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Today, point clouds are becoming an increasingly common digital representation of realworld objects. However, the raw point clouds obtained by terrestrial laser scanning (or other methods, e. g., photogrammetry or low-cost sensors) are often noisy with many outliers. Thus, it is necessary to remove the noise and outliers from the point clouds before further processing while preserving the elements of the measured objects in high detail. Moreover, in the case of model creation from point clouds using basic geometric shapes (e.g., planes, spheres, cylinders, etc.), one of the most important processing steps is the segmentation of these shapes. Therefore, filtration of unrelated parts of the point cloud can increase the efficiency of processing. In this paper, two algorithms for point cloud filtration are developed, which can be performed based on the local point density and the local normal variation in the surrounding of the selected point. The algorithms were implemented as a standalone application in MATLAB software. The paper's final part describes the experimental testing of the proposed algorithms on several point clouds with various densities, complexity, and different levels of noise and outliers. [ABSTRACT FROM AUTHOR]

This article is devoted to the questions of the reliability and the accuracy of the invented algorithm. Background: The implementation of autonomous navigation system for unmanned airborne vehicle is required for the reliable navigation in case of the instability of the satellite navigation system. Traditionally this problem is solved by the terrain landform navigation system, also the synthetic aperture radar navigation systems could be used as the correction system for the inertial navigation system. Nevertheless, these correction systems do not allow designers to provide necessary stability and reliability of whole system. Therefore, we use lengthened objects as the reference objects, which are stable enough either in different weather seasons. Also these objects (such as roads, rivers, railways) are very often on flat landforms, where the terrain landform navigation system does not work. Methods: We process the amplitude distribution of the reflected signal in order to get the parameter of the algorithm. The obtained distributions could be compared with etalon distributions, which can be computed for various terrain types. Therefore, we can use the intersection area as the indicator of the underlying terrain. This algorithm could be found in previous papers. This paper describes in detail problem of choice necessary counts number for reliable detection of lengthened objects. The suggested solutions allow user to implement this algorithm in the real systems. Also the comparison of the developed algorithm with algorithm based on the KolmogorovSmirnov criterion briefly described there. Conclusion: The implementation of the designed algorithm contains resolving of many small but important questions such as choice of necessary counts number of the accuracy of the algorithm. These questions are described in this paper. [ABSTRACT FROM AUTHOR]

Background: This article is devoted to the question of correction system implementation. The correction system is necessary to provide the ability of autonomous navigation the unmanned airborne vehicle. We can see a lot of examples of terrain landform correction systems and “synthetic aperture radar” – based systems. But in the case of using information about lengthened objects, we have a great opportunity to provide robustness objects, which we can reliably cross during our flight. Nevertheless, these objects should be placed in some on-board system, which will process this information to make a suggestion about unmanned airborne vehicle position. Methods: Recently it was suggested such an algorithm, which is based on the histogram comparison of the reflected signal of the pulse radar altimeter. It is well known that the distribution of the reflected signal of the pulse radar is depend on the terrain from which this signal was reflected. Therefore, the idea of using this information as the parameter, which helps to define the terrain type, is described in this paper. The comparison of the histograms (one is etalon, other is current histogram) in this algorithm is based on the evaluation of the intersection area of these histograms. Results: The main part of this paper reveals how this idea could be implemented in the real navigation system structure. The question of performance is also discussed there. It is shown a useful case of implementation of this algorithm. Conclusion: The suggested algorithm could be implemented in the real on-board system and it allows us to increase the accuracy of autonomous navigation without implementing any additional hardware decisions. [ABSTRACT FROM AUTHOR]

This paper details findings of the complex research aimed at the strategic planning effective instrument finding and postulates that simulation with agent-based models implementation can become this instrument. Every city model is an immensely complex artefact, as it should be a set of interrelated digital twins of social living and infrastructural non-living objects, which are to reflect the real objects in the dynamics of their lifecycles, at the same time, providing an opportunity for developing effective control measures and means. If one considers an active agent to be an intellectual entity, and wants to model their behaviour, it is necessary to look for the agent's motivation. In the model, motivation for every individual's act or action is represented through their needs. Common algorithms of needs meeting in the form of recipes are stored in the main data base of the model, in Global Knowledge Base. This paper also delivers description both in verbal and graphical forms the algorithm of recipes implementation. [ABSTRACT FROM AUTHOR]

Pulse-width modulation (PWM), or pulse-duration modulation (PDM), is a modulation technique used to encode a message into a pulsing signal. Although this modulation technique can be used to encode information for transmission, its main use is to allow the control of the power supplied to electrical devices. This paper proposes the PWM control of the laboratory bell furnace with utilization of PI controller. The paper presents the PI control algorithm modified in order to regulate the power of furnace. The control is focused on temperature stabilization in furnace or in batch. The main problem is that the proposed furnace does not enable continual control the power. There is possible just On-Off control with a digital signal. Paper present how to transform the PI controller output into the PWM control actuating. There was utilized PLC as a main controller of furnace. The control algorithms were proposed in B&R Automation Basic language as a cyclic tasks implemented on PLC. The proposed experimental furnace was used in order to simulate the annealing of steel coils and verification of indirect measurement of temperature. [ABSTRACT FROM AUTHOR]

Machine Learning (ML) is the study and the usage of the mathematical algorithms which can improve their performance without the need for human interaction. These algorithms are considered as a subset of Artificial Intelligence (AI). Machine learning algorithms use past data as input and produce new predicted values as an output. Machine learning algorithms have been used in many areas for solving an innumerable number of tasks. However, the various tasks need applying of different machine learning algorithms for obtaining maximum accuracy of the target results. In this paper, an analysis with consideration of the advantages, disadvantages, and different areas of applications in the real world are made for each of the four ML algorithm groups - supervised, unsupervised, semi-supervised, and reinforcement learning. After the comparative analysis is done, the ensemble methods boosting, stacking, and bagging are introduced, described, and compared. Emphasis is done on defining the accuracy of which ML algorithms can be improved and which ensemble methods can be used for that. Machine Learning algorithms combined with ensemble methods are highly competitive and provide the best results in most cases where they are applicable. [ABSTRACT FROM AUTHOR]

