Category: Issue 1 (211)

Issue 1 (211), article 7

DOI:https://doi.org/10.15407/kvt211.01.090

Cybernetics and Computer Engineering, 2023, 1(211)

VOLKOV O.Ye.¹, PhD (Engineering), Senior Researcher, Director
https://orcid.org/0000-0002-5418-6723 ,
e-mail: alexvolk@ukr.net

SHEPETUKHA Yu.M.¹, PhD (Engineering), Senior Researcher,
Leading Researcher of the Intelligent Control Department
https://orcid.org/0000-0002-6256-5248
e-mail: yshep@meta.ua

PAVLOVA S.V.², DSc (Engineering), Professor,
Professor of School of Software
e-mail: dep185@irtc.org.ua

BOGACHUR Yu.P.¹, PhD (Engineering), Senior Researcher,
Leading Researcher of the Intelligent Control Department
https://orcid.org/0000-0002-3663-350X ,
e-mail: dep185@irtc.org.ua

¹International Research and Training Center for Information
Technologies and Systems of the National Academy of Sciences of Ukraine
and the Ministry of Education and Science of Ukraine,
40, Akad. Glushkov av., Kyiv, 03187, Ukraine

²Shanxi Agricultural University
81, Longcheng str., Xiaodian Taiyuan, Shanxi, 030031, China

TO 90th ANNIVERSARY OF PROFESSOR VADIM PAVLOV: A CONCISE REVIEW OF THE MAIN RESULTS FOR 50 YEARS OF SCIENTIFIC ACTIVITY

The article sums up the main results of scientific activity of Professor Vadim Pavlov (1933–2016) – a famous scholar in the field of control theory and its applications. A monography “Invariance and Autonomy in Non-linear Systems” describes an approach to solving problems of poli-invariance and poli-autonomy by the method of forced separation for the systems of differential equations. A monography “Foundations of ergatic systems theory” is based upon the concept of “organismic approach” that unites into a single whole the general principles of both control theory and the one of a living systems. Taking organismic principles into consideration gives a possibility to structure a man-machine interaction in such a way that uses comparative advantages of humans as well as computerized technical means. 

In a monograph “Conflicts in technical systems”, it has been grounded that ergatic theory could be successfully applied for solving conflicts in technical systems of different levels. Concept of active interaction with the environment determines a capability to formulate general principles for ergatic system’s operation in conflict conditions.  In the last period of life, Prof. Pavlov, on the grounds of systematization as well as generalization of his previous endeavors, had been conducting research directed at the creation of both conceptual and mathematic fundamentals of intelligent control. In his last monograph “Intelligent control of complex non-linear dynamic systems: analytics of intelligence”, intelligent control is defined as a human activity connected with solving tasks of sensing, comprehension, reasoning and execution of a necessary interaction with the object. 

Within the frames of research in intelligent theory field, Prof. Pavlov had also conducted works related to creation of methods as well as technologies for image-based control of complex dynamic objects and processes. This technology has been used in control systems for sea ships and aircrafts operating in complicated navigational conditions and critical working modes. In this context, it is necessary to distinguish a number of “AntiCon” (abbreviation for “anti-conflict”) systems developed within the frames of Ukrainian Academy of Sciences‘ research programs and aimed at solving conflict situations and provision the safe movement of sea vessels. 

Finally, it is reasonable to pay attention to the vision of Prof. Pavlov related to further development of research in the field of intelligent control as well as elaboration of goal-directed systems. The author stressed that the task of non-linear object’s control taking into consideration specific feature of a human and computer had been at the stage of formation. Therefore, a primary attention should be paid to the development of theoretical fundamentals of integrated intelligent control with a full usage of system’s non-linear technological resource.

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REFERENCES

1 Pavlov V.V. Invariance and Autonomy in Non-linear Systems. Kyiv: Naukova dumka, 1971, 272 p.

2 Malinovsky B.N. Academician V. Glushkov. Kyiv: Naukova dumka, 1993, 144 p.

3 Pavlov V.V. Fundamentals of ergatic systems theory. Kyiv: Naukova dumka, 1975, 240 p.

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7 Pavlov V.V. Conflicts in technical systems. Kyiv: Vyshcha shkola, 1982, 184 p.

