bluuebunny/crossref_metadata_2025 huggingface dataset:
Measurement of Some Climatic Parameter in Babylon Governorate by Statistical and Mathematical Methods
Authors: Mahmood Mahmood
Published: February 2021

Evaporation transpiration is one of the most important results in the water balance equation for any natural area or water body, and it is also a critical component of the hydrological cycle. The relationship between temperature and transpiration was obtained using the Thornthwaite method in three stations along with Babylon Governorate. The data for the three meteorological stations were taken for 10 years. The value of climate change was obtained within the study area, including temperature, evaporation, humidity, and rainfall. The value of potential evapotranspiration was calculated by the Thornthwaite method, and the highest value was obtained in July (421.9), and the lowest value in January (3.66). Also, the increase in water was calculated for a study area. It appeared that the increase in evapotranspiration and decrease was in direct relationship with the temperature intensity of the study area.
OWNERSHIP STRUCTURES, INVESTORS CONFIDENCE AND FINANCIAL DECISIONS IN FAMILY FIRMS: EVIDENCE FROM GCC MARKETS
Authors:   Institute of Management Sciences, BZU Multan, Shahid Muhammad Sadiq
Published: February 2021

The objective of this study is to examine the impact of financial decisions on the ownership structure. This study adopted two themes of ownership structure (e.g., 25% & 50%) that categorized the family-owned firms (FOF) and non-family firms (NFOF). The data was collected from 286 firms listed at GCC stock exchanges annual reports, stock exchange database, and Data Stream that range from 2010-2016 periods. The findings of this study showed that the FOFs have lesser investment-internal fund sensitivity than NFOFs. Though, there is an insignificant effect of the block holder on investment funds sensitivity. However, the little implication of dividend payout in FOFs as compare to NFOFs was disclosed in the results. Moreover, it wrapped up that there are less agency problems and information asymmetry in FOFs comparatively.
Problem and Challenges Faced by Students, Parents, and Teachers in Google Classes & Television Lessons
Authors: Dorji Tshewang
Published: February 2021

The qualitative study was carried out under Thimphu Thromde, Bhutan, to assess the use of Google class and Television lessons during the emergence of COVID-19 in the 2020 academic year. The study used Google class & Television lesson observations to gain the first-hand experience and face-to-face interviews with students, parents, and teachers to get in-depth views. The Google class and television lesson observation and interview data were analyzed using emerging themes. The findings revealed that Google class and Television lessons played an essential role in making up lessons lost during schools' closure. However, the study further revealed some pertinent issues related to the Google class and Television lessons, including students resorting to copying assignments and homework directly from friends or copying directly from textbooks and the internet. Students were overburden by the heavy load of assignments assigned by different subject teachers, among many others. More preparedness and training for teachers in ICT based pedagogy was required. The study might draw policy attention to consider the problem and challenges before implementing Google class and Television lessons shortly to avoid pitfalls. The study was limited to the Thimphu Thromde, Bhutan, using a small sample size of students, parents, and teachers. A future mixed-method research approach uses surveys with students, parents, and teachers; focus group discussions with students, parents, and teachers; and policymakers' interviews are recommended.
Clinical Evaluation of the Efficacy of Bovine Amniotic Fluid on Healing of Experimental Corneal Defects in Rabbits
Authors: SAĞLIYAN Aydın , ŞAHİN Merve , GÜNAY Cihan , DURMUŞ Ali Said , POLAT Eren
Published: February 2021

This study was conducted to investigate the effectiveness of amniotic fluid in defects in the epithelial tissue of the cornea. In the study, 14 New Zealand rabbits, which were experimentally created with a 3 mm diameter full-thickness defect in the corneal epithelium, were used. After the rabbits were randomly divided into two groups, amniotic fluid was applied to the rabbits in the first group (AF) and saline solution was applied to the rabbits in the second group (CG) three times a day for 20 days. Clinical examinations and tests were performed on the 7th, 14th, and 20th days of the study and the condition of the corneal defects was photographed. Clinical examinations revealed that tear break-up time (TBTT), fluorescein staining, rose bengal staining, corneal turbidity, and corneal vascularization were better in the AF group than in the CG group. As a result, it is concluded that amniotic fluid is effective in corneal epithelial defects and it would be beneficial to use it in addition to medical or operative treatment.
Coping with the Covid-19 pandemic: A comparative study of the capabilities of the Kenyan and Nigerian insolvency frameworks
Authors: Iheme Williams C , Mba Sanford U
Published: February 2021

The Covid-19 pandemic has undeniably ravaged the global economy and plunged many countries in Africa, including Kenya and Nigeria into an economic recession. This article departs from the premise that credit is the lifeblood of market systems. Accordingly, the credit and insolvency laws of both countries must be adjusted in certain ways during and after the pandemic, in order to enable them to cope with the dire economic challenges resulting from the pandemic. The article identifies some material defects in the Insolvency Act 2015 (Kenya) and the Companies and Allied Matters Act 2020 (Nigeria), and argues that these defects will debilitate a meaningful economic recovery from the pandemic. The paper shows the lack of suitability of their existing insolvency frameworks, as well as some aspects of the public law: it proposes a number of tailor-made recommendations that benefitted from the experiences of certain other common law jurisdictions.
K-Means Algorithm For Clustering Poverty Data in Bangka Belitung Island Province
Authors: Sugianto Castaka Agus , Bokings Tri Pratiwi Olivia Riska
Published: February 2021

