thermodynamical methods is presented.
E-LEARNING ENVIRONMENT FOR THE REMOTE STUDYIN MATERIAL PROPERTIES COURSES
Authors: Arras Peter , Kolot Yelizaveta , Tabunshchyk Galyna , Kozík Tomas
Published: February 2021

In this paper a newly developed e-learning environment for the support of the study on Material Properties is presented. It was developed to support the blended learning of the material and shape stiffness. Course structure is organized in HTML content, and virtual and remote laboratories are integrated in the computer aided learning module (CALM), which support both teach ers during the hand-on teaching and students during self-study.
BIG DATA TRANSFER FOR TABLET-CLASS MACHINES
Authors: Veluppillai Tevaganthan , Ortiz Brandon , Hiromoto Robert E.
Published: February 2021

Several well-known data transfer protocols are presented in a comparative study to address the issue of big data transfer for tablet-class machines. The data transfer protocols include standard Java and C++, and block-data transfers protocols that use both the Java New IO (NIO) and the Zerocopy libraries, and a block-data C++ transfer protocol. Several experiments are described and results compared against the standard Java IO and C++ (stream-based file transport protocols). The motivation for this study is the development of a client/server big data file transport protocol for tablet-class client machines that rely on the Java Remote Method Invocation (RMI) package for distributed computing.
INTEGRATION OF CLOUD COMPUTING PLATFORM TO GRID INFRASTRUCTURE
Authors: Falfushinsky Vladislav , Skarla Olena , Tulchinsky Vadim
Published: February 2021

Both grid and cloud are used to organize large scale calculations and data processing on remote computers. Grid which became a basic computing infrastructure for the Large Hadron Collider experiments provides unified technical solutions for sharing and merging distributed heterogeneous computing resources within big collaboration groups. Cloud became popular among data centers and computing service providers because of flexibility, manageability and efficient hardware utilization. Both share common ideology “computing as a service”, so one can expect additional benefits from their integration. The paper describes our approach to the integration. We propose to use cloud within grid sites for acceleration of application deployment and easy support of multiple virtual organizations by grid sites. The cloud in grid approach has been implemented and tested in Ukrainian National Grid, a part of European Grid Infrastructure.
TECHNIQUE OF CONSTRUCTION MODELS OF BEHAVIOR ALGORITHMS OF RADIO ELECTRONIC COMPLEX SYSTEM USING THE SCHEME OF PATHS METHOD
Authors: Volochiy Bohdan , Ozirkovskyi Leonid , Shkiliuk Oleksandr , Mashchak Andriy
Published: February 2021

This paper presents the technique of constructing models of behavior algorithms of radio electronic complex system using new scheme of paths method. This technique allows estimation of the efficiency indexes of RECS taking into account behavior algorithm’s features, hardware and software reliability and self-diagnostics procedures.
WAVELET SHRINKAGE ADAPTIVE HISTOGRAM EQUALIZATION FOR MEDICAL IMAGES
Authors: Megelin star Anbu , Subburaj Perumal
Published: February 2021

Enhancement techniques play a major role in medical image processing, to improve the quality of raw images. This paper proposes a novel algorithm namely wavelet shrinkage adaptive histogram equalization (WSAHE) for medical image enhancement. This algorithm consists of four stages namely, decomposition of images using wavelet transform, application of adaptive histogram equalization on the approximation coefficients, application of shrinkage on the detailed coefficients and the reconstruction of image. Experiments show that the proposed method enhances the image brightness while preserving edges.
A STRUCTURED PROCESS FOR TRANSFERRING ACADEMIC RESEARCH INTO INNOVATION PROJECTS – PIMES CASE STUDY
Authors: Wolff Carsten , Igel Burkhard , Lauschner Uwe
Published: February 2021

Academic research is promoting the free mind. The intention is to discover new findings in early phases of the innovation process. The researchers consider their creativity to be dependent on freedom and openness. Nevertheless, today’s research institutions are large and many of them conduct a business projects requiring a constant flow of projects and results. The challenge is to use professional innovation processes without destroying creativity and freedom. Ideas need to have a chance to result into a research project and scientists need to be protected from too much administration. Innovation processes for academic research need to be lean, simple, efficient and effective. This paper presents processes and tools for the early phase of transferring an innovative idea into a funding project. They are based on an IT platform which allows web based access from any place at any time. Results from the application in a research group are evaluated.
A FUZZY PAY-OFF METHOD FOR REAL OPTION VALUATION IN DETERMINATION OF MINING ENTERPRISE VALUE
Authors: Turek Marian , Sojda Adam
Published: February 2021