8 Pavlov V.V., Pavlova S.V. Intelligent control of complex non-linear dynamic systems: analytics of intelligence. Kyiv: Naukova dumka, 2015, 216 p.)

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10 Pavlov V.V. Synthesis of strategies in man-machine systems. Kyiv: Vyshcha shkola, 1989, 162 p.

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12 Pavlov V.V., Pavlova S.V., Bohachuk Y.P. Method and apparatus for computer networks of application process high-speed cycles control. Patent 83118 Ukraine, Int.Cl. (2006) H04L 12/66 G05B 15/02 G05B 17/00, 2008.

Received 05.01.2023

Issue 1 (211), article 6

DOI:https://doi.org/10.15407/kvt211.01.077

Cybernetics and Computer Engineering, 2023, 1(211)

KOVALENKO O.S., DSc (Medicine), Professor,
Head of the Medical Information Systems Department
https://orcid.org/0000-0001-6635-0124 ,
e-mail: askov49@gmail.com

KOZAK L.M., DSc (Biology), Senior Researcher,
Leading Researcher of the Medical Information Systems Department
https://orcid.org/0000-0002-7412-3041 ,
e-mail: lmkozak52@gmail.com

KRYVOVA O.A.,
Researcher of the Medical Information Systems Department
https://orcid.org/0000-0002-4407-5990 ,
e-mail: ol.kryvova@gmail.com

BYCHKOV V.V., DSc (Medicine),
Senior Researcher of the Medical Information Systems Department
https://orcid.org/0009-0004-8385-9925 ,
e-mail: vvb0949@gmail.com

NENASHEVA L.V.,
Junior Researcher of the Medical Information Systems Department
https://orcid.org/0000-0003-1760-2801 ,
e-mail: larnen@ukr.net

International Research and Training Center for Information
Technologies and Systems of the National Academy of Sciences
of Ukraine and Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine

APPLICATION OF CLASSIFICATION MODELS BY DATA MINING
AND INFORMATION TECHNOLOGY FOR ANALYZE
THE RESULTS OF TREATMENT OF CARDIAC AND DIABETIC PATIENTS

Introduction. In recent years, the scientific community, especially in the medical field, has been putting a lot of efforts and resources into the development of eHealth technologies and systems. Various methods of intellectual support, which are necessary to ensure high quality of medical care, have been developed. The study of the effectiveness of the application of various methods of diagnosis, treatment of patients and restoration of their health is one of the important components of the assessment of the quality of medical care.

The purpose of the paper is to analyze the results of providing medical care with the use of developed models based on Data Mining methods to identify factors that affect the results of treatment.

The results. A method of estimating the medical care results using Data Mining methods has been developed, the feature of which is the combination of filtering algorithms, clustering and classification methods. Models of the medical care result depending on significant factors were built. To test the developed method, a retrospective analysis was carried out using a database of hospital patients of various departments of clinical facilities. The distribution of treatment results evaluation (according to the standardized formulation) of cardiac and diabetic patients was obtained, and concomitant diseases and complications were analyzed. A model for determining the factors influencing the treatment outcome, based on the decision tree method (CART), has been developed. Analysis of the decision tree structure makes it possible to draw conclusions about the decision-making logic by a specific doctor. With the help of decision tree models, the relationship between complications, the main diagnosis and other factors, in particular, concomitant diagnoses, recurrence of hospitalization etc., was analyzed.

Conclusions. The combination of statistical methods and the developed method and models based on Data Mining (a decision tree calculated according to the CART algorithm and 10-fold cross-validation) for  analysis of medical hospital databases made it possible to identify the frequency characteristics of concomitant diseases and complications typical for cardiac and diabetic patients, and also allowed to determine the main factors that depend on the decision-making by doctors about the outcome of treatment.

