Harvester open publications of NAS Ukraine
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A three-dimensional model of semantic search: queries, resources, and results
No full textWe propose three-dimensional model of semantic search that analyzes search requests, information resources (IRs) and search results. This model is proposed as an additional tool for describing and comparing information retrieval systems (IRSs) that use various elements of artificial intelligence and knowledge management for more effective and relevant satisfaction of user information needs. In this work we analyze existing approaches to the semanticization of search queries and the use of external knowledge sources for retrieval process.The values of parameters analyzed by this model are not mutually exclusive, that is, the same IRS can support several search options. More over, the representation means of queries and resources are not always comparable.The model makes it possible to identify IRSs with intersected triads «request-IR-result» and to perform their comparison precisely on these subclasses of search problems. This approach allows to select search algorithms that are more pertinent for specific user tasks and to choose on base of this selection appropriate retrieval services that provide information for further processing. An important feature of the proposed model is that it uses only those IRS characteristics that can be directly evaluated by retrieval users.Prombles in programming 2023; 4: 39-5
First-order sequent calculi of logics of quasiary predicates with extended renominations and equality
No full textThe paper considers new classes of software-oriented logical formalisms – pure first-order logics of partial quasiary predicates with extended renomi- nations and predicates of strong equality and of weak equality.Prombles in programming 2022; 3-4: 11-2
Software system for laser targeting dropped ammunition
Get PDFFor last few years usage of small commercial unmanned aerial vehicles (UAV) on battlefield was drastically increased. In addition to use UAVs as spotter, they more and more frequently applied to drop small ammunition on enemy forces. In this paper laser targeting system that suitable for use on lightweight, mobile drones that drop freefalling ammunition was developed. Laser targeting systems are used for detecting and tracking the targets in the battlefield by obtaining the position information of these targets which is being designated and illuminated by UAV’s laser designator then the laser light reflected from these targets and come to the input of the optical systems of the dropped ammunition. An optical system for collimating the reflected beam from the target is one of the main components of the laser targeting system (LTS). The Quad Detector (QD) as a part of this optical system is simply consists of four photodiodes capable of detecting light spot projected on its surfaces and determine the deviation position of the laser spot from its center. It converts the incident laser spot to its corresponding photocurrent, the readout circuit that filter and convert the photocurrent to its corresponding voltage and the tracking system that is controlling the laser seeker movement to track the intended target based on the feedback information of the QD depending on the real position of the tracking platform. Developed system will ensure that munitions are accurately hit the target, reducing unnecessary casualties and damage, as well as reducing the number of sorties required and the time spent in hazardous airspace for the unmanned aerial vehicle.Problems in programming 2023; 2: 10-23
Problems of information technologies automation for the NAS of Ukraine scientific institutions’ administrative-managerial activity and approaches to solve them
No full textSpecific problems of the National Academy of Sciences (NAS) of Ukraine Scientific Institutions’ administrative-managerial activity (AMA) informatization is analyzed. Seven reference AMA Information Technologies (IT) are proposed for scientific-organizational, progress, staffing and accounting Institutions’ services. Industrially tested tools are investigated for AMA IT automated support. National software platform UnityBase with A5 SYSTEMS Application is substantiated as a tool for first stage of informatization. Approach for managing NAS of Ukraine Scientific Institutions informatization based on UnityBase platform is proposed. It is based on innovative management methodology, namely Appreciative Inquiry, – to cope with organizational resistance concerning informatization and elaborate its effective strategy.Prombles in programming 2023; 3: 05-2
Research of software solutions for forecasting electricity generation and consumption in Ukraine that are based on machine learning methods
No full textThe problem of security in energy sector is an important aspect for Ukraine. The purpose of monitoring in this area is to optimize the flow of electricity between market participants, between European partners and Ukraine. It is critically important to maintain a balance between producers and consumers of energy. Both over and undersupply of energy represent risks to infrastructure. The previously available wholesale electricity market model with single buyer has been replaced by a model based on bilateral, day-ahead and intraday markets, as well as balancing and ancillary services markets. Now the participants can freely trade electricity and energy companies can provide services that provide stability of the energy system and supply electricity to the final consumer. The demand forecasting in electricity markets is one of the components that must be implemented for successful business operations and optimization of business processes. Based on the model of the Institute of problems of modeling electricity engineering of NANU, the paper sets out the task of developing a software system for forecasting threats in the energy sector of Ukraine using machine learning methods. Experiments were conducted on the application of regression methods to restore a column with data from bilateral contracts for the task of forecasting electricity generation and consumption. The results of the application of machine learning algorithms on peacetime data demonstrated that it is possible to predict market volumes and tariff plans one hour in advance with a good accuracy which allows to go beyond one-day planning in the future.Prombles in programming 2023; 3: 99-10
Повідомлення про новий сорт Crataegus ‘Kokhno’ та +Crataegomespilus