The Central Bureau of Statistics is a non-ministerial government institution that reports directly to the President. Based on data from The Central Bureau of Statistics in September 2019, the wealth rate in Indonesia was 9.22% and the number of indigent people in Indonesia reached 24.79 million. The poverty rate in the Bangka Belitung Islands Province was low compared to the national level. This is evidenced by 4.62% of people in Bangka Belitung Island Province were indigent people, which is lower than the national average of 9.22%. The data mining techniques using the K-Means Clustering method are used for this study. The research data was taken from the website of the BPS from 2014-2019 which consisted of 7 districts and/or cities with 3 variables. The variables used are the number of indigent people (in thousands), the average length of school education (years), and adjusted per capita expenditure (thousand rupiahs/year). All data is processed by Rapidminer and 3 clusters are carried out, namely: medium cluster level 0, high cluster level 1, and low cluster level 2. Cluster 0 contains districts/cities whose people have the longest average school time, high per capita expenditure, and a large number of indigent people. Cluster 1 contains districts/cities whose people have a short average school time, low per capita expenditure, a moderate number of indigent people. Cluster 2 contains districts/cities whose people have an average school time, moderate per capita expenditure, a small number of indigent people. Based on the result, the government can prioritize Kabupaten Bangka, Kabupaten Bangka Barat, Kabupaten Bangka Selatan in assisting, especially in the cost of education scholarships and social funds as well as other infrastructure improvements for the welfare of the inhabitants of Bangka Belitung Islands Province.
STEGANOGRAPHY EFFECTS IN VARIOUS FORMATS OF IMAGES. A PRELIMINARY STUDY
Authors: Mastronardi Giuseppe , Castellano Marcello , Marino Francescomaria
Published: February 2021

In this paper the effects of steganography in different image formats (BMP, GIF, JPEG and DWTcoded) are studied. With respect to these formats, we try to give an answer to the following questions: 'how many bits of noise (i.e. the textual secret message) can be injected without perceptually deteriorating the quality of the image?' and 'how and where to inject these bits in order to achieve the best tradeoff in terms of length of the textual message and preserved quality of the image?'
MONITORING OF THE HEAT TRANSFER IN BUILDINGS
Authors: Lipnik Gorazd , Matko Vojko
Published: February 2021

In paper is introduced measurement method for monitoring of temperatures on big objects. Measurement equipment used in method and results on known object are also introduced. When temperatures are monitored for a long period of time (at least 14 days), the lost of heat, quality of isolation and quality of heat regulation can be estimated.
ІНФОРМАЦІЙНО-АНАЛІТИЧНА СИСТЕМА СУПРОВОДУ ФІНАНСОВО-КРЕДИТНОЇ ДІЯЛЬНОСТІ: МОДЕЛІ БАЗОВИХ ТА ВАЛЮТНИХ КРЕДИТІВ
Authors: Марецька Е.
Published: February 2021

Запропоновано математичні моделі консолідації кредитів, що сплачуються у повних внесках. Розроблені моделі в раховують різноманітні способи нарахування процентів: простий чи складний, постійну чи змінну процентні ставки. Створений математичний апарат дає можливість порівнювати кошти кредитів, знаходити оптимальні умови надання кредитів.
WEB BASED VIRTUAL ROBOT PROTOTYPING AND MANUFACTURING
Authors: Mihali Raul , Sobh Tarek , Koval Vasyl , Korkishko Tymur , Sachenko Anatoly , Kochan Volodymyr
Published: February 2021

Developing an environment that enables optimal and flexible design of robot manipulators using universal reconfigurable links, joints, controllers, actuators and sensors is an essential step for efficient robot design and prototyping. Robot control has to be made by a universal controller with remote hardware and software reconfigurations. This technique allows to create an optimal configuration of software and hardware components for designing of the specialized robot, its algorithmic control and rapid prototyping.
MULTI-SITE PRODUCT CONFIGURATION OF TELECOMMUNICATION SWITCHES
Authors: Felfernig Alexander , Friedrich Gerhard , Jannach Dietmar , Russ Christian , Zanker Markus
Published: February 2021

Knowledge­based product configurators support their users in tailoring configurable products according to their specific demands and these systems have been successfully applied in many industrial sectors over the last decades. However, within today’s networked economy, the complex solutions of fered to the customers are in many cases assembled from configurable sub­products themselves. Within this paper we describe a business case where due to organisational and confidentiality reasons a single­configurator approach is not applicable and several configurators along the supply chain must cooperate in finding correct product configurations and in presenting them to an online customer. We present an algorithm based on Constraint Satisfaction that takes the specific characteristics of the problem domain into account and compare our approach to other work in the field of Distributed Problem Solving. The implementation framework for distributed configuration which is currently developed in the EU­funded project CAWICOMS1 is discussed in the final sections.
IS ARTIFICIAL NEURAL NETWORK INTELLIGENT?
Authors: Imada Akira
Published: February 2021