The article presents the use of real options in determination of mining enterprise value. The value estimation is based on discounted cash flow method. The adoption of fuzzy numbers allows introducing a risk aspect to the known method of determination of enterprise value. A classic discounted cash flow method uses one scenario on the basis of which one value is determined. The method presented is grounded on three scenarios: optimistic, the most probable, pessimistic. On this basis the values defining a fuzzy number are indicated. Algorithm of this defuzzification, based on the idea of real options enables indicating a concrete value.
ATTRIBUTE-BASED AUTHENTICATION SCHEMES: A SURVEY
Authors: Yang Huihui , Oleshchuk Vladimir
Published: February 2021

Attribute-based authentication (ABA) is a way to authenticate users via attributes which are the properties of those to be authenticated, for example, resources, contextual information (time, location, etc.) or their combination. In ABA schemes, attributes instead of identity are requested to be presented or even evidence showing that users own the required attributes is enough, so it is more flexible and privacy-preserving compared with traditional identity-based authentication. In this paper, we first explain the general structure and security requirements of ABA schemes, and then give an example to demonstrate their cryptographic construction. Next, we analyze recent work and discuss future research topics on the construction of ABA schemes, including attribute tree building, cryptographic construction, security models, hierarchy, traceability and revocation.
AN IMAGE-PROCESSING TECHNIQUE FOR GLAUCOMA DETECTION ON THE BASIS OF OPHTHALMIC IMAGES
Authors: Ben Mansour Maroua , Mlouhi Yosra , Jabri Imed , Battikh Tahar , Maalej Lotfi , Lakhoua Mohamed Najeh
Published: February 2021

In this paper, a new strategy of observation and analysis of the ophthalmologic images in order to detect the glaucoma is presented. In fact, we have treated the imagery applied to the Retina and we were able to develop some algorithm of digital image treatment, and the motif analysis techniques for the detection of the optic disc. And to do this, we have exploited the pretreatment of the image techniques such as morphological filters to improve the quality of the image and the Canny filter for the edge detection. Under the framework of the detection of circular shapes, we have opted the use of Algorithm which is the most famous detector of shapes and Hough Transform to detect the Papilla and Excavation. All these images will be applied on the fundus in order to create software illustrating some techniques of the image treatment, capable of determining precisely the relationship between the excavation diameter and the Papilla diameter which is a determining factor in the diagnosis of the Glaucoma.
BIOLOGICALLY INSPIRED FILTERS UTILIZING SPECTRAL PROPERTIES OF TOEPLITZ-BLOCK-TOEPLITZ MATRICES
Authors: Vidacic Dragan , Messner Richard A.
Published: February 2021

The construction of filters arising from linear neural networks with feed-backward excitatory-inhibitory connections is presented. Spatially invariant coupling between neurons and the distribution of neuron-receptor units in the form of a uniform square grid yield the TBT (Toeplitz-Block-Toeplitz) connection matrix. Utilizing the relationship between spectral properties of such matrices and their generating functions, the method for construction of recurrent linear networks is addressed. By appropriately bounding the generating function, the connection matrix eigenvalues are kept in the desired range allowing for large matrix inverse to be approximated by a convergent power series. Instead of matrix inversion, the single pass convolution with the filter obtained from the network connection weights is applied when solving the network. For the case of inter-neuron coupling in the form of a function that is expandable in a Fourier series in polar angle, the network response filter is shown to be steerable.
CELLULAR AUTOMATA MODELING OF IMPURITIES SEGREGATION IN THE MELT CRYSTALLIZATION PROCESS
Authors: Shumylyak Liliya , Zhikharevich Vladimir , Ostapov Sergey
Published: February 2021

The paper deals with the issue of the construction of a cellular automata model of the directional crystallization of binary solutions process. The basic approach and general methodology for the development of cellular automata models are examined. This allowed to obtain the spatial distribution of the studied characteristics. The paper gives an overview of available techniques on the problem, outlines the arguments in favor of a cellular automata method. The occurring processes of redistribution of impurities concentration and overcooling are emphasized. Previously known idea of a mechanism of the melt concentration overcooling is considered. The results of the calculation of impurity concentration distribution along the track of the sample during crystallization are presented. Dependence of the phase transition melting temperature on the value of the impurity concentration is determined on the basis of the calculated impurity distribution. Graphic examples of the varieties of uneven impurity distribution as a result of overcooling concentration of the melt are given.
IMPROVING SUPPORT ESTIMATES BY FUSION OF PRE-ELECTION DATA
Authors: Sirola Miki , Talonen Jaakko , Sulkava Mika
Published: February 2021