No full textCrataegus (+Crataegomespilus) ‘Kokhno’ is a new graft chimera originated from the junction where Crataegus germanica (= Mespilus germanica) scion was top-grafted onto a stock Crataegus sp. In 1993, in the arboretum of one of the forestry-division offices in the Volhynia region, Vladyslav Oleshko found a putative hybrid between hawthorn and medlar, which was named in honor of well-known Ukrainian dendrologist Mykola Kokhno. He believed this plant was the result of a crossing between Mespilus germanica and Crataegus ucrainica because it was characterized by heterophylly having a mixture of both medlar and hawthorn leaves. The flowers of this plant are not solitary but placed in corymbs. The fruits are not aligned in size and range from 0.5–5.0 cm in diameter. The study of this hawthorn-medlar in the dendrological collection of the M.M. Hryshko National Botanical Garden (Kyiv, Ukraine) led to the conclusion that it is a graft chimera, not a hawthorn-medlar sexual hybrid. This hawthorn-medlar cultivar is morphologically similar to medlar but differs in the arrangement of flowers and fruits. The fruits typical for varietal medlar develop from solitary flowers, whereas atypical small fruits are located in groups. Both types of fruits have no germs in the stones. The cultivar ‘Kokhno’ is adapted to the Forest-Steppe of Ukraine and performs well as an ornamental and fruit plant. An outline of the history and nomenclature of graft hybrids (chimeras) between Crataegus and Mespilus is given
Deeplearning-based approach to improving numerical weather forecasts
No full textThis paper briefly describes the history of numerical weather prediction development. The difficulties, which occur in the modelling of atmospheric processes, their nature and possible ways of their mitigation, are described. It also indicates alternative methods of improving the quality of meteorological forecasts. A brief history of deep learning and possible ways of its application to meteorological problems are given. Then, the paper describes the format used to store the 2m temperature forecasts of the COSMO numerical regional model. The proposed neural network architecture enables correcting the forecast errors of the numerical model. We conducted the experiments on the data of eight meteorological stations of the Kyiv region, so we obtained eight trained neural network models. The results showed that the proposed architecture enables obtaining better-quality forecasts in more than 50% of cases. Root-mean-square errors of the resulting forecasts decreased, and it is a widespread skill-score of improved-quality forecasts in meteorological science.Prombles in programming 2023; 3: 91-9
Recurrent neural networks for the problem of improving numerical meteorological forecasts
No full textThis paper briefly describes examples of how deep learning can be applied to geoscientific problems, as well as the main difficulties that arise when scientists apply this technique to the problems of meteorological forecasting. This paper aims at comparing the two most popular types of recurrent neural network architectures, namely the long short-term memory network and the gated recurrent unit when they are used to improve 2m temperature forecast results obtained using numerical hydrodynamic methods of meteorological forecasting. An efficiency comparison of architectures of recurrent neural networks was performed using the root-mean-square error. It is shown that all models with gated recurrent units are more efficient than models with long short-term memory. Thus the best architecture of recurrent neural networks for solving the problem of improving numerical meteorological forecasts has been revealed.Prombles in programming 2023; 4: 90-9
Problems of scaling semantic information resources with a complex structure
No full textWe analyze scaling problems arising in modern intelligent information systems (IISs) and classify main reasons for their occurrence in their practical solutions. IISs integrate various elements of artificial intelligence (AI) for acquisition of knowledge relevant to actual user tasks. Important properties of these IISs are use of data with complex structure and orientation on semantic information resources (IRs). Therefore we analyze main features of the Data-Centric AI and opportunities for acquiring domain knowledge in various representations from Big Data. Knowledge organization systems (KOS) provide models and methods for effective store, retrieval and use of information processed by the Web-oriented IISs, and we consider existing approaches for their software platforms.We analyse the specifics of the scaling for systems focused on the semantic information processing and its differences from traditional data and Big Data scaling. This specifics is caused by complexity of data structure, number of various semantic relations between information objects into IR and complexity of semantic queries executed by KOS.On example of e-VUE – the Wiki-portal of the Great Ukrainian Encyclopedia – we analyze various situations that arise in process of practical development of semantic information resources with large volume and complex structure. Various ways of semantic retrieval into this information resource that use possibilities of the Semantic MediaWiki plugin are considered from the point of view of scaling aspects (such as increase of information objects, their relations and complication of their structure and characteristics). On base of this analysis we generate a set of recommendations aimed at ensuring more efficient development of such resources and their efficient functioning for practical use.Prombles in programming 2022; 3-4: 171-18
Digital health systems: SMART-system for remote support of hybrid E-rehabilitation services and activities
Get PDFThe top-priority challenges were faced by the medical rehabilitation system in Ukraine. Particularly important tasks include, first of all, the rehabilitation of patients who have recovered from COVID-19 disease and people with Combat stress reaction. This fact is well understood both by the society and the leadership of the Ministry of Health of Ukraine, which is creating a special working group on this problem. Ukraine has a system of medical and prophylactic institutions designed for psychological and physical rehabilitation of military personnel; these use modern rehabilitation technologies. However, long-term rehabilitation in such centers is not available to everyone. Therefore, the use of telerehabilitation technology for patients with post-traumatic stress disorder and similar disorders in com- bination with a means of objective control of the functional state is extremely important. One of the most effective solutions in medical rehabilitation assistance is remote patient / person-centered rehabilitation. Rehabilitation also needs effective methods for the "Physical therapist – Patient – Multidisciplinary team" system, including the statistical processing of large volumes of data. Therefore, along with the traditional means of rehabilitation, as part of the "Transdisciplinary intelligent information and analytical system for the rehabilitation processes support in a pandemic (TISP)" in this paper, we introduce and define: the revised and completed basic concepts of the hybrid e-rehabilitation notion and its fundamental foundations; the formalization concept of the new Smart-system for remote support of hybrid e-rehabilitation services and activities; and the methodological foundations for the use of services (UkrVectōrēs and vHealth) of the remote Patient / Person- centered Smart-system. The software implementation of the services of the Smart-system has been developed.Prombles in programming 2022; 3-4: 311-32