Now showing 1 - 10 of 13
  • Publication
    Automatic Transformation of Relational Database Schema into OWL Ontologies
    Ontology alignment, or ontology matching, is a technique to map different concepts between ontologies. For this purpose at least two ontologies are required. In certain scenarios, such as data integration, heterogeneous database integration and data model compatibility evaluation, a need to transform a relational database schema to an ontology can arise. To conduct a successful transformation it is necessary to identify the differences between relational database schema and ontology information representation methods, and then to define transformation rules. The most straight forward but time consuming way to carry out transformation is to do it manually. Often this is not an option due to the size of data to be transformed. For this reason there is a need for an automated solution. The automatic transformation of OWL ontology from relational database schema is presented in this paper; the data representation differences between relational database schema and OWL ontologies are described; the transformation rules are defined and the transformation tool’s prototype is developed to perform the described transformation.
    Scopus© Citations 2
  • 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
    ENERGY AUDIT INFORMATION SYSTEM
    (2022)
    Arta Rozentale
    ;
    Inta Kotane
    ;
    The opportunities provided by energy audits to improve the competitiveness of companies by reducing energy consumption and introducing energy-efficient solutions also allow for achieving the environmental goals set by the European Union and Latvia in relation to climate neutrality. It is important to consider the results of energy audits in the development of both local and regional and national policies, thus setting more precise results to be achieved. At present, there is no unified energy audit development information system in Latvia, in which all audit stages and calculations could be performed; this would reduce clerical and calculation errors and allow data to be predicted and used in policy development, research. Within the framework of the work, the authors researched the concept of energy audit, its process and the results to be achieved by companies by implementing energy efficient measures, as well as the policy goals of the European Union and Latvia in environmental improvement programs. The paper summarizes and analyses the programs and methods available in Latvia, which are used to develop energy audits of companies, as well as the practices of other countries and their results.The research goal is to develop the specification of the energy audit information system, based on the analysis of the used energy audit information systems. Based on the findings, the authors developed a specification of the program's energy audit information system requirements, which is suitable for the Latvian market.
  • Publication
    ANALYSIS OF ARTIFICIAL INTELLIGENCE APPLICATIONS FOR AUTOMATED TESTING OF VIDEO GAMES
    Game testing is a software testing process for quality control in video games. Game environments, sometimes called levels or maps, are complex and interactive systems. These environments can include level geometry, interactive entities, player and non-player controllable characters etc. Depending on the number and complexity of levels, testing them by hand may take a considerable effort. This is especially true for video games with procedurally generated levels that are automatically created using a specifically designed algorithm. A single change in a procedural generation algorithm can alter all of the video game levels, and they will have to be retested to ensure they are still completable or meet any other requirements of the game. This task may be suitable for automation, in particular using Artificial Intelligence (AI). The goal of this paper is to explore the most promising and up-to-date research on AI applications for video game testing to serve as a reference for anyone starting in the field.
    Scopus© Citations 8
  • 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
    ;
    Zhukov, Vitaliy
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    ;
    Litavniece, Lienīte
    ;
    ;
    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.