The origin of the unusual landforms of Baer's mounds on the Near-Caspian lowland is not well understood. One of the possible approaches to the understanding of natural history of the region is searching of similar regions. In the many papers the problem of mounds origin is revised but with not of review of geomorphological analogues in the World. Some author states that are not exist of similar landforms anywhere else. The topography characterize by the sets of parallel ridges and hollows / valleys. Range of length of the ridges is 0.5-3 km, average height is 7-10 m, and width is 150-200 m. The clear periodical pattern of the topography allows using landform's spectral analysis in this task. We developed the algorithm of such analysis in the R. The algorithm allows computing the seven parameters: maximum of the waves magnitudes, the importance of given share of waves, the general direction of heights fluctuation, the severity of this direction, frequencies of the biggest wave by the orthogonal directions (W-E and S-N) and the general wavelength. For the Baer's mounds territories the values of spectral characteristics of landforms are unique. The maximum magnitude for mound's territory is about 10 m, and on the around located territories is 1-2 m only. Importance of the main harmonic waves is 0.6 and 0.25 on the averages. The most frequent values of the wavelengths on the mound's site are 700-1500 m, and on the ambient area this parameters are 1500-2500 m and rises with large window size. All this parameters together are spectral fingerprint of these rare landforms. On the SRTM data we started the search of the similar topography. The first results allow saying about existing of similar mounds on the other continents. Used test site - territory of Iran and other neighbor countries. [ABSTRACT FROM AUTHOR]

The paper exposes the tuning and the evaluation with experimental data of an algorithm used to predict the lost data in the GPS readings due to the acquisition rate significantly different from that of the Inertial Navigation System (INS). The developed algorithm provides a real time prediction of the GPS data at the same rate with the INS data in order to be ready for the processing step, which realizes the fusion of the two systems. To acquire the data, an INS/GPS hardware structure based MEMS sensors has been developed in the Aerospace Engineering laboratories at the University of Craiova, Romania, as a part of a research project. Its detection components are an inertial module and a satellite positioning module, the data provided by them being integrated with a microcontroller. The data from inertial sensors have been acquired with a rate of 100 samples/s, while the GPS receiver provided data once per second. The prediction algorithm implements an intelligent approach based on adaptive neuro-fuzzy inference systems (ANFIS). The neuro-fuzzy algorithm is an extrapolator for the data received from the GPS system, but whose training mechanism, uses in the first phase data from the INS system, which, after initialization, in the short term, does not significantly degrade the performance of the navigation solution under the influence of sensors errors in the inertial detection unit. The structural scheme of the Fuzzy Inference System training process includes six channels: three speed components and three global coordinates. The INS/GPS hardware structure has been boarded on a testing vehicle and experimental data acquired for many testing situations. The evaluation results with the experimental data proved a very good operation of the developed algorithm, it being ready to be incorporated in the INS/GPS integrated structure for the next stage of the research project. [ABSTRACT FROM AUTHOR]

The method of two-phase locking (2PL) is still used in concurrency access in the global transaction management. It has its advantages in distributed database management systems (DDBMS), conflicted events. The paper views modeling algorithms of Centralized, Distributed and Primary copy Two-version Two-phase locking. The presented algorithms are models of the corresponding variants of the 2PL protocols for DDBMS using two versions. As in concurrency control of distributed transactions in DDBMS deadlocks are possible to appear, one of the ways for their preventing is the usage of two-version architecture of the data in a distributed database (DDB). The lack of algorithms published as well as results from investigations of such algorithms imposes the development of simulation models and their investigation. In detail the paper considers such models of Two-version two-phase locking (2V2PL): Centralized 2V2PL, Primary copy 2V2PL and Distributed 2V2PL. The simulations of the 2V2PL algorithms and the results reported are achieved by the system of imitation modeling GPSS Studio. GPSS Studio is the latest extension (shell) of the GPSS World Imitation Modeling Environment with the following new features: automatic text alignment; contextual hints; general management of the study (models, experiments and results) through a special project structure; Using libraries from pre-created standard composite or elementary blocks; Design of interactive forms for analysis of modeling results; Automatically create a virtual report of the study, etc. The main characteristics of transaction processing in distributed database management systems such as throughput, response time and probability service are presented. [ABSTRACT FROM AUTHOR]

The present paper is dedicated to investigation of the business protection technologies from the perspective of security facilities at multiple levels of the organisation development. Objective instruments that allow to ascertain causes of the organisation disruption and to develop a system of counter measures act in the capacity of such resources. We offer a new method of assessment of the security service level of readiness to perform their duties in the conditions of changes introduced within the organisation. Its implementation improves the performance of the overall security system within the organisation. It is achieved by means of detection of cases of loop of vigilance of the staff at the stage of introduction of the new technological resources. Introduction of the new automated tools, by causing reduction of the degree of responsibility exhibited by the security guards, gives rise to cases when the security guards are not ready to provide full-value protection of the organisation in the event of temporary stoppage of the system. In which case, any change is an expensive procedure that is why any unauthorized tampering causes serious losses. From this perspective, an organisation must have at its disposal tools of the current status assessment that would not allow to intervene in the steady process. Absence of these tools mark the borders of the highlighted problem. Consequently, full-scale protection is the readiness of the organisation to determine the current position and, when necessary, to restore the lost steadiness of its performance. [ABSTRACT FROM AUTHOR]

Visual identity is an everyday work for the majority of contemporary graphic designers, one of the most challenging forms of visual identity is dynamic identity. Dynamic identity assumes using some randomly generated parts in the design (for example, the appearance of the logo can vary in a broad range). Some designers that worked on the dynamic identity projects create visual identity by intuition, selecting a simple principle for adding randomness, the others develop a very specific approach of adding randomness in each project. The author of this paper believed that the dynamic identity represents the example of using controlled randomness in design, so the systematic approach should exist for adding randomness to the dynamic identity system. This paper discusses a way of using controlled randomness in the development of visual identity, determines the elements of design and a principle of considerable changes in dynamic identity system, explores several different algorithms of applying randomness to visual identity for making it dynamic identity. These algorithms are also evaluated on their potential and usefulness in the process of development of the dynamic identity system. [ABSTRACT FROM AUTHOR]

