Knowledge Modeling of power grid regulation based on reasoning map

To contribute to the intelligence and knowledge of power grid regulation and control operations, this paper presents a method of power grid regulation knowledge modeling based on ELG (Event Logic Graph), which includes an event word extraction based on a predicate-argument model, an event chain extraction and fusion based on event similarity theory, an event generalization based on a soft-pattern algorithm, and an event relationship recognition based on rule pattern matching method and joint constraints. Finally, this paper uses events as nodes and event relationships as directed edges to construct an affair graph stipulated by the power grid regulation and control regulations. The ELG is also called the new generation knowledge graph. But the knowledge graph can only describe the existence of entities and the upper and lower associations between entities. ELG can explain the inheritance, causality between entities and the logic of affair evolution, and the probability of transition between legacy and causality. Therefore, knowledge modeling based on ELG has intelligent advantages. Also, compared with ontology-based knowledge modeling methods, the method proposed in this paper can realize the dynamic representation of control operation knowledge, can express the logic of behavior and logic of operation, and also has higher retrieval accuracy.

A Survey of Ontologies and Their Applications in e-Learning Environments

Ontology technology has been investigated in a wide range of areas and is currently being utilized in many fields. In the e-learning context, many studies have used ontology to address problems such as the interoperability in learning objects, modeling and enriching learning resources, and personalizing educational content recommendations. We systematically reviewed research on ontology for e-learning from 2008 to 2020. The review was guided by 3 research questions: “How is ontology used for knowledge modeling in the context of e-learning?”, “What are the design principles, building methods, scale, level of semantic richness, and evaluation of current educational ontologies?”, and “What are the various ontology-based applications for e-learning?” We classified current educational ontologies into 6 types and analyzed them by 5 measures: design methodology, building routine, scale of ontology, level of semantic richness, and ontology evaluation. Furthermore, we reviewed 4 types of ontology-based e-learning applications and systems. The observations obtained from this survey can benefit researchers in this area and help to guide future research.

Knowledge Modeling in Troubleshooting

Introduction. The article describes the approach to solving the problem of complex technical system troubleshooting based on expert knowledge modeling. Intelligent information systems are widely used to solve the problems of diagnostics of multilevel systems including combine harvesters. The formal description of the subject domain knowledge is the framework for building the knowledge base of these systems. The sequence of creating an expert system knowledge base in accordance with production rules is considered. Materials and Methods. The approach is founded on the fault function table. As the object of diagnostics, one of the subsystems of the combine harvester electric equipment “opening the hopper roof flaps” is considered. The basis for constructing a sequence of elementary checks is a system of logical equations describing both the serviceable and possible faulty states of the subsystem. Results. A structural logic model is developed. As a result of analyzing the fault function table, the sets of elementary checks are determined. Four criteria have been used to analyze the weight of these checks. The authors have determined optimal sequence of checks and have developed a decision tree, which allows finding the cause of the malfunction and is the basis for creating the knowledge base of an intelligent information system. A fragment of the knowledge base is given. Discussion and Conclusion. The proposed approach of expert knowledge modelling increases the efficiency of the unit for troubleshooting of the intelligent decision support system. It makes possible to structure the base of expertise and establishing the optimal sequence of elementary checks. This allows determining the optimal sequence of application of the knowledge base production rule that makes it possible to reduce the time of restoring the serviceability of combines.

A Semantic-Based Framework for Verbal Autopsy to Identify the Cause of Maternal Death

Objective Verbal autopsy is a technique used to collect information about a decedent from his/her family members using questionnaires, conducting interviews, making observations, and sampling. In substantial parts of the world, particularly in Africa and Asia, many deaths are unrecorded. In 2017, globally pregnant women were dying daily around 810 and 295,000 in a year because of pregnancy-related problems, pointed out by World Health Organization. Identifying the cause of a death is a complex process which requires in-depth medical knowledge and practical experience. Generally, medical practitioners possess different knowledge levels, set of abilities, and problem-solving skills. Additionally, the medical negligence plays a significant part in further worsening the situation. Accurate identification of the cause of death can help a government to take strategic measures to focus on, particularly increasing the death rate in a specific region. Methods This research provides a solution by introducing a semantic-based verbal autopsy framework for maternal death (SVAF-MD) to identify the cause of death. The proposed framework consists of four main components as follows: (1) clinical practice guidelines, (2) knowledge collection, (3) knowledge modeling, and (4) knowledge codification. Maternal ontology for the framework is developed using Protégé knowledge editor. Resource description framework application programming interface (API) for PHP (RAP) is used as a Semantic Web toolkit along with Simple Protocol and RDF Query Language (SPARQL) is used for querying with ontology to retrieve data. Results The results show that 92% of maternal causes of deaths assigned using SVAF-MD correctly matched manual reports already prepared by gynecologists. Conclusion SVAF-MD, a semantic-based framework for the verbal autopsy of maternal deaths, assigns the cause of death with minimum involvement of medical practitioners. This research helps the government to ease down the verbal autopsy process, overcome the delays in reporting, and facilitate in terms of accurate results to devise the policies to reduce the maternal mortality.