Keywords: eHealth, Data Mining methods, CART algorithm, information technology, treatment outcomes

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REFERENCES

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2. Ossebaard HC, Van Gemert-Pijnen L. eHealth and quality in health care: implementation time. Int J Qual Health Care. 2016 Jun;28(3):415-419. [doi: 10.1093/intqhc/mzw032]
https://doi.org/10.1093/intqhc/mzw032

3. Tossaint-Schoenmakers R., Versluis A., Chavannes N., Talboom-Kamp E., Kasteleyn M. The Challenge of Integrating eHealth Into Health Care:Systematic Literature Review of the Donabedian Model of Structure, Process,and Outcome. J Med Internet Res. 2021;23(5):e27180 doi: 10.2196/27180
https://doi.org/10.2196/27180

4. Triberti S., Savioni L., Sebri V., Pravettoni G. eHealth for improving quality of life in breast cancer patients: A systematic review. Cancer Treatment Reviews, 2019, Vol. 74, pp. 1-14.
https://doi.org/10.1016/j.ctrv.2019.01.003

5. Rybarczyk-Szwajkowska А., Marczak M. Quality assessment of health care services in patients and medical staff opinion. January 2011. URL: https://www.researchgate.net/ publication/273335138_Quality_assessment_of_health_care_services_in_patients_and_medical_staff_opinion

6. Legido-Quigley H., McKee M., Walshe K., Suñol R., Ellen Nolte E., Klazinga N. How can quality of health care be safeguarded across the European Union? BMJ. 2008 Apr 26; 336(7650): 920-923. doi: 10.1136/bmj.39538.584190.47
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7. ASA physical status classification system. URL: https://www.asahq.org/standards-and-guidelines/asa-physical-status-classification-system

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11. Formalized assessment of the patient’s condition using scales for major internal diseases. Zaporizhzhia state medical university. 2015, 79 p. (in Ukrainian).

12. Rogach I.M., Slabky G.O., Kachala L.O. et al. Quality control of medical care at the level of a health care facilities. Guidelines. Uzhgorod: MES of Ukraine, 2014, 48 p. (in Ukrainian).

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16. Kisekka V., Giboney J. S. The Effectiveness of Health Care Information Technologies: Evaluation of Trust, Security Beliefs, and Privacy as Determinants of Health Care Outcomes. J Med Internet Res. 2018, V.20, №4, pp. 1-11.
https://doi.org/10.2196/jmir.9014

17. Kushniruk A., Hall S., Baylis T., Borycki E., Kannry J. Approaches to demonstrating the effectiveness and impact of usability testing of healthcare information technology. Studies in health technology and informatics. 2019, 257, pp. 244-249.

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20. Houthooft R., Ruyssinck J., van der Herten J., et al. Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores. Artif Intell Med. 2015;63:191-207.
https://doi.org/10.1016/j.artmed.2014.12.009

Received 26.12.2022

Issue 1 (211), article 5

DOI:https://doi.org/10.15407/kvt211.01.064

Cybernetics and Computer Engineering, 2023, 1(211)

Chepizhenko V.I.¹, DSc (Engineering), Senior Research,
Leading Researcher of the Intellectual Control Department.
https://orcid.org/0000-0001-8797-4868,
e-mail: chepizhenko.valeriy@gmail.com

Pavlova S.V.², DSc (Engineering), Professor,
Professor of School of Software
https://orcid.org/0000-0002-6256-5248 ,
e-mail: pavlova_2020@ukr.net

Skyrda I.I.³, PhD (Engineering),
Aviation Communication, Navigation and Surveillance expert (CNS expert)
https://orcid.org/0000-0002-9363-8921 ,
e-mail: skyrda2@gmail.com

¹International Research and Training Center for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine.
40, Akad. Glushkov ave., Kyiv, 03187, Ukraine.

²Shanxi Agricultural University
81, Longcheng str., Xiaodian Taiyuan, Shanxi, 030031, China.

³EUROCONTROL
Rue de la Fusée, 96, Brussels, 1130, Belgium

TRAJECTORY MOVEMENT CONTROL OF UNMANNED AERIAL VEHICLES IN A SWARM

Introduction. Today, the use of swarms of unmanned aerial vehicles (UAVs) is effective for solving the tasks of monitoring large areas of the earth’s surface and infrastructure objects, processing large areas of agricultural land, digital mapping, designing land objects in 3D, planning and designing construction works, road surface monitoring, etc. An important issue here is the potential for simultaneous conflicts between unmanned aerial vehicles moving in a swarm.

The purpose of the work is to develop a scalable, flexible method of controlling the trajectory of unmanned aerial vehicles in a swarm based on the approach of artificial potential fields.