P colonies (see [2]) are a well-established version of the P systems (see [3]), the computational device based on membrane computing. One branch of the research of the P-colonies focuses on the possibility to consider the two-dimensional environment, in which the agents act, and the 2D P colonies (see [1]) were introduced. 2D P colonies showed to be suitable for the simulations of various (not only) multi-agent systems, and natural phenomena, like the flash floods. The Grey wolf algorithm (see [4]) is the optimization-based algorithm inspired by social dynamics found in packs of grey wolves and by their ability to create dynamically hierarchies in which every member has a clearly defined role. The wolves’ primary goal is to find and hunt down prey, which in our case equals finding the optimal solution to the given problem. The grey wolf algorithm displays positive results thanks to the principles of randomness and communication between wolves. In this paper, we propose a model of the 2D P colonies with the blackboard. The only communicating device in the case of the 2D P colony is the environment, what is not sufficient for some kinds of multi-agent systems. The blackboard is a communication device accessible for all the agents at the same time, and it allows to share all the necessary information. An agent can read and write on the blackboard using its communicating rules. Using the blackboard allows us to simulate the grey wolf algorithm using the 2D P colony, describe and formalize the behavior of the wolves and agents in the multi-agent system in general. [ABSTRACT FROM AUTHOR]

Particle swarm optimization (PSO) is a stochastic computational technique for finding optimal regions of complex search spaces. The method was inspired by social behavior of organism and it belongs to the evolutionary computation (EC) to the group of swarm intelligence (SI). It has a few parameters to adjust and the method is easy to implement, which are the main advantages. The main aim of this paper is to find out, if limitation of the search space influences the optimization process. In this paper, we compare two modifications of PSO algorithm - variant using the parameter of inertia weight and variant with constriction factor. Both variants are solved separately for constrained and unconstrained space. Constrained area is when the boundaries are clear district, unconstrained is when particles can cross the boundaries. For comparison, eleven benchmark functions which were prepared for the special session on real-parameter optimization of CEC 2005 were used. Differences in results between constrained and unconstrained area is presented in this paper. It was found, that constrained area of search space gives better results. In additional, variant of PSO algorithm with linearly decreasing inertia weigh is better for chosen optimization problem. [ABSTRACT FROM AUTHOR]

In this paper the approach to virtual laboratory "Geoinformation Systems" creation is proposed. Virtual laboratory is a complicated system that consists of a lot of hardware and software tools. The laboratory was created in order to improve the quality of education in the fields of geoinformatics and information technologies. The laboratory provides scientific support of the educational process, integration of innovative research and educational activities. During the course of self-study, students have the opportunity to communicate with each other, and thereby to develop the skills of collective work on large projects using modern and advanced information technology. The students work with knowledge base on the three levels of control: training testing; control testing with evaluation of knowledge; final testing, the results of which automatically generates an academic records. The laboratory provides comprehensive support for the scientific and educational activities - from training sessions (lectures, seminars etc.) with the use of modern educational technology to independent research work of students. In addition, the laboratory is the technological basis for further development and approbation of the concept of electronic research and educational complex: the methodologies of design and creation of hardware, software, information and organizational support, experimental evaluation of the complexity of the implementation of the developed architecture, evaluating the effectiveness of new educational technologies. A variety of different hardware and software tools allow to create a variety of educational routes. The composition and structure of the virtual laboratory is discussed. Experience of using the system is presented. The description of the curriculums and practical works is given. [ABSTRACT FROM AUTHOR]

This paper proposes an adjustment algorithm of GPS vector as correlated observations. The theoretical and practical analysis has been performed for the case of a small GPS vector network (of a few hundred meters) to monitor displacements of land area or deformations of engineering structures. The detailed record of correlated observations adjustment algorithm is presented. In this case, the adjustment procedure using the least squares principle can be proven to be unchanged. The key task in this approach (adjustment of correlated values) is still the correct determination of weight coefficients matrices. Also the analysis of impact of adjusting coordinates on the spatial lengths of vectors (used, for example, to determine the so-called relative displacements) is also presented. Two factors affecting the mutual correlation of GPS vectors are considered: synchronous measurement with a static method using two or more receivers and closure of elementary figures (triangles) during numerical development of a vector network. The completed practical example (for several comparative calculation variants) allows for assessing the impact of GPS vector correlation. [ABSTRACT FROM AUTHOR]

Hydropower plants are objects which horizontal and vertical displacement must be monitored regularly. Method used for determination of horizontal displacements of the Hydropower plant Mostar in Bosnia and Herzegovina, and its practical execution are presented. Algorithms for regular adjustment of indirect measurements and Stransformations into optimal datum are also presented in this paper. Further, regular adjustments of indirect measurements of the reference and control point coordinates in the conventional datum are performed for two epochs of measurements (December 2014 and June 2015). For each epoch regular adjustments are performed in a way that two base points are fixed, and all the other points, reference and control, are adjusted simultaneously. For adjusted values, in both cases, the S-transformation algorithm is used for transformation from conventional to optimal datum. Horizontal displacements are calculated between those two epochs, as well as regarding zero-epoch (year 1988). The analysis of the obtained position displacements is given, as well as the recommendations for the future series of measurements. [ABSTRACT FROM AUTHOR]

In the context of urban planning, it is very important to estimate the nature of the roof of every building and, in particular, to make the difference between flat roofs and gable ones. This analysis is necessary in seismically active areas. Also in the assessment of renewable energy projects such solar energy, the shape of roofs must be accurately retrieved. In order to perform this task automatically on a large scale, aerial photos provide a useful solution. The goal of this research project is the development of algorithm for accurate mapping of two different roof types in digital aerial images. The algorithm proposed in this paper includes several components: pre-processing step to reduce illumination differences of individual roof surfaces, statistical moments calculation and color indexing. Roof models are created and saved as masks with feature specific descriptors. Masks are then used to mark areas that contain elements of the different roof types (e.g. gable and hip). The final orthophoto visualize an accurate position of each of the roof types. The result is evaluated using precision recall method. [ABSTRACT FROM AUTHOR]

Authors describe the novel approach to boost the scientific data analysis performance with the data-storing schema for distributed scientific research systems. This approach optimizes the workload on storage nodes and enhances the computation performance. Managing the enormous output of scientific research systems is expected to be the most technically difficult part of all recent projects producing Petabytes of imagery data. In this paper we describe the distributed storage structure with indexing techniques which can be effectively applied for scientific multidimensional data processing in geoinformatics. Basic principal of this project is distributed (N,K)-block storage schema (LH*RS or SDDS). We develop the descent of LH*RS especially for multidimensional data arrays using the multiscaled representation of these arrays and using the efficient pre-processing algorithms. The LH*RS is positioned as the general-purpose method, and its efficiency does not depend on the data file type but we can implement some enhancements in its distribution algorithm in order to accelerate its performance in the case of multidimensional or imagery data. Dataset is decomposed into data blocks of several levels using the Wavelet transform. The required dataset of the requested scale and resolution is reconstructed from the corresponding set of downloaded blocks on client's side. In order to accelerate data queries processing we can additionally use a pre-computed statistic results blocks and their hierarchical representation. Main principle of data preprocessing comprises the original data merging with the results of transformation algorithm in adjacent buckets of the same storage. These results are computed only once during the data storing stage simultaneously with data distribution and with the same computing unit. The main advantage of this approach is that we can use these results together with original data or even separately to serve different data queries with both value and dimension subsetting conditions. This approach can reduce the resource costs of corresponding scientific problems. Another advantage of this schema is possibility of sparse data processing for regular or irregular coordinate grid. [ABSTRACT FROM AUTHOR]