Application of Bayesian Networks of Genotype by Environment Interaction Evaluation Under Plant Disease, Soil Types and Climate Condition-using Bayesia Lab

Genotype by environment interaction (GEI) linked to plant disease, soil properties and climate conditions add potential value for a breeding program to underpin decision making. In understanding genotype x environment interaction, the most challenging factors are the identification of genetic variation for a range of traits and their responsiveness to the climate change factors. In order to study the complex relationships with genetic and non-genetic factors, the application of Bayesian network tools will help understand and accelerate plant breeding progress and improve the efficiency of crop production. In this study, we proposed the application of Bayesian networks (BNs) to evaluate genotype by environment interaction under plant diseases, soil type, and climate variables. An adapted to simulate multiple environmental trial (MET) data of maize (corn) was used to examine the performance of the BN predictive modeling using BayesiaLab for deriving knowledge and graphical structure for exploring GEI diagnosis and analysis. The results highlighted that genotypes have the same probability and the frequentist of rainfall, temperature, soil type, and disease type occurred as <=88 (46%), 35 (37%), clay (27%), and MB (47%) respectively, which have to monitor reflects in each discretization. This study provided a roadmap to knowledge modeling of GEI using BayesiaLab software. On a broader scale, this study helps predict the yield of crop varieties by understanding agronomic and environmental factors under farm conditions rather than conducting long-term agricultural testing under well-controlled conditions of the on-station trials. Future improvements of BNs application of METs should consider working on a larger and more detailed soil and irrigation system linked to agro system.

Modeling in the environment of three-dimensional graphics as a method of forming students' critical thinking

The problem and the aim of the study. The formation of critical thinking is one of the most important tasks that teachers face in the vocational education system. The complexity, versatility of the studied objects, phenomena and processes of reality make it necessary for the mentors of the digital school to look for universal methods of cognition. The authors propose to use the modeling method in 3D graphics environments to form critical thinking as an important skill that meets the challenges of globalization and transformation. Research methods. The main method is modeling, as a general scientific method for studying the phenomena of reality using the analogy between the model and the original. The research was carried out on the basis of Vyatka State University for students of the training programme 44.04.01 Pedagogical education, profile Informatization of Education (master degree level). A software tool for organizing modeling as a method of teaching and scientific cognition is SketchUp. The Pearson’s χ2 (chi-square) criterion was used as a method for statistical processing of the experimental data. Results. The students of the experimental group used modeling in the environment of three-dimensional graphics at the following stages: acquiring theoretical information about the original object, creating a substitute model, developing a system of research problems, reflection, checking and adjusting the results in the conditions of the original object, the statement of a qualitatively new knowledge. The assessment of the levels of formation of critical thinking was carried out and statistically significant differences in the qualitative changes that occurred in the pedagogical system were revealed, χ2emp.2 > χ2crit0.05 (6.42 > 5.99). In conclusion, the conditions under which three-dimensional modeling contributes to the development of basic properties that ensure the formation of critical thinking are generalized: application together with other methods of scientific knowledge; modeling not only in a software environment for creating a 3D project, but also developing an Instruction as a model for its practical application; obtaining qualitatively new knowledge, etc.

3D GIS FOR A SMART MANAGEMENT SYSTEM APPLIED TO HISTORICAL VILLAGES DAMAGED BY EARTHQUAKE

Historic villages are included in the category of cultural heritage to be safeguarded and preserved. Accidental events, such as earthquakes, represent a threat to their vulnerability. Usually, the analyses of damaged buildings, which are part of these villages, are then carried out singularly, not fostering instead the constitution of a mapping at the urban scale that allows a more complete knowledge of the state of damage and risk of adjacent buildings and of the entire area. An information system such as 3D GIS is a suitable solution for this purpose. The aim of this research is to develop a SMART management system for preservation activities of historical villages through the management of heterogeneous types of data, from the survey to the technical documentation. The workflow is structured as follows: (i) Data acquisition: the survey of a small village was carried out by combining geomatic techniques necessary to produce a complete point cloud; (ii) 3D modeling: data extrapolation from the post-processed point cloud and subsequently generation of a GIS based on 3D model thanks to the creation of DTM and DSM of the area of interest; (iii) Knowledge modeling: a geospatial information model is necessary to put in order and together all the information collected for the whole village and for each building composing it; (iv) SMART management modeling: improvement of the information management system that guarantees the possibility to enrich and update data at any time. This research paves the way to develop a web platform where GIS data would be imported for a digital twin approach.