The results. The developed method has properties of scalability and flexibility. The method contains a simple control algorithm, that allows several UAVs to fly as part of a swarm along a given trajectory, while solving the task of resolving conflict situations (preventing collisions between swarm members and with static and dynamic obstacles). The proposed method consists in decentralized real-time management of the swarm. The simulation results show that the method, presented in the article, increases the efficiency of swarm formation and flight performance, as well as UAV collision avoidance.

Conclusions. The proposed method scales well and is suitable for controlling a swarm of different sizes, it can also be applied to control a swarm of UAVs with different flight characteristics, since the formation of the resulting motion vector does not depend on the specific technical characteristics of the UAV, but takes into account certain limitations.

Keywords: unmanned aerial vehicle, modified artificial potential fields, UAV swarm, collision avoidance.

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REFERENCES

1. A. Benghezal, R. Louali, A. Bazoula, T. Chettibi. Trajectory generation for a fixed-wing UAV by the potential field method. 3rd International Conference on Control, Engineering & Information Technology (CEIT). Tlemcen. 2015. P. 1-6. DOI: 10.1109/CEIT.2015.7233049
https://doi.org/10.1109/CEIT.2015.7233049

2. Chen, H., Yin, Ch., Xie, L. Automatic Discovery of Subgoals Sequential Decision Problems Using Potential Fields. Conference Paper in Communications in Computer and Information Science. 2007. DOI: 10.1007/978-3-540-74282-1_66.
https://doi.org/10.1007/978-3-540-74282-1_66

3. Y. U. Cao, A. S. Fukunaga, A. B. Kahng. Cooperative Mobile Robotics: Antecedents and Directions. Autonomous Robots. 1997. V.4. P. 1-23.

4. H. C. Hsu, A. Liu. Applying a Taxonomy of Formation Control in Developing a Robotic System. IEEE International Conference on Tools with Artificial Intelligence. 2005. P. 3-10.

5. D. Galzi, Y. Shtessel. UAV formations control using high order sliding modes. American Control Conference. Minneapolis. MN. 2006. P. 6. DOI: 10.1109/ACC.2006.1657386
https://doi.org/10.1109/ACC.2006.1657386

6. Y. Huang, J. Tang, S. Lao. UAV Group Formation Collision Avoidance Method Based on Second-Order Consensus Algorithm and Improved Artificial Potential Field. Symmetry 11(9):1162. 2019. DOI: 10.3390/sym11091162.
https://doi.org/10.3390/sym11091162

7. H. Yin, L. Cam, U. Roy. Formation control for multiple unmanned aerial vehicles in constrained space using modified artificial potential field. MATHEMATICAL MODELLING OF ENGINEERING PROBLEMS. 2017. V.4. P. 100-105. DOI: 10.18280/mmep.040207.
https://doi.org/10.18280/mmep.040207

8. L. Chaimowicz, V. Kumar. Aerial Shepherds: Coordination among UAVs and Swarm Robots. International Symposium on Distributed Autonomous Robotic Systems 2004.

9. P. Kostelnik, M. Samulka, M. Janosik. Scalable multi-robot formations using local sensing and communication. Proceedings of the Third International Workshop on Robot Motion and Control.2002. P. 319-324.

10. N. E. Leonard, E. Fiorelli. Virtual leaders, artificial potentials and coordinated control of groups. Proceedings of the IEEE Conference on Decision and Control. 2001. P. 2968-2973.

11. K. Sugihara, I. Suzuki. Distributed algorithms for formation of geometric patterns with many mobile robots. Robot Systems. 1996. V. 13.
https://doi.org/10.1002/(SICI)1097-4563(199603)13:3<127::AID-ROB1>3.0.CO;2-U

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13. Y. Koren and J. Borenstein. Potential field methods and their inherent limitations for mobile robot navigation. Proceedings of IEEE International Conference on Robotics and Automation 1991.

14. Ch. Huang, W. Li, Ch. Xiao, B. Liang, S. Han, Songchen. Potential field method for persistent surveillance of multiple unmanned aerial vehicle sensors. International Journal of Distributed Sensor Networks. 14. 2018. DOI: 10.1177/1550147718755069.
https://doi.org/10.1177/1550147718755069

15. V. Kharchenko, V. Chepizhenko, S. Pavlova. Synergy of Piloted, Remotely Piloted and Unmanned Air Systems in Single Air Navigation Space. 2016. DOI: 10.13140/RG.2.1.1502.8885.