Nowadays the conditions for admission to higher education institutions in Russia can allow centralizing the procedure for competitive selection of applicants across the country to increase the clarity and publicity of this process concerning applicants, as well as to reduce the universities expenses for the admission campaign organization. The federal information system for providing Unified State Exam and admission can become the heart of such centralization, but at the present time there are no algorithms for competitive selection. The research paper suggests a modification of the existing mathematical model for the organization of a centralized competition for higher educational institutions in Russia, which is a multi-criteria task of the objective function of higher educational institutions optimizing (the system of higher education generally), corresponding to enrolling the applicants with the highest score, and the target functions of entrants, consisting in the admission to the most interesting (top-priority) Programme of Study. To grade the applicants, we suggest the evaluation function modification, which includes a new term intended to gradate the entrants having the same scores for their entrance examinations and individual achievements as well. The research also suggests a heuristic iterative algorithm for solving the defined multi-criteria optimization problem, which is based on searching a solution for one particular university in the context of indicating a number of specialties and directions of preparation in the application of each enrollee. We have estimated the speed of the algorithm as logarithmic with the help of an especially designed program. The research shows that the algorithm is applicable for calculating the competitive situation nationwide over executing time. [ABSTRACT FROM AUTHOR]

In this paper we presented the calculation algorithms and the software for the calculation of the moving average with various windows, for calculating the analytical expressions of the polynomial tendencies of various degrees and for the calculation of the correlation factor variation between two parameters. Trend analysis is part of the field of regression analysis that satisfies the smallest squares criterion. The difference between the calculated value of the trend surface at a certain point and the value observed at that point is the residual value. If moving averages or trending surfaces are considered to be the regional or large-scale component, then the residual value is the local or small-scale component. The removal of the regional trend has the effect of highlighting the local components represented by residual values. Principles of trend surface analysis are also applicable to hyper-surfaces in any dimensions. A surface occupying a three-dimensional space is a mathematical function with a dependent variable and two independent variables. We can operate mathematically with four or more variables, that are of major importance in applications where we want to investigate more geological or geophysical parameters. Viewing spatial relationships in a three-dimensional space is very difficult. The best method is to assign a constant value to an independent parameter and to represent the parameter that depends only on two independent parameters, as in the case of trending surfaces. This type of representation is the general trend of the parameter dependent on two independent parameters. Typically, the dependent parameter is a geological or geophysical parameter and the two independent parameters are latitude and longitude. Depending on the degrees of the calculated trend, we can get the effect of the filters on anomalies. The high pass filters are obtained by the difference between the initial values (measured) and the values calculated for the trending surface in the same nodes of the network. The band pass filters, are obtained by the difference between the calculated values for two levels of degrees for trend surfaces in the same nodes of the network. Low pass filters are represented by the values calculated from the surface analytical expressions of the network nodes used. In the paper we have exemplified these methods for a test area, copper mine Assarel Medet near Panagyurishte, in the project Real-Time Mineral X-Ray Analysis for Efficient and Sustainable Mining, acronym: X-MINE. [ABSTRACT FROM AUTHOR]

This paper describes multiple homogeneous coordinate transformations necessary for interior and exterior (relative and absolute) orientation in analytical and digital photogrammetry & remote sensing. In this paper, I intend to analyze the 3D operations like rotations, translations and scaling which are performed using matrices and lineal algebra in homogeneous coordinates. Each operation is performed by multiplying the 3D vertices by a specific transformation matrix. Using 4x4 transformation matrices allows us to combine rotations, translations, scales and shears into a single matrix. Because a 3D object or scene is composed of a collection of 3D models, which have four different coordinates systems or spaces (Space-global, Space-object, Space-view and Space-screen), the homogeneous transformations presented are referring to the transition from one system to another. The algorithms of the transformations presented are examples of affine transformations which are fast to compute and very useful throughout computer graphics. In the same time, this paper reviews basic philosophy concerning homogenous transformations very useful in the relationship between photogrammetry and computer vision applications. [ABSTRACT FROM AUTHOR]

3D modelling of the geology formations of the earth is an essential step towards understanding of complex geological phenomena and must be based on the whole of knowledge and available data for the study area (digital terrain models, geological and geophysical maps, sections, drill-holes and geological interpretation). 3D GeoModeller software made by Intrepid Geophysics Co. was designed to assemble together into the same 3D space data from various sources, in order to ensure geometrical coherence. For interpolation of geology and geophysical data will take into account the geology 'boundary' data (geology contacts, interfaces and limits), the dip of the geology formations and processed geophysical data with some algorithms. In our paper we show few algorithms for filtering data in 2D and 3D that we made, as so as, mobile averages with different windows (square or cubic) or polynomial surfaces. These methods are based on the smallest squares’ method used for the smoothing of geological and geophysical data, where the difference between the calculated value of the trend surface at each point and the value observed at that point is the residual value. The sum of the squares of these residual values must be minimal according to the smallest square criterion. Polynomial surfaces or mobile averages with different windows are considered to be the regional components, then the residual value should be considered as the local or smallscale component. The degree of regionalism is proportional to the size of the mobile window, respectively inversely proportional to the degree of the polynomial surface. Removing the regional trend from original data has the effect of highlighting local components represented by residual values. We exemplify results of these algorithms for territory of Romania. [ABSTRACT FROM AUTHOR]