This article was originally written for the purpose of breaking the ice in the round table discussion held in the conference. Since the name of the conference is ‘Neural Network and Artificial Intelligence’ the topic of this article is, “What is intelligence?” when we talk about artificial intelligence in general, and artificial neural network in particular. In the history of the field of artificial intelligence, we have had many arguments claiming that artificial intelligence was not intelligent enough yet, or would not be possible to be intelligent even in the future. We take a brief look at such arguments in the history, and then try a speculation concerning if a machine intelligence is as flexible as human intelligence or not. Some experiments of path-finding, with spiking neurons, from this point of view are shown. These were discussed in the roundtable discussion. Here, in this special issue, additionally one thought-experiment using a quantum random walk is discussed. Then a further consideration on a role of consciousness for a machine to be intelligent is followed.
MODEL OF SEMANTIC CONTEXT OF LEXEMES IN THE TEXT MINING ALGORITHMS
Authors: Pavlyshenko Bohdan M.
Published: February 2021

The model of semantic context of lexemes which represent the structure semantic configuration of lexems corpus of text arrays has been proposed. It is shown that partially ordered set of semantic concepts are formed in the lexem semantic context. Concepts’ intents are defined by semantic fields, concepts extents – by lexems.
METHOD OF ENVIRONMENT RECONSTRUCTION USING EPIPOLAR IMAGES
Authors: Koval Vasyl , Adamiv Oleh , Sachenko Anatoly , Kapura Viktor , Roth Hubert
Published: February 2021

In this paper the method for 3D Environment reconstruction usingepipolar images is presented. Method allows to fuse stereoimages within certain time depending on acceptable computational resources
THE MODEL OF DATA PRESENTATI ON WITH FUZZY PORTRAITS FOR PATTERN RECOGNITION
Authors: Maksimova Aleksandra
Published: February 2021

This paper deals with a data presentation model based on fuzzy portraits. The fuzzy portraits are formed by integral characteristics of pattern classes. It is the basis for fuzzy classifier construction. It is determined that further division of some classes of images into clusters increases the quality of pattern recognition algorithm. The main idea of fuzzy clustering for fuzzy portraits creating and problem of adequate fuzzy partition choice is considered. The paper provides the stages of fuzzy production knowledge base construction on the basis of fuzzy portraits. The local validity measure for fuzzy portrait is defined. The problem of identification in chemical and food industries is considered as an application of this approach.
THE ART AND SCIENCE OF GPU AND MULTI-CORE PROGRAMMING
Authors: Hiromoto Robert E.
Published: February 2021

This paper examines the computational programming issues that arise from the introduction of GPUs and multi-core computer systems. The discussions and analyses examine the implication of two principles (spatial and temporal locality) that provide useful metrics to guide programmers in designing and implementing efficient sequential and parallel application programs. Spatial and temporal locality represents a science of information flow and is relevant in the development of highly efficient computational programs. The art of high performance programming is to take combinations of these principles an d unravel the bottlenecks and latencies as sociate with the architecture for each manufacturer computer system, and develop appropriate coding and/or task scheduling schemes to mitigate or eliminate these latencies.
USE OF ARTIFICIAL INTELLIGENCE TECHNIQUES FOR PROGNOSTICS: NEW APPLICATION OF ROUGH SETS
Authors: Zalewski Janusz , Wojcik Zbigniew
Published: February 2021

The objective of this paper is to set the context for the potential application of rough sets in prognostics. Prognostics is a field of engineering, which deals with predicting faults and failures in technical systems. Engineering solutions to respective problems embrace the use of multiple Artificial Intelligence (AI) techniques. The authors, first, review selected AI techniques used in prognostics and then propose the application of rough sets to build the system health prognostication model.
EXTRACTION OF LEFT VENTRICULAR CONTOURS FROM VENTRICULOGRAMS WITH LABELING OF IMAGE PIXELS BY ACTIVE CONTOURS
Authors: Polyakova Marina
Published: February 2021

The method of the extraction of left ventricular contours is developed for ventriculograms which obtained by radiological research of heart with the angiographic system. The proposed method includes the underlining of left ventricular contours through the repagular wavelet transform and labeling the pixels of image by active contours that reduced the error of detection of the edge and the area of left ventricle.
ANFIS AND NEURAL NETWORK BASED FACIAL EXPRESSION RECOGNITION USING CURVELET FEATURES
Authors: Khandait S.P. , Thool R.C. , Khandait P.D
Published: February 2021