16. I. Skyrda. Decentralized Autonomous Unmanned Aerial Vehicle Swarm Formation and Flight Control. Information and Communication Technologies in Education, Research, and Industrial Applications. 14th International Conference, ICTERI 2018. Kyiv, Ukraine, May 14-17, 2018, Revised Selected Papers.2018. P. 197-219. DOI 978-3-030-13929-2
https://doi.org/10.1007/978-3-030-13929-2_10

17. W. Kang, N. Xi, Y. Zhao, J. Tan, Y. Wang. Formation control of multiple autonomous vehicles: Theory and experimentation. Proceedings of IFAC 15th Triennial World Congress. 2002.
https://doi.org/10.3182/20020721-6-ES-1901.00091

18. N. Leonard, E. Fiorelli. Leaders, artificial potentials and coordinated control of groups. Conference on Decision and Control. 2001.

Received 12.01.2023

Issue 1 (211), article 4

DOI:https://doi.org/10.15407/kvt211.01.051

Cybernetics and Computer Engineering, 2023, 1(211)

BONDAR S.O.,
Acting Head of Intelligent Control Department,
https://orcid.org/0000-0003-4140-7985 ,
e-mail: seriybrm@gmail.com

International Research and Training Center for Information
Technologies and Systems of the National Academy of Science and Ministry of Education and Science of Ukraine.
40, Acad. Glushkov ave., 03187, Kyiv, Ukraine

USAGE OF HIGH-FREQUENCY POSITIONING OF THE HYBRID UNMANNED AERIAL VEHICLE FOR AUTOMATIC LOCATION ADJUSTMENT UNDER
LIMITED LOCATION CIRCUMSTANCES

Introduction. Diversity of missions that could be perfectly performed by unmanned aerial vehicles generates demand for something more optimized and flexible than just a scheme “one aircraft for one mission”. Complex tasks are also not a seldom fact at modern civil and military operation. So technologies are providing brand new types of precise hybrid unmanned aerial vehicles that could take mission accomplishing tasks to the next level and provide much more pertinent way for each mission performance using just one aircraft for tasks that have only one fundamental thing in common – they needed to be done in the sky. 

The purpose of the paper is to justify usage of a hybrid unmanned aerial vehicle for the performance during multitasking missions instead of a larger number of aircrafts of the airplane and helicopter type.

Results. The article describes specific variants of scenarios for the use of unmanned aerial vehicles, as well as a unit for adjusting the position of the aircraft, which also allows to improve the accuracy of the aircraft control and therefore the accuracy of performing tasks with such equipment, which opens up a large space for the use of such equipment and reduces the need for the presence of several equipment for such task execution, which, in turn, increases economic efficiency during the usage of a more complex device. The article consists of algorithm description that adjust the position of the aircraft along the axes, as well as a description of the tasks for which such aircrafts are designed and used

Conclusion. The use of more complex equipment with more on-board electronics can be justified during  tasks performing with a large number of tasks and during the multiple operation of the aircraft ensuring itself. The number and direction of the tasks justifies the appearance of hundreds of aircraft in service in civil and military organizations in Ukraine. The operation of such devices can completely change the task performance approach at aerial photography, positioning, digitization of objects, as well as the implementation of a whole range of military tasks.

The result of the work on current stage is unmanned aerial vehicle location adjustment unit algorythms structure by all three axis, as well as a selection of scenarios, in particular those simulated in a training environment, for which the use of hybrid unmanned aerial vehicles equipped with such a unit is the most optimal option. 

Keywords: unmanned aerial vehicle, hybrid aircraft, control module, autopilot

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REFERENCES

1. Adnan S. Saeed, Ahmad Bani Younes, Chenxiao Cai, Guowei Cai A Survey of Hybrid Unmanned Aerial Vehicles https://www.sciencedirect.com/science/article/abs/pii/ S0376042117302233

2. GT20 Gyrotrak by Airial Robotics Makes Debut at New York’s FAA-Designated UAS Test Site // GeniusNY http://www.geniusny.com/news/gt20-gyrotrak-by-airial-robotics-makes-debut-at-new-yorks-faa-designated-uas-test-site