Romania and Bulgaria started to develop in partnership a system of monitoring, warning and dissemination of data on the quality of environment in the border-area counties. The project it is achieved under the strategic project WATER - integrated water management and is financed under the Romania - Bulgaria Cross-border Cooperation Programme 2007-2013. The project goal it is to establish a common management and control system of the quality of the Danube waters under extreme conditions, caused by natural and technological disasters. The project area includes about 500 km on Romanian and Bulgarian common Danube border area. In order to implement the designed activities in the project area, one of the major infrastructure needed it is the geodetic network and based on that a geo-database including digital maps, specific data and metadata, GIS applications, et al. Along the history, from geodetic point of view, for different activities on the Danube (navigation, water level and quality monitoring, floods management) different kinds of Coordinate and Reference Systems (CRS) were used by Danube countries. For the Romanian-Bulgarian sector, an important issue of this project it is the establishment of a common CRS including horizontal and vertical position. Technical University of Civil Engineering Bucharest (TUCEB - Romania) and Executive Agency for Exploration and Maintenance of the Danube River (EAEMDR - Bulgaria) are the responsible partners for Activity 6 of the WATER project. The main goal of the Activity 6 it is to adopt and to implement a common CRS according to the European INSPIRE Directive. This paper presents geodetic research and applications performed on Activity 6 of the WATER project in order to establish coordinates conversion and transformation standards. The theoretical and practical implementation of horizontal CRS, named ETRS89 (European Terrestrial Reference System) and vertical CRS, named EVRS (European Vertical Reference System) are presented. Research on possible connections between these CRS and previous CRS (as Black Sea 1975 and Baltic Sea) are investigated. The final results of this activity can contribute to the modern realization of the most recent connection between the national geodetic networks of Romania and Bulgaria. [ABSTRACT FROM AUTHOR]

Numerical modeling is an useful and frequently applied tool in the design of various types of geotechnical constructions. The progressive development of computer technology allows to perform faster and more accurate analyzes. The most important factor that affect simulation time of numerical algorithms is the rank of compaction of the computational grid. In this paper the analysis of the effect of the density of grid computing numerical model of flood embankments on the computation time are presented. The accuracy of modeling results for different shapes of assumed computational grid model were presented additionally. The analysis was conducted due to the changes in slope stability factor of the embankment, accidental displacement, strain and total stress state within the modeled object. Numerical computations was conducted with FLAC v.7.0 based on the finite difference method. [ABSTRACT FROM AUTHOR]

The developed multidimensional data mining algorithm integrates logical and statistical computing. It provides interactive and exploratory environment for mining spatial and temporal features of time series datasets. The algorithm is applied on Crop production database which stores spatial time series on crop production in EU-Balkan states. The paper discusses the mined information on crop production quantity and area harvested in Bulgaria at national and regional level. The data mining algorithm and software can be used to analyze spatial time series when studying the dynamics of social systems, economical activities and natural resources exploitation. [ABSTRACT FROM AUTHOR]

This paper presents the way of implementation of some control algorithms required for positioning of manufacturing tool ( cutter) at a point in a plan X-0-Y, or for drawing a well-defined coordinate geometric figure (triangle , square, rectangle, circle, etc.). The experimental stand used for present testing algorithms is made of two screw-nut systems (one for each axis), each driven by a DC motor, systems which converts the rotary motion of both engines in translational moving of the manufacturing tool support. The paper contains experimental results obtained from testing studied algorithms, and some conclusions about the precision of these algorithms for drawing geometrical figures mentioned above. The experimental stand used for testing algorithms allows positioning in a rectangular space with an area of 0.5 m2. For applications requiring greater processing area, can be made changes on both axes. [ABSTRACT FROM AUTHOR]

Cluster analysis is an important category of data mining issues. Clustering techniques are frequently applied also in business and economy, for example in customer's classification, enterprises grouping or in other economic data analyses. The paper submits a new clustering method, which we have named Firefly Clustering Algorithm (FCA), based on a recently developed and commonly applied optimisation technique - Firefly Algorithm (FA) that simulates natural behaviour of living fireflies. After brief presentation of the original idea of classical FA as an optimisat ion technique, we submit the description of FCA - the proposed clustering method. The algorithm has been implemented in form of our computer program written in C++. Next we show a financial utilisation of FCA as a tool for cluster analysis of selected stock companies quoted on Warsaw Stock Exchange, with taking into account two factors (as input variables): return rate and risk. Results have been visualised and discussed. Directions of further researches have been outlined. Although here we have considered a 2-dimensional problem (i.e. a dataset with only 2 numerical features), the presented FCA method is universal and can be applied for any number of inputs (obviously with limited visualisation capabilities). [ABSTRACT FROM AUTHOR]

Brief description of the study and used methods. Brief description of the study and used As part of the preparatory work aimed to create the application solution allowing for the automation of searching objects in data, obtained in the scanning process using ALS (Airborne Laser Scanning) or TLS (Terrestrial Laser Scanning), the authors prepared a artificial (synthetic, theoretical) model of space, used for the verification of operation of algorithm based on the images analysis. The research described in the paper was based on synthetically generated model of points cloud which gave bases to continue works on real data sets obtained from the registration with the use of airborne scanner (LiDAR). Authors attempt to point out the importance (and essence) of analyses using a synthetic model in the analysis of authors algorithms (including those based on the use of the integration of known algorithms), applicable to the surveying works aimed to identify objects on results of laser scanning or filtration in order to obtain the numerical terrain model. In modern IT publications, is possible to find solutions that relate to authors applications created with the use of classical development tools or scientific computing environments of Matlab type. Most often, in these papers, there is a lack of studies which use the synthetic models with a priori known parameters, structure and other characteristic spatial features which confirm the effectiveness and verification of used algorithms. Therefore, the article provides an overview of segmentation methods and analysis of possible data filters and results of the development include their use in relation to the prepared and strictly (exactly) parameterized synthetic model which simulates the points cloud from LiDAR. The Laplacian of Gaussian, Sobel, Canny and Prewitt operators and Robert's cross edge detection are subject to the detailed analyses as well as individual stages of data processing into the raster nature. There are also possibilities of chain use of Freeman code and Douglas-Peucker algorithm for the vectorization of the obtained data. The authors present an assessment of the effectiveness and registered problems. The works were summarized with the preparation of the author's application aimed to the segmentation and the creation of the digital terrain model. This application was implemented to work on real data (empirical analyses). [ABSTRACT FROM AUTHOR]

This paper focuses the surveying and processing protocol developed by the CRdC Benecon Scarl/Dipartimento di Architettura e Disegno Industriale Luigi Vanvitelli of the Seconda Università degli Studi di Napoli in conjunction with the Gruppo Esplorazione Aeromarittima of the Guardia di Finanza. This heterogeneous team operates several instruments and aeronautical configurations, integrating active and passive remote sensing instruments. Data processing is adapted to the different morphology and land use/cover of the imaged areas. In urban areas, the spectral angle mapped algorithm is used against a collection of Cannabis reflectance spectra collected in field activities. In forested areas, images are classified along with topography and hydrographical information. The operational protocol was developed and adopted towards the activities conducted in 2012, 2013 and 2014 in Albania for the identification of Cannabis cultivations. The imaged area summed to approximately 990 km² in 2012, 3618 km² in 2013 and 4313 km² in 2014. At the end of the missions, the remote sensing activities affected more than 15.08% of the area of the Country. [ABSTRACT FROM AUTHOR]