Curvelet transform is a promising tool for multi-resolution analysis on images. This paper explains a new approach for facial expression recognition based on curvelet features extracted using curvelet transform. Curvelet transform is applied on the database images and curvelet coefficients are obtained for selected scale for image analysis. Facial curvelet features are compressed using singular value decomposition (SVD) approach. Back propagation neural network (BPNN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are used as classifiers for classifying expressions into one of the seven categories like angry, disgust, fear, happy, neutral, sad and surprise. Experimentation is carried out on JAFFE database. The experimental results show that the novel approach is a better option for extracting feature values and classifying facial expressions.
DEVELOPING SEMANTIC NETWORK MANAGEMENT SYSTEM
Authors: Semchyshyn Yuriy , Kulpa Ivan , Kolosovskyi Igor , Hrechnikov Oleksandr , Hayda Petro
Published: February 2021

The paper considers semantic networks. It is a way of representing knowledge as a set of nodes-concepts connected by edges-relations. The history and current state-of-the-art of semantic networks is analyzed. The experience of designing and developing semantic network management system is described in four sections covering the following topics: data structures design, semantic analysis algorithm implementation, graph visualization methods selection and Web-based user interface development. The developed system is fully-operational tool for building and studying semantic networks. The system will be used for the further research.
THE GENERALIZED CONSTRUCTION OF PSEUDONONDETERMINISTIC HASHING
Authors: Luzhetsky Volodymyr , Baryshev Yuriy
Published: February 2021

This article is devoted to the development of hash constructions, which are based on the pseudonondeterministic hash conception. The conception allows to design hash functions with improved infeasibility to cryptanalysis. Both proposed constructions and known ones are generalized as pseudonondeterministic constructions.
ОПТИМАЛЬНИЙ СИНТЕЗ ЗВОРОТНИХ КВАНТОВИХ СУМАТОРІВ З ДОПОМОГОЮ ГЕНЕТИЧНИХ АЛГОРИТМІВ
Authors: Дейбук Віталій , Грицку Іон
Published: February 2021

У роботі запропоновано новий спосіб кодування хромосом у генетичному алгоритмі для моделювання схем зворотних повних однорозрядних суматорів з функцією транзиту у базисі елементів Фредкіна. Отримані з допомогою такого підходу схеми мають кращі параметри затримки та кількості зайвих виходів (входів) порівняно з відомими аналогами, що демонструє ефективність та застосовність такого підходу.
SELF-ORGANIZING NEURAL GROVE: EFFICIENT NEURAL NETWORK ENSEMBLES USING PRUNED SELF-GENERATIONG NEURAL TREES
Authors: Inoue Hirotaka , Sugiyama Kyoshiro
Published: February 2021

R ecently, mul tiple classifier systems have been used for practical applications to improve classification accuracy. Self-generating neural networks are one of the most suitable base-classifiers for multiple classifier systems because of their simple settings and fast learning ability. However, the computation cost of the multiple classifier system based on self-generating neural networks increases in proportion to the numbers of self-gene rating neural networks. In this paper, w e propose a novel prunin g method for efficient classification and we call this model a self-organizing neural grove. Experiments have been conducted to compare the self-organizing neural grove with bagging and the self-organizing neural grove with boosting, and support vector machine. The results show that the self-organizing neural grove can improve its classification accuracy as well as reducing the computation cost.
COMPREHENSIVE MULTILEVEL SECURITY RISK ASSESSMENT OF DISTRIBUTED INFORMATION SYSTEMS
Authors: Kotenko Igor , Doynikova Elena
Published: February 2021

The paper suggests the multilevel approach to the risk assessment that is based on the system of security metrics and techniques for their calculation. Proposed techniques are based on attack graphs and service dependencies. They allow evaluating security of network topologies, malefactors and attack characteristics, and integral security properties and characteristics calculated on the basis of the cost-benefit and zero-day vulnerability analysis. Classification of these characteristics and separation of the security information on static, dynamic and historical allows defining different assessment levels. The paper considers the main issues and recommendations for using the risk assessment techniques based on the suggested approach.
TOOLS FOR BIOMEDICAL DATA ARCHIVING IN UKRAINIAN GRID INFRASTRUCTURE
Authors: Sudakov Oleksandr , Salnikov Andrii , Sliusar Ievgen , Boretskyi Oleksandr
Published: February 2021

Tools for archiving and extraction of data in Ukrainian National Grid for end-users’ applications are proposed, implemented and deployed for practical applications in medical imaging, non-linear dynamics, and molecular biology. Proposed tools provide the facilities to utilize large distributed storage space in grid infrastructures for different practical tasks including desktop applications. Tools may be successfully used even when on client platforms it is impossible to setup grid middleware, use web browser interfaces or grid security infrastructure authentication. Tools consist of extensible client compatible with different software and hardware platforms; web service for data transfer; web service for transparent data replication on grid storage elements.
VECTOR CLOCK TRACING AND MODEL BASED PARTITIONING FOR DISTRIBUTED EMBEDDED SYSTEMS
Authors: Hoettger Robert , Igel Burkhard , Kamsties Erik
Published: February 2021