3. Bondar S.O., Schepetukha Yu.M., Voloscheniuk D.O. Using of high-quality positioning tools for hybrid Unmanned aerial vehicles automatic correction under the Limited space condition Cybernetics and Computer Engineering, 2022, vol.2(208), pp. 44-59.
https://doi.org/10.15407/kvt208.02.044

4. Pircher M., Geipel J., Kusnierek K., Korsaeth A. Development of a hybrid uav sensor platform suitable for farm-scale applications in precision agriculture https://www.researchgate.net/publication/319411305_development_of_a_hybrid_uav_sensor_platform_suitable_for_farm-scale_applications_in_precision_agriculture, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W6-297-2017

5. QP532 Hybrid eVTOL Drone Long-endurance hybrid UAV for inspection and mapping https://www.unmannedsystemstechnology.com/company/aheadx/qp532-hybrid-evtol-drone/

6. Miriam McNabb Hybrid Electric UAV from Advanced Aircraft Systems: HAMR UAVs Selected by AFWERX https://dronelife.com/2022/02/14/hybrid-electric-uav-from-advanced-aircraft-systems-hamr-uavs-selected-by-afwerx/

7. Emma Helfrich, Roy Choo Meet Australia’s Home-Grown ‘STRIX’ VTOL Combat Drone Concept https://www.thedrive.com/the-war-zone/meet-australias-home-grown-strix-vtol-combat-drone-concept

8. Hybrid UAVs: The Advent of Responsive Combat Capability https://chanakyaforum.com/hybrid-uavs-the-advent-of-responsive-combat-capability/

9. Unmanned aerial aircraft usage features for detail preciseness during the cartography developments. XIV International Scientific and technical conference “Avia-2019”, Kyiv 2019. pp. 51-52.

10. Bowen Zhang, Zaixin Song, Fei Zhao, Chunhua Liu Overview of Propulsion Systems for Unmanned Aerial Vehicles. – MDPI, 2022.
https://doi.org/10.3390/en15020455

11. Beard R.W., McLain T.W. Small Unmanned Aircraft: Theory and Practice. Princeton: Princeton Univ. Press, 2012. 320 p.
https://doi.org/10.1515/9781400840601

12. Bondar S, Simakhin V, Semenoh R, Suslova T. Usage of unmanned aerial vehicle groups to perform attack, support, communication and evacuation operations of front-line military units during active hostilities 1370th International Conference on Recent Innovations in Engineering and Technology, Oxford, United Kingdom ISD-RIETOXFO-190922-23065

13. Park S., Deyst J., How J.P. A New Nonlinear Guidance Logic for Trajectory Tracking, Navigation and Control Conference: proceedings of the AIAA Guidance, Aug.2004. AIAA-2004-4900.
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14. Small Unmanned Aircraft Systems (SUAS) Flight Plan 2016-2036 / Headquarters United States Air Force, 2016

15. Marco Fioriti, Silvio Vaschetto, S. Corpino, Giovanna Premoli Design of hybrid electric heavy fuel MALE ISR UAV enabling technologies for military operations. Aircraft Engineering and Aerospace Technology, Volume 92 Issue 5, February 2020.
https://doi.org/10.1108/AEAT-05-2019-0109

16. Hrytsenko V.I., Volkov O.E., Komar M.M., Bogachuk Yu.P. Intellectualization of modern systems of automatic control of unmanned aerial vehicles. Cybernetics and Computer Engineering, 2018. No. 1. P. 45-59.(in Ukrainian)
https://doi.org/10.15407/kvt191.01.045

17. Volkov O.E., Hrytsenko V.I., Komar M.M., Volosheniuk D.O. Integral Adaptive Autopilot for an Unmanned Aerial Vehicle. AVIATION, 2018.Vol. 22. Issue 4. pp. 129-135.
https://doi.org/10.3846/aviation.2018.6413

18. Lockheed Martin designs 3-tone UAV with flying range up to 920 km. Sundries: news, technologies, society. https://sundries.com.ua/lockheed-martin-proiektuie-3-tonnyi-bpla-z-dalnistiu-polotu-920-km/

Received 11.01.2023

Issue 1 (211), article 3

DOI:https://doi.org/10.15407/kvt211.01.040

Cybernetics and Computer Engineering, 2023, 1(211)

