Software & Systems

Articles of journal № 2 at 2016 year.

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11. Methods and tools for analysing informative features when processing medical data [№2 за 2016 год]
Authors: Bykova V.V., Kataeva A.V.
Visitors: 10055
Many modern hospitals have information systems for storing medical data about their patients’ health. These data are for doctors to recognise (diagnose) pathological processes. However, experts face a problem of dimension in medical data analysis, detection of regularities in these data and their extraction. The dimension of stored data is determined by the number of different features that describe the health of the patient is very large and sometimes reaches several tens or hundreds of factors. Therefore, reducing the dimensionality of the feature space and selection of the most informative features is important for medical information systems. The article describes the problem of selection of informative features as a problem of combinatorial optimization. Its computational complexity is O (2n), where n is the initial number of features. The generalization of this problem with regard to the possibility of designing new factors based on the source features. The article gives a brief review of basic methods of sign space reduction, such as a principal component analysis and a method of extreme group of features. It also reviews statistical methods for estimating informative features used in medical diagnostics: the method of cumulative frequency, Shannon’s and Kullback’s methods. The application of these methods is demonstrated for diagnosing kidney disease. The article describes the program InformSigns, which implements all the statistical methods. InformSigns gives doctors a convenient interface for estimating informative features describing patients’ state of health. This complex can be integrated in specialized medical information systems for diagnostics of various pathological processes.

12. Modeling musical creativity using genetic algorithms based on GENOM platform [№2 за 2016 год]
Authors: Arutyunov V.O., A.N. Averkin
Visitors: 7653
The paper considers the problem of modeling musical creativity (M MC) using genetic algorithms (GA). During the work we designed and implemented a software system that represents a scalable platform for experiments on MMC. Implementation is limited by simulation of small monophonic melodies. The main efforts were directed to creating a platform that covers the majority of existing options for experiments and provides an opportunity to expand. The developed software includes a user interface with the ability to configure experiments, view scores and play the received melody, as well as a programming interface to extend the capabilities of the system. The implementation of the application is based on modern web technologies. It was developed with the help of a cross-platform free software (React, React-Router, Webpack, Bootstrap, Babel, Alt, ABCJS). The software product can be used as a tool for experimentation in MMC. In addition, the product can be used as a basis for creation of specialized solutions (including commercial) that use GA for MMT. The openness of the product and the possibility of extensions provides a possibility for its further improvement and use.

13. A model and algorithmization of the assignment problem under additional constraints [№2 за 2016 год]
Authors: Kordyukov R.Yu., Dopira R.V., Ivanova A.V., Abu-Abed, F.N., Martynov D.V.
Visitors: 10246
The article discusses the problem of optimal selection of candidates for working in tender projects based on financial conditions offered by candidates. It presents key criteria in selecting appropriate applications of candidates on the basis of pre-announced standards. The problem is formalized. The objective function is to minimize the costs for project implementation. The developed model aggregates the source data and constraints into one system and allows operating the initial conditions for their analysis. The authors offer a special algorithm for optimal appointment variants search based on the graph theory, the method of sequential analysis and option screening, as well as implicit enumeration. This algorithm takes into account the requirements for the applications of candidates. It works both in terms of the excistance of enterprises’ maximum and minimum financial constraints, and in their absence. It allows selecting performers for a complex project, which involves the successful completion of many individual projects in its composition. The developed software provides opportunities for creating a list of competitive projects, candidates for their implementation and their applications for certain types of work, taking into account the existing cost, time and probability limits. The algorithm searches all applications that meet the requirements of standards, then it determines the optimal selection among them, taking into account the performers’ possibilities of the acquisition of allocated resources.