In this paper, Gallup results and a questionnaire in the context of a voting advice application related to the Finnish presidential election are combined. The main emphasis is on preprocessing phases where raw data is reformed to temporal data sets. We also pay attention to find optimized parameters for a merged recursive model. Aggregated data from a questionnaire was stored frequently and modified by a differential equation. The method presented in this paper allows us to visualize more accurately the daily support of each candidate before the election. The results can be used for further research such as forecasting the results and the success of presidential campaigns.
COMPUTING UNCERTAINTY OF THE EXTREME VALUES IN RANDOM SAMPLES
Authors: Dorozhovets Mykhaylo , Bubela Ivanna
Published: February 2021

This paper proposes and analyses a statistical method for uncertainty evaluation of extreme values (minimal or maximal) for measurement results with significantly limited number of observations n = 3…10 and considerable deviation of observation probability density function (PDF) from normal distribution. The method is based on properties of order statistics. It can be used for the uncertainty evaluation of mechanical properties of testing products in a food industry (when minimal values of measurement results are observed) and for the investigation of a number of harmful elements (when maximal values of measurement results are observed).
THE METHODS OF ARTIFICIAL INTELLIGENCE FOR MALICIOUS APPLICATIONS DETECTION IN ANDROID OS
Authors: Bezobrazov Sergei , Sachenko Anatoly , Komar Myroslav , Rubanau Vladimir
Published: February 2021

This paper presents and discusses a method for Android’s applications classification with the purpose of malware detection. Based on the application of an Artificial Immune System and Artificial Neural Networks we propose the “antivirus” system especially for Android system that can detect and block undesirable and malicious applications. This system can be characterized by self-adaption and self-evolution and can detect even unknown and previously unseen malicious applications. The proposed system is the part of our team’s big project named “Intelligent Cyber Defense System” that includes malware detection and classification module, intrusions detection and classification module, cloud security module and personal cryptography module. This paper contains the extended research that was presented during the IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS’2015) [1].
FAST MEDICAL DIAGNOSTICS USING AUTOASSOCIATIVE NEURO-FUZZY MEMORY
Authors: Perova Iryna , Bodyanskiy Yevgeniy
Published: February 2021

This paper proposes an architecture of fast medical diagnostics system based on autoassociative neuro-fuzzy memory. The architecture of proposed system is close to traditional Takagi-Sugeno-Kang neuro-fuzzy system, but it is based on other principles. This system contains of recording subsystem and pattern retrieval subsystem, where diagnostics of patients with unknown diagnoses is realized. Level of memberships for all other possible diagnoses from recording subsystem is determined too. System tuning is based on lazy learning procedure and “neurons in data points” principle and uses bell-shaped fuzzy basis functions. Number of these functions changes during training process using principles of evolving connectionist systems. Bell-shaped membership functions centers can be tuned using proposed algorithm, processes of accumulation patients in fundamental memory and patients retrieval are described. This hybrid neuro-fuzzy associative memory combines advantages of fuzzy inference systems, artificial neural networks and evolving systems and its using provides the increasing of autoassociative memories capacity without essential complication of its architecture for medical diagnostics tasks.
A LOW ENERGY CONSUMPTION SMART ANTENNA ADAPTIVE ARRAY SYSTEM FOR MOBILE AD HOC NETWORKS
Authors: Inzillo Vincenzo , De Rango Floriano , Ariza Quintana Alfonso
Published: February 2021

Smart Antenna Systems (SAS) are largely employed in wireless networks for their capabilities to provide very high performances with respect to omnidirectional antennas. The use of adaptive array Smart Antenna could bring to enhance aspects such as energy management, especially in Mobile Ad Hoc Network (MANET), when the network performance closely depends on the battery life of the mobile nodes as well as on the routing protocol features. In this paper, we propose a new adaptive array Smart Antenna System that improves some Ad Hoc Distance Vector (AODV) network protocol features through a mechanism of energy consumption optimization. The system implements the Least Mean Square (LMS) as adaptive algorithm; for this purpose, we perform a co-simulation between Matlab, that implements the LMS algorithm and Omnet++, that provides a complete simulation environment for MANET.
OBSERVATIONS-BASED COMPUTATIONAL ANALYTICS ON LOCAL CLIMATE DYNAMICS. PART 2: SEASONALITY
Authors: Kolokolov Yury , Monovskaya Anna
Published: February 2021