Hyperspectral images and field spectroradiometer with high spectral resolution can improve substantially crop mapping by reducing similarities between different crop types which has similar ecological conditions. This is done by recording fine details of the crop interaction with sunlight. This paper deploys crop spectral signatures database interactive tool for the major crops in the Eastern Mediterranean Basin. The collection of spectral signatures of crops is performed during the growth stage of the crops. The database includes several physical and chemical parameters for crops, resampled spectral signatures for a specific multispectral or hyperspectral satellites. Combining the hyperspectral data with an efficient segmentation algorithm can increase the accuracy of the final crop map. To prove this idea, major crops such as "winter wheat" and "spring potato" are mapped using the hyperspectral data which includes spectral signatures database and CHRIS-Proba satellite images. The images are segmented using different supervised algorithms. The evaluation of the results showed that using the database interactive tool with Spectral Angle Mapper (SAM) algorithm increased the accuracy significantly. [ABSTRACT FROM AUTHOR]

One of the most important issues in the problem of fusing partial maps without common reference frames into one large global map is requirement of manually obtaining the locations of mobile 3D laser scanners that are used to scan the environment. In this paper, we propose a novel positioning approach to obtain the locations of 3D laser scanners. The main limitation of our approach is that 3D laser scanners must be equipped with long-range wireless interfaces or off-the-shelf long-range wireless interfaces must be installed on them. Via references points (anchor nodes) on the corners of the environments, we use the measured distances and find the locations of the 3D laser scanners through multilateration technique. Although the approach proposed in this study is much easier to implement and much more cost-effective compared to the existing approaches, it is well-known that there are many challenges in real world scenarios that cannot be included in simulation environments and these challenges have impacts on the success of positioning algorithms. Therefore, the future work of this study consists of field tests using a set of 3D laser scanners and a group of anchor nodes so that the positioning accuracy of the proposed approach can be verified. [ABSTRACT FROM AUTHOR]

The article proposed the technology of monitoring the process control system the manmachine- environment. Machine Health Monitoring Center uses technology to identify trends that will help improve the service, support, and overall design of equipment. Technology specialists handle hundreds of alerts per day, either contacting the customer directly or passing the information on to a service manager or field dispatcher. Hardware-software automated monitoring enables structural studies and monitoring algorithms of technological machines, and operator actions. The proposed methods and technologies for monitoring control parameters earthmoving machinery are the basis for the synthesis of algorithms of Automated Control System. The possibility of modeling control processes based on the diagnostic data improves the quality of models. Refines the model of the medium and technology of machines, as a result of the diagnosis, provide lifecycle ACS algorithms during the design and operation. Increases competitive technological machines due to functionality associated with the correction of the control algorithms. [ABSTRACT FROM AUTHOR]

The paper is devoted to construction of the time efficient algorithm for solving the structural inverse gravimetry problem. The problem is in finding by known gravitational data multiple interfaces between layers with different constant densities. This problem is described by a nonlinear integral equation of the first kind; so, it is ill-posed. After discretization of the area and approximation of the integral operator, the problem is reduced to solving a system of nonlinear equations. An efficient method was constructed on the basis of the nonlinear conjugate gradient method. The approximation method based on dropping out the lesser elements of Jacobian matrix was proposed. The parallel algorithm was developed and numerically implemented for the multicore processor. The structural gravimetry problem of reconstructing three surfaces using quasi-real data was solved. Comparison of the proposed matrix approximation approach with the exact calculation in terms of the execution time was carried out. The scaling of the parallel algorithm was studied. [ABSTRACT FROM AUTHOR]

This paper presents the integral equations of the direct problem of magnetic prospecting with respect to demagnetization. These equations are derived for a two-layer medium model. The method of determining the intensity of a secondary magnetic field for the case of magnetizing by a static field, which potential is a harmonic function, is described. The respective integral equations are written based on the theory of a simple layer potential. An iteration algorithm for solving the three-dimensional structural inverse problem of magnetic prospecting with respect to demagnetization for the sampled medium model is proposed based on the modified method of local corrections. For the method of local corrections, it is important to suggest that a change in the model field is mostly influenced by a change in the geometry of part of the object's boundary that is the nearest to the point of observation. The main feature of this algorithm allows us to get effective technique for solution of magnetic inverse problem for medium with any numbers of layers. [ABSTRACT FROM AUTHOR]

Based on a real-life example, the report presents the methodology and the process of adapting in situ measurements from static CPTu probing for an application in a design process, using direct methods of driven pile capacity estimation. The report discusses two approaches. One of them is based on a real-life original CPTu measurement involving preliminary soil assessment while the other one is based on the initial averaging of the measurement values qc and fs. The paper provides methods of averaging cone resistances (qc, qcsi, fsi), which become the input data for the algorithm of calculating the capacities of the pile side and its base. The authors focus on two most common methods of estimating pile capacity directly from a CPT measurement: the Philipponnat and the Bustamante-Gianeselli method. The issue of the maximum pile side resistance qs,k,i(max) is presented and illustrated graphically. The ranges of adopting averaging zones qc for pile base capacity assessment are provided for both methods together with the resultant differences. [ABSTRACT FROM AUTHOR]

The aim of the paper was both to present the possibility of use of the method of the search of space with specific features and identify the fragments with similar features. The described method was designed to automate the operation of original hybrid method in the field of space planning grouping of similar spatial parameters. Extremely useful seems to be here digitization of spatial data, underlying geographic information system. The hybrid method combines methods of spatial assessment and valuation (Bajerowski's method), numerical taxonomy (Ward's method) and axioms of the theory of planning spatial use (totality axiom). The article describes the principles of group planning space using the Ward's method. The algorithm was tested on one of the rural districts of Warmia and Mazury (Poland). The application demonstrated the effectiveness of the method in grouping the planning of homogeneous features. Assumptions of method are universal and can be used depending on purpose of the search by the wider group of stakeholders. [ABSTRACT FROM AUTHOR]