ZOSIMOV V.V., DSc (Engineering), Associate Professor,
Professor of the Department of Applied Information Systems,
https://orcid.org/0000-0003-0824-4168,
e-mail: zosimovv@gmail.com

Taras Shevchenko National University of Kyiv,
60, Volodymyrska st., Kiyv, 01033, Ukraine

PROBABALISTIC APPROACH TO RANKING SEARCH RESULTS USING BAYESIAN BELIEF NETWORKS

Introduction. This paper proposes a probabilistic approach to ranking search results using Bayesian Belief Networks (BBN). The proposed approach utilizes BBN to model the relationships between search queries, web pages, and user feedback, and to calculate the probability of a web page being relevant to a specific query. The approach takes into account various factors, such as keywords, page relevance, domain authority, and user feedback to generate a ranking score for each search result. 

The purpose of the article is to conduct an analysis on the feasibility of creating a search engine that uses BBNs and probabilistic ranking methods for improving the accuracy and efficiency of search results.

Results. The proposed approach was evaluated on a real-world dataset, and the results showed its effectiveness. Overall, the results suggest that the use of BBNs can provide a promising approach to enhancing search engine performance and user experience. The approach’s effectiveness is attributed to its ability to model and reason about uncertainty and dependencies among variables, and its consideration of various factors, such as keywords, page relevance, domain authority, and user feedback.

Conclusions. The proposed method has the potential to improve search relevance, reduce user frustration, and increase user satisfaction. However, further research is needed to optimize the proposed approach and to explore its applicability in different contexts. Overall, the study suggests that BBNs can provide a valuable tool for developing more effective and user-friendly search engines. Moreover, the use of Sphinx as a base search system shows promise in enabling the proposed approach to be integrated into practical search systems. Nonetheless, further research is needed to optimize the approach and evaluate its applicability in different contexts.

Keywords: search engine, ranking, Bayesian Belief Networks, probabilistic model, information retrieval.

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11 Guo C. Deep Bayesian active learning for neural networks. Journal of Machine Learning Research, JMLR.org. 2017, Vol. 18, pp. 1-47.

12 Sattari P. Bayesian deep reinforcement learning: A survey. Journal of Machine Learning Research, JMLR.org. 2020, Vol. 21, pp. 1-35.

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14 Official Sphinx search system site. URL: Sphinx http://www.sphinxsearch.com/

Received 23.01.2023

Issue 1 (211), article 2

DOI:https://doi.org/10.15407/kvt211.01.029

Cybernetics and Computer Engineering, 2023, 1(211)

KRYGIN V.M.¹, PhD Student,
Junior Researcher of Pattern Recognition Department,
https://orcid.org/0000-0002-9000-1685 ,
e-mail: valeriy.krygin@gmail.com

KHOMENKO R.O.²,
Programmer
https://orcid.org/0000-0001-7640-4077 ,
e-mail: ruslank3584@gmail.com

MATSELLO V.V.¹, PhD (Engineering), Senior Researcher,
Head of Pattern Recognition Department
https://orcid.org/0000-0001-7640-4077 ,
e-mail: matsello@gmail.com

¹International Research and Training Center for Information
Technologies and Systems of the National Academy of Sciences
of Ukraine and Ministry of Education and Science of Ukraine,
40, Acad. Glushkova av., Kyiv, 03187, Ukraine

²Postindustria Inc.,
1935 Walgrove av., Los Angeles CA 90066, USA.

EXPERIMENTAL VERIFICATION OF THE SELF-DRIVEN ALGORITHMS FOR SOLVING MAX-SUM LABELING PROBLEMS

Introduction. Max-sum labeling problems play an essential role in modern pattern recognition and can be used with other methods and a stand-alone approach. An essential step in building a pattern recognition system is the choice of an algorithm to solve the problem, which may require experimentation with different algorithms. This fires a need for software that allows solving different problems with the help of different algorithms for further analysis of the results of experiments and the final selection of the algorithm.

The purpose of the paper is to demonstrate the capabilities of the developed software for solving max-sum labeling problems.

Results. The software containing various algorithms for solving max-sum labeling problems was developed and experimentally tested. The program operation is shown on the example of image processing problems based on labeling: color image restoration, binary image denoising, posterization and binocular stereo vision.

