The Prescription of Drug Ontology 2.0 (PDRO): More Than the Sum of Its Parts

While drugs and related products have profoundly changed the lives of people around the world, ongoing challenges remain, including inappropriate use of a drug product. Inappropriate uses can be explained in part by ambiguous or incomplete information, for example, missing reasons for treatments, ambiguous information on how to take a medication, or lack of information on medication-related events outside the health care system. In order to fully assess the situation, data from multiple systems (electronic medical records, pharmacy and radiology information systems, laboratory management systems, etc.) from multiple organizations (outpatient clinics, hospitals, long-term care facilities, laboratories, pharmacies, registries, governments) on a large geographical scale is needed. Formal knowledge models like ontologies can help address such an information integration challenge. Existing approaches like the Observational Medical Outcomes Partnership are discussed and contrasted with the use of ontologies and systems using them for data integration. The PRescription Drug Ontology 2.0 (PDRO 2.0) is then presented and entities that are paramount in addressing this problematic are described. Finally, the benefits of using PDRO are discussed through a series of exemplar situation.

Machine Learning Bias in Predicting High School Grades: A Knowledge Perspective

This study focuses on the machine learning bias when predicting teacher grades. The experimental phase consists of predicting the student grades of 11th and 12thgrade Portuguese high school grades and computing the bias and variance decomposition. In the base implementation, only the academic achievement critical factors are considered. In the second implementation, the preceding year’s grade is appended as an input variable. The machine learning algorithms in use are random forest, support vector machine, and extreme boosting machine. The reasons behind the poor performance of the machine learning algorithms are either the input space poor preciseness or the lack of a sound record of student performance. We introduce the new concept of knowledge bias and a new predictive model classification. Precision education would reduce bias by providing low-bias intensive-knowledge models. To avoid bias, it is not necessary to add knowledge to the input space. Low-bias extensive-knowledge models are achievable simply by appending the student’s earlier performance record to the model. The low-bias intensive-knowledge learning models promoted by precision education are suited to designing new policies and actions toward academic attainments. If the aim is solely prediction, deciding for a low bias knowledge-extensive model can be appropriate and correct. Doi: 10.28991/esj-2021-01298 Full Text: PDF

Web Interoperability for Ontology Development and Support with crowd 2.0

In this work, we treat web interoperability in terms of interchanging ontologies (as knowledge models) within user-centred ontology engineering environments, involving visual and serialised representations of ontologies. To do this, we deal with the tool interoperability problem by re-using an enough expressive ontology-driven metamodel, named KF, proposed as a bridge for interchanging both knowledge models. We provide an extensible web framework, named crowd 2.0, unifying the standard conceptual data modelling languages for generating OWL 2 ontologies from semantic visualisations. Visual models are designed as UML, ER or ORM 2 diagrams, represented as KF instances, and finally, formalised as DL-based models. Reasoning results may be newly incorporated into the shared KF instance to be visualised in any of the provided languages.

Towards Legal Ontology for Education

Semantic Web using ontology-based knowledge model has been largely applied to e-Learning systems. The use of domain ontologies leverages the transformation of the learning contents of serving human to machine understandable formats. The ontology-based approach could further support e-Learning activities related to legal compliances, such as legally validate learners’ profiles or protecting intellectual rights in e-Learning courses. This study proposes a novel ontological e-Learning framework including the legal knowledge model, the e-Learning knowledge model and the common knowledge model. A customized ontology engineering method is conducted to construct the preliminary version of these specified knowledge models, while a Semantic Web Rule Language (SWRL) rule base is constructed to capture knowledge of both laws and domain experts. FOCA based validation is introduced to confirm the feasibility of this proposed framework. Improving the FOCA score of the legal core ontology and enriching both the ontological knowledge model and its SWRL rule base are topics that can be explored in future studies.