The paper continues the discussion concerning the computational decision making on evolution of local climate dynamics taking into account inevitable nonlinear nature of such systems and deficiency of reliable data on its dynamics. Here we focus on seasonality in the context of bifurcation phenomena described by the model of the hysteresis regulator with double synchronization (so-called HDS-model). From this conception, the method of structuring and analysis of meteorological data (method of relative scales) is proposed, where new useful information on local seasonal evolution becomes available. First of all, it concerns increase in analytical resolution (daily description in a climate scale). The key procedures of this method provide building the specialized seasonal structures in relative time scales. Advantages are illustrated in comparison with the traditional processing the time series of temperature observations on daily mean surface air temperature over last century. We believe that the results could be interesting in order to increase the confidence of estimations on coming climate changes.
TRIANGULATING A REGION BETWEEN ARBITRARY POLYGONS
Authors: Tereshchenko Vasyl , Tereshchenko Yaroslav
Published: February 2021

The paper presents an optimal algorithm for triangulating a region between arbitrary polygons on the plane with time complexity O(N log⁡N ). An efficient algorithm is received by reducing the problem to the triangulation of simple polygons with holes. A simple polygon with holes is triangulated using the method of monotone chains and keeping overall design of the algorithm simple. The problem is solved in two stages. In the first stage a convex hull for m polygons is constructed by Graham’s method. As a result, a simple polygon with holes is received. Thus, the problem of triangulating a region between arbitrary polygons is reduced to the triangulation of a simple polygon with holes. In the next stage the simple polygon with holes is triangulated using an approach based on procedure of splitting polygon onto monotone polygons using the method of chains [15]. An efficient triangulating algorithm is received. The proposed algorithm is characterized by a very simple implementation, and the elements (triangles) of the resulting triangulation can be presented in the form of simple and fast data structure: a tree of triangles [17].
CONTRAST ENHANCEMENT FOR COLOR IMAGES USING AN ADJUSTABLE CONTRAST STRETCHING TECHNIQUE
Authors: Al-Ameen Zohair
Published: February 2021

With the growing demand for high-quality color images, efficient yet low-complexity methods are increasingly needed for better visualization. Unfortunately, the low-contrast is one prevalent effect that degrades color images due to various unavoidable limitations. Hence, a new adjustable contrast stretching technique is proposed in this article to improve the contrast of color images. The processing scheme of the proposed technique is relatively simple. It starts by converting the input color image to grayscale. Then, it automatically computes two contrast tuning parameters depending on the pre-determined grayscale image. Finally, it improves the contrast of the degraded color image using an amended version of an existing contrast stretching technique. Accordingly, its input is a color image and a contrast adjustment parameter δ, while its output is a contrast-adjusted color image. The proposed technique is tested by conducting intensive experiments on real-degraded images, and it is compared with four well-known contrast enhancement techniques. In addition, the proposed and comparative techniques are evaluated based on three eminent no-reference image quality assessment metrics. From the performance analysis of the achieved experiments and comparisons, the proposed technique provided satisfying performances and outperformed the comparative techniques in terms of recorded accuracy and perceived quality.
A METHOD OF PREDICTING THE MAINTENANCE PERIOD OF EMBEDDED SYSTEMS FOR PREVENTING BREACH OF THEIR TIME REQUIREMENTS
Authors: Fedasyuk Dmytro , Marusenkova Tetyana , Chopey Ratybor
Published: February 2021

The work deals with a significant problem of ensuring that the execution time of a firmware running inside a microcontroller-based real-time embedded system never goes out of its expected range, no matter for how long the embedded system has been used. Once having been tested before the first usage, a newly created embedded system is gradually getting slower in its response, due to the fact that its hardware components get worn-out with aging. A possible solution is a replacement of the hardware components that most contribute to such a change in the response time of the embedded system. If such a replacement takes place too far in advance, long before hardware components actually start showing any decline in their response time, the above-mentioned solution is cost-ineffective and impractical, as it leads to a waste of equipment and efforts. We introduce a method for predicting the appropriate maintenance period of a real-time embedded system on the basis of the characteristics of its hardware components.
OPINION TARGET EXTRACTION WITH SENTIMENT ANALYSIS
Authors: Bhatia Surbhi , Sharma Manisha , Bhatia Komal Kumar , Das Pragyaditya
Published: February 2021

