Now showing 1 - 10 of 14
  • Publication
    Konceptuālo un relāciju datu modeļu savietojamības noteikšanas metodoloģija
    Lai informācijas sistēmas varētu apmainīties ar datiem, to datu modeļiem jābūt saderīgiem. Bieži vien tas tā nav, jo sistēmas ir veidojuši dažādi izstrādātāji, vadoties pēc dažādiem mērķiem, kā rezultātā rodas atšķirības terminu lietojumā un datu vērtību skaidrojumos. Līdz ar to šo informācijas sistēmu datu modeļi var būt izteikti dažādās notācijās, kas apgrūtina saderības noteikšanu. Šajā promocijas darbā tiek risināta dažādās notācijās izteiktu datu modeļu savietojamības noteikšanas problēma. Datu modeļi tiek transformēti ontoloģijās, pielietojot transformācijas noteikumus. Vēlāk tiek veikta automātiska ontoloģiju savietošana, un iegūts datu modeļu saderības novērtējums. Datu modeļu savietošanas procesā lietoto metožu kopums ir apvienots metodoloģijā, ko var izmantot datu modeļu salīdzināšanai dažādās nozarēs. Metodoloģija ļauj nozares ekspertiem veikt savietošanas uzdevumus automātiskā veidā, ekonomējot šim uzdevumam atvēlēto laiku un resursus. Izstrādātā metodoloģija ir tikusi aprobēta, salīdzinot Latvijas Valsts zemes dienesta datu bāzes relāciju modeli ar ISO 19152 starptautiskā standarta konceptuālo datu modeli, lai noteiktu, cik lielā mērā viens datu modelis atbilst otram. Metodoloģijas nodrošināšanas un aprobācijas vajadzībām ir izstrādāts ontoloģiju savietošanas programmatūras rīks, kas ir viens no šī darba praktiskajiem rezultātiem. Rīks nodrošina automātisku datu modeļu transformāciju un ontoloģiju savietošanu, kā arī ļauj veikt manuālu savietošanu un entītiju anotāciju.
  • Publication
    Konceptuālo un relāciju datu modeļu savietojamības noteikšanas metodoloģija. Promocijas darba kopsavilkums
    Darba mērķis ir izstrādāt metodoloģiju konceptuālo datu modeļu un relāciju datu modeļu savietojamības noteikšanai, kas ļautu automatizēt savietošanas procesu un nodrošinātu nozares speciālistus ar rīkiem darbā ar dažādās notācijās izstrādātiem datu modeļiem. Izmantojot šo metodoloģiju, lietotājam tiek dota metožu kopa, kas ļauj risināt konceptuālo un relāciju datu modeļu savietojamības noteikšanas uzdevumu. Konceptuālo un relāciju datu modeļu savietojamības noteikšanai ir izstrādāts speciāls rīks, kas ļauj šo uzdevumu atrisināt atbilstoši metodoloģijai. Pateicoties tam, tiek ievērojami samazināts nozares speciālistu darba apjoms, kā rezultātā tiek ietaupīts laiks un resursi
  • Publication
    Apple and Pear Scab Expert System
    (2023)
    Apeināns, Ilmārs
    ;
    ;
    Gunārs Lācis
    ;
    Lienīte Litavniece
    Plant disease, such as apple and pear scab, control is a crucial issue of fruit-growing. Apple and pear are among the most widely grown (approximately 43% of all fruit tree area) and economically important fruit crops worldwide and in Latvia. Research projects have produced research data covering various aspects of plant-pathogen interactions, but there is no internal linkage analysis, as well as implementation of other types of data (such as environmental and meteorological data, etc.). Establishing such a data integration system would allow the identification of new regularities in plant-pathogen interactions, and provide mechanisms for disease control decisions. In this study an expert system was developed aimed to help professional fruit-growers evaluate the possible impact of apple and pear scab to the plant health and yield quality. The expert system is based on a previously developed apple and pear scab ontology and consists of a web based front-end and triplestore back-end.
  • Publication
    Digital twin modelling for smart fruit-growing: eco-cyber-physical system 4+1 architecture
    (2023)
    Kodors, Sergejs
    ;
    ;
    Ginta Majore
    ;
    Edgars Rubauskis
    ;
    Lienite Litavniece
    The continuous evolution of technology and industrial revolutions provides new horizons for the application of smart solutions in every aspect of human lives. At the same time, it causes new social and engineering challenges, which require appropriate methodologies and solutions to overcome them. A smart orchard is an example of an eco-cyber-physical system. Modelling of an eco-cyber-physical system is more complex than simple software development because the complexity quickly grows together with the amount of interconnected components. The difficulties come together with various fruit tree species (in our case apples, pears, and cherries), related technologies and orchard systems. Such systems differ even in the frame of one species like apple trees (rootstocks effect on the tree size; planting density; tree canopy training systems, etc.) and some production risk-reducing technologies (rain and hail, against birds and insects protecting covering systems), as well as agricultural machinery movement in the site. An additional accelerator of complexity growth is the development of eco-cyber-physical and data-driven decision-making paradigms, which propose business-driven development considering ecological and technical aspects together within cyberspace. As a result, the product of synergy is a digital twin paradigm, which provides digital mirrors for artificial intelligence to monitor and manipulate the physical world considering environmental aspects. This article presents the digital twin “4 + 1” model of a smart orchard, which is described using modern visual notations like 4EM for project view, ARTSS for logical view, OPM for process view, IoT-adapted UML component diagram for physical view and spatial map for deployment view. The proposed methodology offers a roadmap for design and development of smart solutions in fruit-growing to predict the yield and potential of income generation in the early stages of the season.