Tracking, partitioning and tracing in modern dynamic high performance computing systems are three of the most innovative and important development aspects for performance optimization purposes and state-of-the-art advanced quality. This paper discusses these three aspects with respect to distributed systems and proposes new mechanisms for an advanced utilization of software in this domain. We present a specific tracking mechanism via vector clocks for model and code partitioning purposes and the determination of causality relations. Further, a tracing approach for an effective analysis and thereby utilization of code and the corresponding architecture is introduced. The combination of both approaches leads to a high degree of parallelism and a fine-grained structure of execution units, that further traced, supports a precise analysis of synchronous and asynchronous system’s behavior as well as an optimal load balancing. The mechanisms are introduced with respect to a model based control engineering tool and event diagrams.
USE OF A COST-EFFECTIVE NEUROHEADSET EMOTIV EPOC FOR PATTERN RECOGNITION PURPOSES
Authors: Kawala-Janik Aleksandra , Baranowski Jerzy , Podpora Michal , Piatek Pawel , Pelc Mariusz
Published: February 2021

Application of biomedical signals for the control purposes is currently growing interest of research society. Various biomedical signals enable various control prospects. In this paper application domain of using electroencephalographic signals obtained from an inexpensive Emotiv EPOC headset was described. It is also important to mention the possible implementation of the proposed method on an embedded platform, as it causes some significant limitations due to the little efficiency and low computing power of an embedded system platform. The proposed method enables to extend future application of the BCI system presented in this paper and it also gives more testing flexibility, as the platform can simulate various external environments. It is crucial to mention, that no filtering was done and that the traditional, statistical signal processing methods were in this work neither used, nor described.
STUDY OF TWO 3D FACE REPRESENTATION ALGORITHMS USING RANGE IMAGE AND CURVATURE-BASED REPRESENTATIONS
Authors: Manolova Agata , Tonchev Krasimir
Published: February 2021

In this paper we present a comparative analysis of two algorithms for image representation with application to recognition of 3D face scans with the presence of facial expressions. We begin with processing of the input point cloud based on curvature analysis and range image representation to achieve a unique representation of the face features. Then, subspace projection using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) is performed. Finally classification with different classifiers will be performed over the 3D face scans dataset with 61 subject with 7 scans per subject (427 scans), namely two "frontal", one "look-up", one "look-down", one "smile", one "laugh", one "random expression". The experimental results show a high recognition rate for the chosen database. They demonstrate the effectiveness of the proposed 3D image representations and subspace projection for 3D face recognition.
DESIGN OF THE FUZZY CONTROL SYSTEM FOR THE WASTE HEAT UTILIZATION PLANTS DRIVEN BY THE THERMOACOUSTIC ENGINE
Authors: Kondratenko Yuriy , Korobko Volodymyr , Korobko Oleksiy , Moskovko Oleksiy
Published: February 2021

The paper addresses the synthesis of fuzzy controllers for computerized control system of the waste heat energy (WHE) utilization plants that operate with the thermoacoustic engine (TAE). Based on the analysis of existing systems, the authors present the main tasks of the synthesized control system, describe its structure and main components. Created system is then tested on the experimental thermoacoustic installation. Using the data obtained authors synthesize the mathematical model of thermoacoustic plant and describe the methodology of its control by the adjustments in resonator length of thermoacoustic device. Using the suggested approach authors design a number of conventional discrete and fuzzy controllers and provide the comparative analysis of quality indicators of the designed control systems transient responses.
SEAMLESS AND SECURE INTEGRATION OF SOCIALMEDIA, E-PORTFOLIO AND ALUMN SERVICES INTO UNIVERSITY INFORMATION ARCHITECTURE
Authors: Helmich Ontje , Herzog Michael A. , Neumann Christian
Published: February 2021

This document describes the concept and prototype for an “assembling” IT intergration portal to be used in higher education. Through the use of profiles, good usability and display of concentrated information students should be bound to the portal and university throughout their studies and their life. The proposed solution, to use Elgg as an information portal and social media platform, bridges the gap between the closed nature of university IT infrastructure and user-friendly, communication enhancing advancements of state-of-the-art web applications.
SUPPORT MODEL OF MATERIAL REQUIREMENTS PLANNING IN A COAL MINE
Authors: Jakowska-Suwalska Katarzyna , Wolny Maciej
Published: February 2021

This paper presents a multiple criteria decision making model of material requirements planning in a coal mine. The model is built on the basis of historical data of material consumption and two criteria are considered in the model: (a) probability of a lack of material and (b) deviations of the order size from the material consumption volumes in the last n periods. The work assumes that the volume of material consumed is a continuous random variable with a known distribution. In the model proposed it is also assumed that the costs of material order volume are limited. The problem analyzed with the two criteria is solved by using goal programming and as a result, two non-dominated solutions are received. The game theory approach to multiple attribute decision problems is used to choose the final solution.
TWO-DIMENSIONAL ERROR CONTROL BASED ON MODULAR CORRECTIVE CODES
Authors: Sieck Jürgen , Yatskiv Vasyl , Sachenko Anatoly , Tsavolyk Taras
Published: February 2021