Social networks have increased their demand extensively for mining texts. Opinions are used to express views and reviews are used to provide information about how a product is perceived. The reviews available online can be available in thousands, so making the right decision to select a product becomes a very tedious task. Several research works has been proposed in the past but they were limited to certain issues discussed in this paper. A dynamic system is proposed based on the features using ontology followed with classification. Classifying information from such text is highly challenging. We propose a novel method of extracting aspects using ontology and further categorizing these sentiments into positive, negative and neutral category using supervised leaning technique. Opinion Mining is a natural language processing task that mine information from various text forums and classify them on the basis of their polarity as positive, negative or neutral. In this paper, we demonstrate machine learning algorithms using WEKA tool and efficiency is evaluated using information retrieval search strategies.
CREATING AN INTERACTIVE MUSICAL EXPERIENCE FOR A CONCERT HALL
Authors: Antoshchuk Svitlana , Kovalenko Mykyta , Sieck Jürgen
Published: February 2021

In this paper we introduce a Kinect based posture recognition approach that can classify the user’s pose and gesture and match them to a set of predefined musical instruments. The efficiency of the approach is then demonstrated using two applications. The Virtual Orchestra system uses pose- and gesture-recognition along with Augmented Reality technology to add a virtual musical instrument into the scene, both visually and audibly: the visual representation of the instrument is placed into the user’s hands and the sound of the corresponding instrument is played. An additional functionality is that the user can control the intensity and the pitch of the sound by changing the speed of his hand or finger movements. The Magic Mirror game is the second application developed for the Berlin Concert Hall that uses the posture recognition approach to introduce the visitors to some classical music pieces and familiarize them with various classical musical instruments.
IMPLEMENTING BI-TEMPORAL PROPERTIES INTO VARIOUS NOSQL DATABASE CATEGORIES
Authors: Eshtay Mohammed , Sleit Azzam , Aldwairi Monther
Published: February 2021

NoSQL database systems have emerged and developed at an accelerating rate in the last years. Attractive properties such as scalability and performance, which are needed by many applications today, contributed to their increasing popularity. Time is very important aspect in many applications. Many NoSQL database systems do not offer built in management for temporal properties. In this paper, we discuss how we can embed temporal properties in NoSQL databases. We review and differentiate between the most popular NoSQL stores. Moreover, we propose various solutions to modify data models for embedding bitemporal properties in two of the most popular categories of NoSQL databases (Key-value stores and Column stores). In addition, we give examples of how to represent bitemporal properties using Redis Key-value store and Cassandra column oriented store. This work can be used as basis for designing and implementing temporal operators and temporal data management in NoSQL databases.
POWER-CONSUMPTION-ORIENTED CHECKABILITY FOR FPGA-BASED COMPONENTS OF SAFETY-RELATED SYSTEMS
Authors: Drozd Oleksandr , Antoniuk Viktor , Drozd Miroslav , Karpinskyi Volodymyr , Bykovyy Pavlo
Published: February 2021

This paper is dedicated to the problem of the circuit checkability of components in the safety-related systems, which operate objects of the increased risk and are aimed at ensuring safety of both a system and a control object for accident prevention and a decrease in their consequences. Importance of the checkability of the circuits for ensuring safety in critical applications is emphasized as safety is based on the use of fault tolerant circuitry decisions and their efficiency is defined by the circuit checkability. Development of a logical checkability from testability to structurally functional and dual-mode model which formalizes a problem of the hidden faults and defines ways of its solution is shown. The limitation of a logical checkability in detection of faults in chains of the common signals and the need for development of checkability out of the limits of a logical form, including suitability to checking the circuits on the basis of their power consumption is considered. Power-consumption-oriented checkability (Power-checkability) allowing detection of faults in chains of the common signals is defined. Its analytical assessment for the circuits implemented in FPGA is offered. Experiments providing estimation of power-checkability for FPGA-implementation of iterative array multipliers with various activities of input signals are carried out.