14. Semantic relations in text classification based on Bag-of-words model [№2 за 2016 год]
Authors: Nugumanova А.B., Bessmertny I.A., Pecina P., Baiburin Е.M.
Visitors: 13629
The paper contains the results of research concerning quality improvement of automatic text classification based on statistical approach. It considers Bag-of-words model as a basis model of text representation. This is the most popular and the simpliest text representation model that is used in many tasks of automated language processing. The model represents texts as sets of words ignoring their order and relations. Therefore, the semantic similarity of two texts is assessed by a number of matching pairs of words. So, the texts containing few common words are meant to be semantically far from each other. Due to ignoring semantic links, this feature of Bag-of-words model creates a serious problem in such important task of natural language processing as automatic text classification. This paper proposes to enrich Bag-of-words model by semantic links from these texts extracted based on the joint word appearance statistics. Particularly, the contribution of this work consists in a new method of building and using of a semantic links matrix that is further used to display text representations to a space of linked words. The final purpose of this work is proving that the proposed model is more efficient in binary text classification than the traditional Bag-of-words approach. In order to compare these two models the authors carried out a set of experiments based on the standard Reuters 21578 texts collection. The results of the experiments demonstrate improvement of classification quality comparing to known methods.

15. Advansed design of a customer access network using an 8-tier model [№2 за 2016 год]
Author: Popkov G.V.
Visitors: 7924
The article discusses the aspects of design and optimization of building customer access networks taking into account urban development factors. It also shows disadvantages of modern access networks in a megapolis. Nowadays, telecommunication network operators often neglect the rules for laying cable lines in urban areas. It adversely affects the aesthetics of urban neighborhoods. It deteriorates the performance of customer access cable line sections, make technical operation and network management difficult. The paper describes a general approach to obtaining design solutions for customer access network design in metropolitan areas. The authors propose an 8-tier model of a promising access network to create a single primary communications network (SPCN). They also discuss the 8 levels of the model that completely define the design planes and construction of a customer access network in restrained urban conditions with challenging terrain and third-party engineering constructions. The paper offers a unified approach to constructing a cross-connect network at the primary level of the access network. It will allow flexibility provision of telecommunications services to secondary network operators anywhere in the city. The article shows possible ways and approaches, as well as typical tasks to be solved, which can applied to the optimization of the customer access primary network section using the mathematical apparatus of the graph theory and hypernetworks.

16. Building association rules in medical diagnosis [№2 за 2016 год]
Authors: Billig V.A., Ivanova O.V., Tsaregorodzev N.A.
Visitors: 10567
The article considers a new effective algorithm of creating association rules, which is called AprioriScale. The algorithm is applied to solving a particular medical diagnosis task. Implementation of the algorithm is in C# programming language. The developed programming tools provide doctors with the opportunity to carry out necessary research in the process of medical diagnosing. AprioriScale algorithm is a modification of the classic algorithm Apriori that is able to extract association rules from a database. An important feature of the developed algorithm is means of data presentation and creating associative rules. After long-term medical observations doctors have created a database containing data on the children suffering from severe diseases. Association rules extracted from this database make it possible to differentiate illnesses in an important field of pediatrics. The algorithm and programming tools may be used to solve different tasks both in medical diagnosis and in other applied fields.

17. Open software architecture for surgery training suites [№2 за 2016 год]
Authors: Ivaschenko A.V., Gorbachenko N.A., Kolsanov A.V.
Visitors: 6783
The evolution of modern surgical simulators considering the differences in educational tech nologies at different universities determines the relevance of software requirements, such as interoperability, open architecture and the ability to operate in a common information space. This paper describes the basic principles of software open architecture development for surgical simulators designed to teach surgery at medical universities. The paper focuses on the representation of surgical field objects and modeling their interaction with each other, which would provide an opportunity to create new training modules for surgical simulators. In order to create a distributed platform architecture for modeling operational cases the paper proposes using a design pattern “Entity – component”. Considering the specificity of logic for a particular operating case, the paper presents a hierarchy of interaction between software modules. As the example, the authors consider the algorithm of gripping an organ by a hard instrument with two jaws in an endoscope surgery simulation. In addition, the paper considers the basic principles of interaction between objects using the example of a training module endoscope clipping. The practical implementation results of the proposed approach prove that it can be used to describe various aspects of objects’ behavior in a scene within a unified architecture. It provides the flexibility to customize the behavior and active reuse of components. The proposed approach can reduce time and complexity of new surgical simulators development, as well as adapt existing simulation solutions for their implementation and practical application. This work was performed as a part of a project to create a software development kit (SDK) for medical community to deliver new simulation technologies in medicine with the possibility to exchange them in healthcare and medical education system (supported by the Ministry of Education and Science of Russian Federation (grant 2014-14-579-0003), contract 14.607.21.0007).