This paper deals with different approaches in the generation of weighted real-world graphs as the fundamental data structure for mathematical optimization algorithms. Based-on spatial data originating from the Austrian Digital Cadastral Map we examine three promising strategies to create valid graphs. The applicability of the constructed graphs is examined by solving the minimum Steiner tree problem as a typical representative in the design of wired communication networks. [ABSTRACT FROM AUTHOR]

In the paper we discuss the problem of fuzzy duplicate texts detecting. We give the basic methods and algorithms to detection of full and fuzzy text duplicates, such as Wagner and Fisher, Masek and Paterson, Ukkonen, suffix tree, Bitap, n-grams, shingles, hashing by signature, I-Match signature, TF*IDF etc. The characteristics of algorithms to fuzzy duplicate detections are shows. We review the existing systems of duplicate texts detecting used for Russian and English languages. The benefits and disadvantages of such systems are described. Existing systems checks text duplications only in the internal database or in the Internet. To better search, the system must operate with both types of sources. [ABSTRACT FROM AUTHOR]

Drastic change of land form and vegetation cover after flooding make riparian corridor surveys obsolete frequently. Advanced remote sensing technologies could be employed for the mapping and monitoring of stream renovation projects. The objective of this paper is to develop remote sensing technologies for the surveying and monitoring of the riparian topography and vegetation cover for our stream renovation project. Our tasks include wild habitat conservation for long-billed plover, reed warbler, egrets, leopard cat, and river otter. Land cover classification based on OOC was carried out by merging vertical data of LiDAR and spectral data of high resolution imagery of RGB and CIR band. Spatial resolutions for the LiDAR and digital imagery are 0.5m and 0.2m, respectively. First, Canopy Height of 0.5m resolution were produced based on DSM, DEM from the LiDAR data. Second, land cover map was produced with OOC algorithm. The categories include ground cover(tall grass, short grass), tree(Salix, Robinia), substrate(gravel, gravel/sand, sand, rock outcrop), and water surface. Overall accuracy 86% and correct tall grass, Robinia, sand/gravel. Plant height, NDVI and brightness from LiDAR and OOC algorithm enabled correct Salix, Robinia and tall grass. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a GIS based possibility for determining the possible location of lost tourist. To achieve this it uses Dijkstra algorithm on DEM as the fundamental algorithm. The novelty consists in developing a parameterized analysis algorithm with the corresponding user interface which takes account not only the DEM and the last seen position of the lost tourist, but also the land cover, the meteorological conditions and the fatigue of the person, based on his age and skill in hiking. [ABSTRACT FROM AUTHOR]

In this paper, we deal with analysis and evaluation of objects of interest which are present in ultrasound images as well as assessment of the progress or regressions that occurred in these objects. We focused on the analysis of mining images using active contours and Self-organizing migration algorithm (SOMA). Here, we describe procedures employing combination of common methods and evolutionary algorithms for recognizing points of interest in the images that may serve in determining various parameters and properties of analyzed objects. We use SOMA to optimize the energy function of deformable models used to approximate the locations and shapes of object boundaries. We suppose that SOMA can be used to find the desired global solution. Evolutionary algorithms are based on evolution principles found in nature and respect the Darwin`s theory of natural selection according to the defined cost function and gene recombination and mutation. As the computation of gradient vector flow field and also the evolution of active contour are computationally expensive, we investigate the suitability of the GPU for a parallel implementation. [ABSTRACT FROM AUTHOR]

The article presents a theoretical analysis of existing approaches to assessing threats to the state economic security. The analysis revealed three main methods for assessing economic security:a simple rationing method based on a threshold value, a complex rationing method based on a threshold value, a rationing method for amount of discrepancy. These methods, despite the presence of specific features, are implemented in a certain sequence.As a result of the synthesis of methodological approaches, the authors have formed an assessment algorithm (conducting a monitoring procedure) of threats to the state economic security. To study the analytical capabilities of the proposed assessment algorithm, the sequence of its application is considered on the example of the Russian Federation for the period from 2013 to 2017. The information base for the assessment was compiled by the World Bank, the Federal State Statistics Service, the Central Bank of the Russian Federation, Federal Customs Service of Russia. The calculated integral indicators of the state economic security for the relevant periods of time are properly interpreted; were identified factors that have a negative impact on the level of economic security of Russia.According to the authors, the combination of various methods (the indicative method, the method of normalized values, the integral method) makes it possible to ensure a certain adequacy of the assessment of the state economic security level. As a result, the analysis of the assessment results becomes the basis for the development by the federal authorities of a set of measures and mechanisms for ensuring economic security in the aspect of updating strategic documents. [ABSTRACT FROM AUTHOR]

In this article, mathematical and full-scale modeling of the application of the resistive control method based on the phase-metric principle of the controlling of the growth of suffosion processes is considered. The causes and stages of the growth of suffosion processes are given. Modeling of suffosion processes is carried out on the basis of the geoelectrical model of a spherical cavity of a covered thickness of soil sediments. The description is given of the experimental setup for modeling the suffosion processes and controlling their formation by the phase control method. Approbation of the proposed geoelectrical model of the geological environment and the phase control method was carried out at the site of the alleged development of suffosion processes caused by anthropogenic accident. A comparison of the results obtained was carried out with a given georadar and visual survey of the investigated area. The errors of mathematical modeling are revealed, the adequacy of the results is estimated. The presented models and the results obtained make it possible to create experimental electrical dependences close to real ones. This will contribute to the further development of the phase control method. [ABSTRACT FROM AUTHOR]

The algorithm for computation of the spectral characteristics of terrain was prepared. The periodicity of Earth surface is specific «fingerprint» of the cooperation of geological structure, exogenic processes and history of nature development for geomorphologically detached areas. For computing we used DEMs and 2D discrete Fourier transform with moving quadratic window of different sizes. Matrix of elevations decomposes in the Fourier image which defines harmonic waves set. All set of waves determine height field with absolute accuracy. However fixed part of waves allows reconstructing DEM with the different accuracy according to specific topographical situation. We can use this effect for landform classification. The follow characteristics was calculated: maximum of the waves magnitudes, the importance of given share of waves, the general direction of heights fluctuation, the severity of this direction, frequencies of the biggest wave by the orthogonal directions (W-E and S-N) and the general wavelength. The parameters of frequencies depends of window size (they are expressed in units/parts of window: 1/1, 1/2, 1/3 of window size and others). So we use only five parameters without frequencies for the classification. The used method of the landforms delineation on the Australia territory is Kohonen selforganizing maps (neural network). On the quadratic template net (15*15 neurons) we projected five-dimensional data and visualize the results as map of Sammon. On the finish we created the map of landforms types in Australia in the context of terrain periodicity. [ABSTRACT FROM AUTHOR]