INTEGRATION OF TRADITIONAL AND DISTANCE LEARNING METHODS IN HIGH SCHOOL

In the article the researchers are exploring the integration of traditional and distance learning methods identified as a result of quarantine measures during the coronavirus in high school. The main complex contradictions are revealed. Methods and decisions of a complex problem are developed. The tendencies of the development of distance education are researched. Scientific assumptions about an educology methodology are formed. Main stages of modern educational technologies in universities are defined. The study of integration processes between traditional and distance learning is carried out. The relations between subjects and objects of the university department are learned. It was revealed that the structure of the educational process is complicated due to the use of mobile means of communication and distance forms of educational communications in it, which leads to a change in teaching methods and forms. The features of the learning processes of modern students have specific features now. The necessity of using mobile devices and new software is analyzed. Attention is drawn to the fact that not all teachers are well versed in modern means of online group communications. The basic means of group communications such as: Moodle, Zoom, Skype, Teams and others, providing remote communication of students and teachers are analyzed. The features and specificity of these means of communication are considered. Their possibilities are being studied. Results of reengineering studies at the department are presented. The results of testing student training based on modeling methods are presented too. A digital platform of knowledge models, which consists of two components is created and used. The first component is an interconnected set of models of academic disciplines developed by teachers, and the second component is the knowledge models of these disciplines that students create during their studies. Teaching methods based on integrated intelligence during pandemic in universities are made. Ways to improve learning technologies based on the use of integrated intelligence are proposed in high school.

Students’ errors in L1 Spanish grammar from the perspective of formal linguistics

This paper studies the role that knowledge about formal linguistics can play in teacher education. In order to do so, this contribution focuses on specific secondary students’ errors and misconceptions when confronted with L1 explicit grammar instruction. Errors are measured with respect to a formal theory of grammar. The rationale for developing this research is that certain aspects of formal theories, such as constituency, recursion, dependency and compositionality function, not only are the building blocks of the utterances, but are also needed for speech processing. If this is the case, acquiring them correctly might be helpful for enhancing literacy, since the very same notions are at the core of both the construction and the understanding of any text. As a second issue, the present paper addresses the question of how the absence of such knowledge models the perspective from which students’ errors are evaluated by the teachers. Errors are described following the theories for analyzing errors in mathematics. A side effect of this approach is that the parallelism between errors made in learning mathematics and in learning the grammatical concepts just mentioned allows broadening the perspective from which the latter is approached.

MANAGEMENT OF KNOWLEDGE MODELS USING INFORMATION TECHNOLOGY

The topics of implementing methods of information technology as one of the effective and important methods are discussed for organizational and institutional management purposes. Information technology allows a new knowledge to be discovered which is an important and effective way for the management of organizational processes in order to maintain competitive edge. In today’s competitive and globalization world, the main challenge for organizations remains to be defining customer-oriented strategy where knowledge and its management is an important factor. Recently active works is being conducted for establishing and developing effective models of knowledge management where information technology plays an important role. Generally, information system is a means of collecting and creating new knowledge existing between different individuals/structures using information technology. It describes instruments of knowledge management that allows collaboration and communication between parties involved in business processes. Knowledge management includes facts, data and models of different types which exist in physical and electronic information depository.

Interval Algebra and Region Connection Calculus for Ontological Spatiotemporal Assembly Product Motion Knowledge Representation

Over the last decades, noticeable efforts have been made to construct design knowledge during the detailed geometric definition phase systematically. However, physical products exhibit functional behaviors, which explain that they evolve over space and time. Hence, there is a need to extend assembly product knowledge towards the spatiotemporal dimension to provide more realistic knowledge models in assembly design. Systematic semantic knowledge representation via ontology enables designers to understand the anticipated product’s behavior in advance. In this article, Interval Algebra (IA) and Region Connection Calculus (RCC) are investigated to formalize and construct ontological spatiotemporal assembly product motion knowledge. IA is commonly used to represent the temporality between two entities, while RCC is more appropriate to represent the ‘part-to-part’ relationships of two topological spaces. This paper discusses the roles of IA and RCC and presents a case study of a nutcracker assembly model’s behavior. The assembly product motion ontology with the aid of IA and RCC is evaluated using a task-based approach. The evaluation shows the added value of the developed ontology compared to others published in the literature.