18. Preprocessing sets of precedents to construct decision functions in classification problems [№2 за 2016 год]
Authors: Gdansky N.I., Kulikova N.L., Krasheninnikov A.M.
Visitors: 8696
The article considers an important problem of errors in learning samples for subsequent construction using the method of solving functions precedents in problems of new objects classification. The paper researches the main causes of these errors and their impact on the construction of classifiers. Based on the geometric interpretation of a classification problem the authors propose methods to not only analyze the quality of a training sample, but also identify possible causes of the errors contained in it, as well as perform their correction required for the subsequent construction of an effective classifier. For numerical accounting of common emission lobes, which must be removed and corrected in a learning sample, the authors propose using the corresponding maximum allowable threshold values. There are some recommendations for the main subject areas. The algorithm of precedent analysis uses a special measure of single object proximity to an arbitrary class. It is similar to the method of the nearest neighbor with the difference that neighborhood is determined by not a nearest point but several points. The complexity of the proposed algorithms for analysis and correction of training sets is polynomial according to the number of points in the the learning sample. In the first case it is quadratic, in the second case it is linear. A new corrected training set sets smoother class boundaries in the space of characteristic values. Consequently, the data set of points to a greater extent satisfy the compactness hypothesis and give decision functions with a simpler structure, which requires less computing operations to solve the problem of classification.

19. Approximate reasoning based on temporal fuzzy Bayesian belief networks [№2 за 2016 год]
Authors: Borisov V.V., Zakharov A.S.
Visitors: 6251
The article considers the problem of approximate reasoning modeling under uncertainty. It describes a temporal fuzzy Bayesian network, which represents a Bayesian belief network, where preconditions of cause-effect relationships are complex temporal expressions; a statement truth measure is a fuzzy probability measure. A temporal fuzzy Bayesian network allows qualitative and quantitative setting of cause-effect relationships, taking into account temporal dependencies under conditions of stochastic and non-stochastic uncertainty. A result of approximate reasoning is a value of fuzzy probabilistic truth measure of a statement about finding a network node in one of its states. Moreover, the reasoning process is implemented as a sequential transition between moments of time and for each time moment implementing probabilistic inference in a temporal fuzzy Bayesian network. During the inference for each time moment when there are temporal dependencies we use reasoning results obtained at previous steps. To model approximate reasoning based on a temporal fuzzy Bayesian network the authors propose a method that allows to determine values of a fuzzy probability truth measure of statements during the forward and backward reasoning considering complex temporal dependencies. The proposed method is based, first, on the transformation of a fuzzy Bayesian network with complex temporal statements into a form containing only simple temporal statements. Second, it is based on the join tree construction according to the source fuzzy Bayesian network. Third, it is based on calculating fuzzy probability distribution by transmitting messages between join tree nodes, as well on a time constraint network to transmit messages through heterogenous join tree separators. The paper describes the developed software tools that implement the proposed model and the method of approximate reasoning. There are examples of using the developed model and method for analysing mental and emotional state of patients.

20. Decision assessment principles in the automated system of engineering product quality control [№2 за 2016 год]
Authors: Burdo G.B., Vinogradov G.P., Semenov N.A., Sorokin A.Yu.
Visitors: 9081
The features of multiproduct machinery production are primarily associated with a large number of different products under development and in progress simultaneously. It leads to time shortage while performing the stages of a product life cycle. In this regard, work staging at design and technological preproduction is violated; there are no clear criteria for product quality. It leads to non-predictable results (considering the quality of products). It should be noted that, as a rule, the first samples of high-tech products are created in the conditions that prolong the period of product launch due to the need of its improvement. Therefore, the importance of creating quality control automated systems becomes clear. It is known that in any situation of choice a quality of decision is determined by quality evaluation criteria of each of them. The task becomes more complicated when there are multiple stages of product evaluation. A separate aspect of product quality is assessed at each stage. However, at the same time these aspects (parameters) have a qualitative and quantitative influence on each other. Therefore, the article pays much attention to quality criteria. The paper presents the results of the research in the field of quality control automated systems in multiproduct machinery production. It also considers the principles of choice of product quality evaluation criteria, provides a set of quality evaluation criteria developed on the basis of these principles. The paper shows a decision-making mechanism in the system on the basis of production models and Petri nets.

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