The paper presents a method of detecting and correcting packet errors in the block of data based on the modular corrective codes. Check symbols are calculated separately in rows and columns of the data matrix. Herewith, the same data matrix coefficients are used for calculating the check symbols in rows and columns. This allows the detection and correction of errors packets that are in the same row or column. When two or more distorted information symbols are in the same row (assuming that there is only one error in the column) then errors can be corrected through the analysis of the column syndrome. The possible cases of the distorted symbols placement in a block of data and ways of their fixing are considered. The algorithm for detecting and correcting errors packets is elaborated. In the general case the offered method of error correction, based on modular correcting code, provides a correction of: n errors, which are in the same row or column of the data matrix of n size; 2*n-1 errors that are in the same row and column. The proposed method of encoding / decoding is designed in Verilog and implemented on FPGA in the Quartus II of Altera company.
SOLVING THE ROUTING PROBLEM BY ANT COLONY OPTIMIZATION ALGORITHMS
Authors: Zhikharevich Vladimir V. , Matsiuk Nataliia A. , Ostapov Sergey E.
Published: February 2021

The use of ant colony optimization algorithms for solving the routing problem in a process of products delivery taking into account a city transport infrastructure has shown in this research. The vehicle routing problem belongs to NP-hard task and its solution requires significant computing resources. Therefore, it is recommended to use metaheuristic methods to solve such problems including ant colony optimization algorithms. Solution of the Vehicle Routing Problem will cause a decrease of enterprises non-productive resources consumption and will promote the increase of their efficiency and competitiveness. The test example, consisting of eight consumers of freight and two transportation means with unlimited load capacity, moving around the certain city, is used for the implementation of the model. It can be further refined by taking into account various parameters besides transport infrastructure, including limitations on carrying capacity, a number of vehicles an working hours, an amount of consumers’ orders and a time for loading and unloading, etc.
FROM CAMAC TO WIRELESS SENSOR NETWORKS AND TIME-TRIGGERED SYSTEMS AND BEYOND: EVOLUTION OF COMPUTER INTERFACES FOR DATA ACQUISITION AND CONTROL. PART I
Authors: Zalewski Janusz
Published: February 2021

The objective of this paper is to present a historical overview of design choices for data acquisition and control systems, from the first developments in CAMAC, through the evolution of their designs operating in VMEbus, Firewire and USB, to the latest developments concerning distributed systems using, in particular, wireless protocols and time-triggered architecture. First part of the overview is focused on connectivity aspects, including buses and interconnects, as well as their standardization. More sophisticated designs and a number of challenges are addressed in the second part, among them: bus performance, bus safety and security, and others.
AN EXTENDED DISCUSSION ON A HIGH-CAPACITY COVERT CHANNEL FOR THE ANDROID OPERATING SYSTEM
Authors: Heard Timothy , Johnson Daryl
Published: February 2021

In “Exploring a High-Capacity Covert Channel for the Android Operating System” [1], a covert channel for communicating between different applications on the Android operating system was introduced and evaluated. This covert channel proved to be capable of a much higher throughput than any other comparable channels which had been explored previously. This article will expand on the work which was started in [1]. Specifically, further improvements on the initial covert channel concept will be detailed and their impact with regards to channel throughput will be evaluated. In addition, a new protocol for managing connections and communications between collaborating applications purely using this channel will be defined and explored. A number of different potential mechanisms and techniques for detecting the presence and use of this covert channel will also be described and discussed, including possible counter-measures which could be implemented.
PROGRAMMING AUTONOMOUS BEHAVIOR OF REACTIVE METERING SYSTEMS BY TIMED AUTOMATA
Authors: Krejčí Lukáš
Published: February 2021

The paper presents a new, innovative approach of programming of autonomous behavior of reactive metering systems. The presented method is based on safely timed automata defined by UPPAAL team. This modeling language is extended with event monitoring, utility functions for asynchronous operations invocation and supervising capabilities. Additionally, appropriate metering operations querying principle for metering systems is proposed. Finally, a new method of timed automata systems simulation is presented. This method is based on the principle of random interleaving of automata execution order and probabilities balancing in order to ensure fairness of automata execution. Advantages of presented methods as well as their basic principles are summarized and demonstrated on a case study of AMM network data concentrator. On this case study, it is shown, that proposed methods allow to effortlessly define the autonomous behavior of a data concentrator in the understandable and easily modifiable way, thus they lack major disadvantages of the currently used approach.
OBSERVATIONS-BASED COMPUTATIONAL ANALYTICS ON LOCAL CLIMATE DYNAMICS. PART 3: FORECASTING
Authors: Kolokolov Yury , Monovskaya Anna
Published: February 2021

Computational decision making is discussed in application to seasonal temperature forecasts taking into account inevitable nonlinear nature of local climate systems and deficiency of data on reliable observations. We focus on temperature extremes in terms of daily means and first involve the alternative conceptual model of local climate dynamics (the model of hysteresis regulation with double synchronization, so-called HDS-model) into such analytics. Recent years the HDS-model is describing successfully abnormal interannual temperature variability, on the basis of which it becomes potentially possible to extend forecasts of local daily means up to more than 1 year in future. In this connection the novel method of bifurcation traps is proposed, realized and tested. Results of processing the time series of temperature observations on daily mean surface air temperature illustrate peculiarities of this method in comparison with the traditional viewpoint on the forecasts. We believe that the discussion could be interesting in science and practice in order to increase the confidence of estimations on coming climate changes.
USING GRAPHIC NETWORK SIMULATOR 3 FOR DDOS ATTACKS SIMULATION
Authors: Balyk Anatoliy , Karpinski Mikolaj , Naglik Artur , Shangytbayeva Gulmira , Romanets Ihor
Published: February 2021