  • Publication
    RISK ANALYSIS FOR APPLE ORCHARD SURVEY AND MONITORING USING UAV
    (2023)
    Lienīte Litavniece
    ;
    Kodors, Sergejs
    ;
    Juta Dekšne
    ;
    ;
    Gunārs Lācis
    ;
    Risk analysis is an integral part of modern business management because successful business largely depends on the effective implementation of risk analysis. Agriculture is an important sector in the national economy, therefore Industry 4.0 increasingly provides digital solutions in orchard management, which facilitate and simplify decision-making in daily tasks. Meanwhile, unmanned aerial vehicles are applied as the agriculture sector's main monitoring and data acquisition tool. However, this means that it is necessary to pay attention to risk analysis due to the process of managing the orchard, where not only a person and the mechanized equipment controlled by him, which moves on the ground but also flying automated equipment participates. The purpose of the article is to perform the risk analysis for the survey and monitoring of orchards for yield estimation using unmanned aerial vehicles by considering commercial apple orchards in Latvia. The main thing is that most risks are predictable, but planning is necessary to reduce the probability of their occurrence.  
  • Publication
    SIMULATION OF A SCHOOL CANTEEN TO UNDERSTAND MEAL DURATION IMPACT ON FOOD WASTE
    (2021)
    Kodors, Sergejs
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    Zhukov, Vitaliy
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    ;
    Litavniece, Lienīte
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    ;
    Zvaigzne, Anda
    A system simulation is a one of the approaches to understand business processes or to explain them to other people. It is an excellent decision making solution to provide data-driven conclusions based on system modelling and experiments. This paper proposes simulation results of a school canteen. The aim of the research was to investigate the relation between a food waste amount and meal time duration. The proposed simulation was based on business process analysis, business process modelling, a Monte Carlo method and expert knowledge. The frequency distributions were constructed based on children meal duration observation completed by their mothers. It is a magnificent citizen science solution to involve mothers in the research because they can additionally better understand their children meal preferences and habits. Therefore, a questionnaire for citizens was developed, which can be applied to collect statistical data for model accuracy improvement and extension.
    Scopus© Citations 1
  • Publication
    APPLE AND PEAR SCAB ONTOLOGY
    (2021) ; ;
    Toms Bartulsons
    ;
    Olga Sokolova
    ;
    Lienīte Litavniece
    ;
    Anna Nikolajeva
    An important issue in horticulture is ensuring plant disease, such as scab, prevention and treatment. Apple and pear are among the most widely grown (approximately 43% of all fruit tree area [1]) and economically important fruit crops specified worldwide and in Latvia. Scab diseases caused by ascomycetous fungi Venturia inaequalis and V.pyrina are economically the most important diseases worldwide. Research projects have produced research data covering various aspects of plant-pathogen interactions, but there is no internal linkage analysis, as well as implementation of other types of data (such as environmental and meteorological data, etc.). Establishing such a data integration system would allow the identification of new regularities in plant-pathogen interactions, and provide mechanisms for disease control decisions. Semantic analysis is one of information technology approaches to finding relationships in data. The product of analysis is ontology. There are plant disease ontologies which provide classification of diseases and describe their reasons. However, there is no ontology which describes a specific plant and relations among its farming parameters and disease probability. Such an ontology for apple and pear scab is presented in this paper. The constructed ontology can be applied to develop guidelines or digital expert systems.
    Scopus© Citations 1
  • Publication
    Pathfinding Algorithm Efficiency Analysis in 2D Grid
    (2013) ;
    Kodors, Sergejs
    The main goal of this paper is to collect information about pathfinding algorithms A*, BFS, Dijkstra's algorithm, HPA* and LPA*, and compare them on different criteria, including execution time and memory requirements. Work has two parts, the first being theoretical and the second practical. The theoretical part details the comparison of pathfinding algorithms. The practical part includes implementation of specific algorithms and series of experiments using algorithms implemented. Such factors as various size two dimensional grids and choice of heuristics were taken into account while conducting experiments.
    Scopus© Citations 5
  • Publication
    RAPID PROTOTYPING OF PEAR DETECTION NEURAL NETWORK WITH YOLO ARCHITECTURE IN PHOTOGRAPHS
    (2023)
    Kodors, Sergejs
    ;
    Marks Sondors
    ;
    Gunārs Lācis
    ;
    Edgars Rubauskis
    ;
    Apeināns, Ilmārs
    ;
    Fruit yield estimation and forecasting are essential processes for data-based decision-making in agribusiness to optimise fruit-growing and marketing operations. The yield forecasting is based on the application of historical data, which was collected in the result of periodic yield estimation. Meanwhile, the object detection methods and regression models are applied to calculate yield per tree. The application of powerful neural network architectures for rapid prototyping is a common approach of modern artificial intelligence engineering. Meanwhile, the most popular object detection solution is YOLO architecture. Our project team collected the dataset of fruiting pear tree photographs (Pear640) and trained YOLOv5m with mAP@0.5 95% and mAP@0.5:0.95 56%. The obtained results were compared with other YOLOv5-7.0 and YOLOv7 models and similar studies.
  • Publication
    Urban Objects Segmentation Using Edge Detection
    (2013)
    Kodors, Sergejs
    ;
    This manuscript describes urban objects segmentation using edge detection methods. The goal of this research was to compare an efficiency of edge detection methods for orthophoto and LiDAR data segmentation. The following edge detection methods were used: Sobel, Prewitt and Laplacian, with and without Gaussian kernel. The results have shown, that LiDAR data is better, because it does not contain shadows, which produce a noise.
    Scopus© Citations 3