Conclusions. The software described in the article verifies in practice the correctness of the self-driven algorithm for solving max-sum labeling problems. The application allows the operator to choose an algorithm for the labeling task and configure its parameters. This program will be helpful for developers of computer vision systems based on labeling problems and under-graduates, graduate students, and researchers studying structural pattern recognition methods.

Keywords: labeling problems, pattern recognition, computer vision, software.

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Received 02.01.2023

Issue 1 (211), article 1

DOI:https://doi.org/10.15407/kvt211.01.005

Cybernetics and Computer Engineering, 2023, 1(211)

ODARCHENKO R.S.¹, DSc (Engineering), Professor,
Head of the Telecommunication and Radio Electronic Systems Department
https://orcid.org/0000-0002-7130-1375 ,
e-mail: odarchenko.rs@ukr.net

BONDAR S.O.², Acting Head of Intelligent Control Department, Researcher
https://orcid.org/0000-0003-4140-7985 ,
e-mail: seriybrm@gmail.com

SIMAKHIN V.M.², Ph.D. student,
Researcher of Intelligent Control Department
https://orcid.org/0000-0003-4497-0925 ,
e-mail: thevladsima@gmail.com

SIERIEBRIAKOV A.K.², PhD student,
Researcher of Intelligent Control Department
https://orcid.org/0000-0003-3189-7968 ,
e-mail: sier.artem1002@outlook.com

PINCHUK A.D.¹, Student
https://orcid.org/0000-0003-3567-0445 ,
e-mail: pinchuk.ad87@gmail.com

SAMOILENKO V.V.¹, Student
e-mail: vladss1954@gmail.com

STANKO P.O.³, PhD (Engineering),
Associate Professor of the Information Technologies Department
https://orcid.org/0000-0001-5794-3593
e-mail: p_stanko@ukr.net

¹National Aviation University,
1, av. Lubomyra Huzara, 03058, Kyiv, Ukraine

²International Research and Training Center for Information
Technologies and Systems of the NAS and MES of Ukraine,
40, av. Acad. Glushkov, 03680, Kyiv, Ukraine

³University of New Technologies,
5A, st. Metrobudivska, 03065, Kyiv, Ukraine

RESEARCH OF THE MAIN MEANS AND INTERMEDIATE RESULTS OF THE RUSSIAN-UKRAINIAN CYBERWAR: CYBERVOLUNTEER INITIATIVES

Introduction. This research paper examines the current state of cyberwarfare in the world. The issues regarding definition of the very term “cyberwar” are discussed. The historical beginning of the Russian-Ukrainian cyberwar, its course and current state are considered, as well as the main means of its conduct are examined. It has been determined that this cyberwar was the world’s first full-scale global cyberwar. The main attention is paid to the cybervolunteer IT army of Ukraine, which appeared in the course of this cyberwar and is successfully combating with the russian federation on the cyberfront.

The purpose of the article  is to show the process of waging a real cyberwar today, the application of the means for its carrying out, and conduct a study of its intermediate results; using Ukraine as the example to show the efficiency and effectiveness of the work of cybervolunteer initiatives.

The results. An analysis of the main existing approaches to conducting cyberwarfare was carried out, and the types of cyberattacks that are most often used were determined. It has been determined which directions and means of conducting cyberspace the russian federation focuses on. The IT activities of the Ukrainian army were studied, the key areas of work were determined and their detailed classification was given. In the course of the study, the main indicators of the effectiveness of the cyberarmy of Ukraine were determined and statistical data on the work of key areas were collected, on the basis of which the efficiency, effectiveness and problems that arise during the fight on the cyberfront were analyzed.

Conclusions. For the first time, the process of waging the Russian-Ukrainian cyberwar was examined in detail, with an emphasis on the activities of cybervolunteer initiatives of Ukraine. Determining the key areas of their activity made it possible to investigate the effectiveness and determine the intermediate results of this cyberwar. After analyzing all the data, recommendations were made to improve efficiency and effectiveness in the fight on the cyberfront.

Keywords: cyberfront, cyberwar, approaches to waging cyberwars, cyberweapons, Russian-Ukrainian cyberwar, cybervolunteer initiatives, IT Army of Ukraine.

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Received 20.11.2022