Distributed Denial of Service (DDoS) attacks are still one of the major cybersecurity threats and the focus of much research on developing DDoS attack mitigation and detection techniques. Being able to model DDoS attacks can help researchers develop effective countermeasures. Modeling DDoS attacks, however, is not an easy task because modern DDoS attacks are huge and simulating them would be impossible in most cases. That’s why researchers use tools like network simulators for modeling DDoS attacks. Simulation is a widely used technique in networking research, but it has suffered a loss of credibility in recent years because of doubts about its reliability. In our previous works we used discrete event simulators to simulate DDoS attacks, but our results were often different from real results. In this paper, we apply our approach and use Graphical Network Simulator-3(GNS3) to simulate an HTTP server’s performance in a typical enterprise network under DDoS attack. Also, we provide references to related work.
DEPENDABLE INTERNET OF THINGS FOR NETWORKED CARS
Authors: Großwindhager Bernhard , Rupp Astrid , Tappler Martin , Tranninger Markus , Weiser Samuel , Aichernig Bernhard K. , Boano Carlo Alberto , Horn Martin , Kubin Gernot , Mangard Stefan , Steinberger Martin , Römer Kay
Published: February 2021

The Internet of Things (IoT) extends the Internet to include also wireless embedded computers that are often equipped with sensors and actuators to monitor and control their physical environment. The IoT is increasingly used for safety-critical applications such as smart factories or networked cars, where a failure of the IoT may lead to catastrophic consequences. The IoT is therefore in urgent need of dependability, where reliability, availability, and security properties can be guaranteed even in harsh environments (e.g., radio interference) and under deliberate attacks (e.g., exploiting side channels). In this paper we give an overview of recent research activities in the LEAD project “Dependable Internet of Things in Adverse Environments” towards a dependable IoT, specifically dependable wireless communication and localization using Ultra-Wide-Band technology, secure execution of real-time software, protocol testing and verification, and dependable networked control. We also present the TruckLab testbed, where our research results can be integrated and validated in a platooning use case. In this testbed, model trucks are automatically controlled to follow a lead truck.
AN ALGORITHM FOR ASSESSING THE AVAILABILITY CRITERIA IN TELECOMMUNICATION NETWORKS
Authors: Monakhov Yuri M. , Monakhov Mikhail Yu. , Lantsov Vladimir N.
Published: February 2021

This article describes the method for estimating the availability of TCP/IP virtual data links and the TCP/IP network as a whole. As criterion of availability, authors consider boundary values, i.e. the minimum availability of network when the majority of the tasks are carried out via channels with the minimum availability, and the maximum availability of network when the majority of the tasks are carried out via channels with the maximum availability. After the minimum and maximum availability of channels have been estimated, it is possible to use the rated distance for assessment of availability value for the network as a whole Authors offer the analytical model of evaluating availability of telecommunication system components based on the Kolmogorov distance. Authors also brought up and tested an algorithm that allows computing the scalar value of availability of network with complex topology. Experiments have shown that the mean error of assessment (an arithmetic average from relative errors of all channels of this network) equals approximately 14.5% and only 25% of total number of relative errors by channel considerably exceed a mean error.
THE DEVELOPMENT OF TRUST MATRIX FOR RECOGNIZING RELIABLE CONTENT IN SOCIAL MEDIA
Authors: Saaya Zurina , Hong Tham Weng
Published: February 2021

Social media has emerged as a popular platform for users to share information about real-world events, particularly during disaster emergencies. However, disaster managers often having problem to gather an accurate information of the current situation since not all observations are made by reliable users. In this project, we address this problem by developing a trust matrix framework to identify the trustworthiness of the information shared on social media. Specifically, this project is focusing on flood disaster management and information shared on Twitter platform. The first objective of this project is to create text corpus for statistical and keyword analysis of a flood event shared on social media. Second objective is to develop a trust matrix for the flood events from social media. Third objective is to evaluate trust matrix for flood event using crowd-sourced data. The evaluation of trust matrix is done using real flood event dataset which are gathered between June and July 2018. To establishing a ground-truth for trust matrix framework, each data is mapped with actual flood event from news portal.
STUDIES ON STATISTICAL ANALYSIS AND PERFORMANCE EVALUATION FOR SOME STREAM CIPHERS
Authors: Gorbenko Ivan , Kuznetsov Alexandr , Gorbenko Yurii , Vdovenko Serhii , Tymchenko Vladyslav , Lutsenko Maria
Published: February 2021