3D model has been presented for numerical modeling of gravitational waves near the shoreline in this work. It consists of Navier-Stokes equation system, which includes three momentum equations and mass conservation law equation in region with dynamically varying boundaries. The variant of physical processes splitting method (the method of pressure correction) has been used to construct stable and conservative finite volume scheme. The adaptive alternating-triangular iterative method has been used for solving obtained grid equations with nonselfadjont operator in case of limited grid Peclet number. The numerical results have been compared to ones, obtained using the 2D wave model. It has been shown that presented 3D model gives more realistic description of physical wave process near the coastal line. The practical significance of constructed 3D model, numerical algorithm and the complex of programs consist in the possibility of its application for the study of hydrophysical processes in coastal water systems, as well as in assessing of the hydrodynamic effect on shore protection constructions and coastal structures in the presence of gravitational surface waves. [ABSTRACT FROM AUTHOR]

Modern socio-economic systems, as objects of management, are complex spatially distributed systems and territories, which indicates the need to develop and apply geoinformation management. Natural, man-made and social processes of territory development unfold in time and in space and are characterized by a variety of parameters described by a random vector. The components of the natural and climatic potential are random non-stationary processes, the study of which leads to the necessity of forming, according to the results of measurements, multi-factor models. Representation of the territory in the form of a multi-factor and multi-parameter model allows to study the patterns of behavior of the system, taking into account the complex influence of the main factors and parameters on the management of the system. In the article, we consider risk as an object of management and revealing the ratio of real losses (relative damages) and possible losses (risks) we find optimal management strategies. Territory management by the criterion of minimizing real and possible losses (risks) is an explicit or implicit time function specified in the form of a certain control algorithm. The used algorithms may be different, but they are represented by the functional dependence on the input effects and the initial state of the system. This method, based on the use of multi-parameter models, allows management taking into account the forecast of possible losses (risks) in time, which significantly improves the quality of management for social and economic systems. [ABSTRACT FROM AUTHOR]

The first results of using adaptive regression modeling (ARM-approach) in description of the latitude periodic change are analyzed. A multicomponent (polyharmonic) model of the latitude part observed dynamics containing between 14 and 21 harmonics requires interpretation and autoregressive forecasting of the 6th order providing high accuracy for the period of two years. This article provides the analysis, modeling, and forecasting of the latitude periodic change using the "Automated System for Robust Modeling" (ASRM-2017) package designed for geoprocessing and it is representing a system in which algorithms of time series analyzing and processing are implemented on the basis of adaptive regression modeling (ARM-approach). It is considered that in almost constant orientation of the Earth's rotation axis relative to "fixed stars" the Earth body moves around the axis of rotation. The points of intersection of the rotation axis with the surface of the Earth are geographic Earth's poles and they move on the Earth's surface since the Earth oscillates relative to its axis of rotation. According to the accepted terminology, this phenomenon is called periodic motion of the Earth's poles. The amplitude of the pole "swinging" on the circumpolar surface can reach a few dozens of meters. This is a significant value for today's practical applications depending on the quality of coordinate and time support. Therefore, the motion of the poles will certainly be taken into account in modern navigation, astrometry, geodesy, etc. The work also deals with the correlation between the Earth's pole motion and strong earthquakes. [ABSTRACT FROM AUTHOR]

Localisation and navigation are essential tasks for a mobile robot. If a mobile robot knows where it is, then it can make a plan to reach its destination. Localisation and navigation processes are not isolated from each other, they are closely linked. In fact, the ability for a mobile robot to localise itself is a basic requirement for reliable longrange autonomous navigation. Using sensory information about its environment, the mobile robot can perform actions dependent on this sensory information and navigate around. Although highly accurate localisation and mapping using low-cost hardware is very difficult, the emergence of new sensor technologies and development of state-of-the-art localisation and navigation algorithms help researchers and practitioners to realise their goals. In this study we evaluate the effects of speed and measurement variance on the accuracy of mobile robot localisation. As the results of our simulation studies prove, increasing speed and measurement variance of a mobile robot results in higher position error and velocity error. This indicates that high robot speed and high measurement variances may significantly reduce the accuracy of localisation algorithms. [ABSTRACT FROM AUTHOR]

An algorithm for extracting information on the types and subtypes of soils for each pixel of big data sets of remote sensing on agricultural lands is proposed. For this, a mathematical apparatus for constructing a multi-temporal (empirical) soil line is used. The classical soil line (SL) is defined in the RED-NIR spectral space by two coefficients "a" and "b" [2, 6, 9]. In this form, SL does not characterize soil types and subtypes. A multi-temporal soil line (MSL) is the major axis of an ellipse that describes all possible pairs of RED-NIR values that a pixel (resolution element) of remote sensing data corresponding to bare soil surface can take. MSL is specified in the spectral space by several (number N) coefficients. The resulting N-dimensional space of MSL coefficients makes it possible to give a unique characterization of each type and subtype of soils in the following zonal series: soddy podzolic, light gray forest, gray forest, dark gray forest, podzolized chernozems, leached chernozems. Dispersion analysis allows us to state that the soils of this series are statistically separated from each other in a set of MSL coefficients. That is, the MSL coefficients are characteristic of the type and subtype of the soils, and MSL is an empirical soil line (ESL) of the soil type and subtype. Classical SL is a collection of empirical soil lines of different soils on one remote sensing data scene. [ABSTRACT FROM AUTHOR]

The increase of transferred information amounts brings the need to create new automated systems for data recognition, classification and routing. It is impossible to solve such problems without modern machine learning technologies and artificial intelligence technologies. An algorithm that takes into account the linguistic and syntactic properties of documents, the characteristics of the subject area is formulated on the basis of the system approach to the analysis and decomposition of the task of document routing in the electronic document management system of scientific and educational institutions. This let to extract, process, and recognize senders and recipients of documents using machine learning methods with greater efficiency and accuracy. On the basis of the received data the subsystem of automatic routing of documents in system of electronic document management is formed. The obtained scientific results are applicable to the development of automatic routing systems in electronic document management systems. The presented approaches to the recognition and processing of recipients and senders of documents and text analysis are used to solve the problems of routing documents in various subject areas. [ABSTRACT FROM AUTHOR]