This paper presents the results of the comparative analysis of safety statistics and performance of encryption, the Strumok stream symmetric cipher (proposed for the national encryption standard of Ukraine) with other known cryptographic transformation algorithms, such as SALSA20, SNOW2.0, HC, AES with usages in stream mode, etc. They are accepted as national, international standards or are presented by the New European Schemes for Signatures, Integrity, and Encryptions (NESSI), Cryptography Research and Evaluation Committees (CRYPTREC) and others. The result of safety statistics is an analysis of the cryptographic properties of the output sequences using statistical test sets developed by the National Institute of Standards and Technology (NIST STS) and the DIEHARD tests. The result of the study of performance is the evaluation of the use of central processing unit (CPU) time to convert one octet of data to 64-bit computing platforms, following the test profile used in the eSTREAM contest.
METHOD FOR DETECTING AGING RELATED FAILURES OF PROCESS SENSORS VIA NOISE SIGNAL MEASUREMENT
Authors: Toosi Topi , Sirola Miki , Laukkanen Jarkko , Van Heeswijk Mark , Karhunen Juha
Published: February 2021

In this article we examine the methods for detecting and predicting aging related process sensor failures by analyzing the noise of the sensor output signal. The study uses data from non-differential and differential pressure transmitters used in the pressure and water level measurements of the reactor pressure vessels of units 1 and 2 of the Olkiluoto nuclear power plant in Finland. The article contains a review of the current methods for detection of sensor failures. Additionally, we present a new method for detecting changes in the sensor output signal. The method creates fingerprints of the power spectra of the sensors by using Principal Component Analysis (PCA). The changes in these fingerprints together with the measurements of the redundant sensors can be used to detect indications of some of the impending sensor failures. In the experimental study we are able to produce stable fingerprints for both the non-differential and differential pressure transmitters. Also, a potential failure in one of the differential pressure transmitters in Olkiluoto unit 2 is detected by inspecting the fingerprints and analyzing the spectral changes of the transmitter output signal.
REINFORCEMENT LEARNING BASED ANTI-COLLISION ALGORITHM FOR RFID SYSTEMS
Authors: Loganathan Murukesan , Sabapathy Thennarasan , Elobaid Elshaikh Mohamed , Nasrun Osman Mohamed , Abd Rahim Rosemizi , Jusoh Muzammil , Ilman Jais Mohd , Ahmad Badlishah
Published: February 2021

Efficient collision arbitration protocol facilitates fast tag identification in radio frequency identification (RFID) systems. EPCGlobal-Class1-Generation2 (EPC-C1G2) protocol is the current standard for collision arbitration in commercial RFID systems. However, the main drawback of this protocol is that it requires excessive message exchanges between tags and the reader for its operation. This wastes energy of the already resource-constrained RFID readers. Hence, in this work, reinforcement learning based anti-collision protocol (RL-DFSA) is proposed to address the energy efficient collision arbitration problem in the RFID system. The proposed algorithm continuously learns and adapts to the changes in the environment by devising an optimal policy. The proposed RL-DFSA was evaluated through extensive simulations and compared with the variants of EPC-C1G2 algorithms that are currently being used in the commercial readers. Based on the results, it is concluded that RL-DFSA performs equal or better than EPC-C1G2 protocol in delay, throughput and time system efficiency when simulated for sparse and dense environments while requiring one order of magnitude lesser control message exchanges between the reader and the tags.
HYBRID DECISION SUPPORT SYSTEM FRAMEWORK FOR CROP YIELD PREDICTION AND RECOMMENDATION
Authors: Chiche Alebachew
Published: February 2021

In this paper, a hybrid decision support system is presented which uses both quantitative and qualitative data to provide effective and efficient decision making for crop yield prediction and suggestion. Our framework integrates KD-DSS and DD-DSS for solving complex problems by complementing the existing gap of individual decision support system in agriculture domain. For analyzing collected quantitative data of agriculture research center, our framework uses artificial neural network as a data mining technique. So, we use ANN for uncovering hidden knowledge in stored dataset. And this knowledge is further integrated with the knowledge base developed by acquiring qualitative data from expertise and represented using an IF-THEN production rule. The integration of knowledge collected from both qualitative and quantitative source of data provides a potential advantage for solving complex problems for decision makers. Finally, we will have the opportunity to enhance the framework coupling the features which can provide a group knowledge sharing among decision makers. So, this feature can present the opportunities to fill the disparity of decisions made by different decision makers.
IOT STATUS COMMUNICATION FOR HOME AUTOMATION
Authors: Steane Tyler Nicholas Edward , Radcliffe PJ
Published: February 2021

The vast majority of home automation systems depend on a permanent central controller and this is the source of many serious problems. The controller may be eliminated by using one or more Intermittent Control Devices such as a smartphone, but the responsibilities of the controller must be redistributed. This paper considers the problem of keeping multiple intermittent controllers up-to-date with status information for devices around the home. Four protocols are proposed, taking key lessons from existing network protocols, and then implemented, tested and compared with the expected performance of UPnP. All four protocols outperform UPnP and further analysis shows that these protocols can be implemented in a robust and user-friendly manner. A comparison of the packet efficiency of these protocols demonstrates that the combination of device registration and packet broadcasting makes for the most efficient protocol and should form the basis of devices status communications in home automation systems without a permanent central controller.