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This research is devoted to the determination of hidden dependencies between the flow of particles that come from the Sun and precipitation-induced floods in the United Kingdom (UK). The analysis covers 20 flood events during the period from October 2001 to December 2019. The parameters of solar activity were used as model input data, while precipitations data in the period 10 days before and during each flood event were used as model output. The time lag of 0–9 days was taken into account in the research. Correlation analysis was conducted to determine the degree of randomness for the time series of input and output parameters. For establishing a potential causative link, machine learning classification predictive modeling was applied. Two approaches, the decision tree, and the random forest were used. We analyzed the accuracy of classification models forecast from 0 to 9 days in advance. It was found that the most important factors for flood forecasting are proton density with a time lag of 9, differential proton flux in the range of 310–580 keV, and ion temperature. Research in this paper has shown that the decision tree model is more accurate and adequate in predicting the appearance of precipitation-induced floods up to 9 days ahead with an accuracy of 91%. The results of this study confirmed that by increasing technical capabilities, using improved machine learning techniques and large data sets, it is possible to improve the understanding of the physical link between the solar wind and tropospheric weather and help improve severe weather forecasting.

The paper presents ideas and initiatives from two ongoing Erasmus+ projects funded by the European Commission. Both projects use e-Learning as an enabler for communicating interesting and important learning contents that are believed to increase and improve employability prospects for the targeted groups of learners. The WINnovators project targets young women with reduced opportunities for quality education in different areas of STEM/STEAM and intends to demonstrate how their entrepreneurial skills can gradually grow by providing them with e-Learning incentives in such areas. The YNSPEED project intends to offer free MOOC courses addressing hot topics of modern society – artificial intelligence, sustainable development, and fake news. In the YNSPEED project, the target group of learners are young people (aged 16-29). It is believed that their interest in such important topics can be boosted by communicating the corresponding relevant learning content in a carefully designed way. The Shine a light metaphor is a common point and a common approach in both projects – e-Learning technology is used to facilitate informal education for the targeted learners and to indicate directions that often get either omitted or misunderstood in traditional schools.

This chapter presents the IntelLEO solution that was developed in order to provide a new paradigm, namely, Intelligent Learning Extended Organization (IntelLEO). IntelLEO leverages intelligent technologies to support learning and knowledge-building (LKB) activities of a community that emerges as a temporal integration of two or more different business and educational communities and organizational cultures, with emphasis to LKB activities of Individuals and groups across various boundaries (vertical-within the organizations involved and horizontal-within and between the organizations).. The solution is implemented as part of the IntelLEO project, an FP7 project in the area of technology enhanced learning. IntelLEO software solution supports the process of transformation between tacit and explicit knowledge on the cross-organizational level, describing the ways for improving the responsiveness of organizations participating in IntelLEO. Responsiveness in this context is defined through increased motivation to proactively learn and construct knowledge in an IntelLEO. The IntelLEO pedagogical model was derived from the initial organizational SECI knowledge management model and adapted to describe crossorganizational learning in extended organizations. The IntelLEO technological services were developed to address motivational enablers within SECI model. Thereby, the IntelLEO SECI model for promoting motivated LKB acts across organizations was supported with the technological means that enabled to apply the model in extended organizations.

This paper presents the service-oriented development of Content and Knowledge Provision tool, one of the core services developed within IntelLEO, an FP7 project in the area of technology-enhanced learning. The project aims at enhancing cross-organizational Learning and Knowledge Building practices at the workplace. Content and Knowledge Provision tool enables employees to upload different kinds of learning resources into a knowledge repository, annotate them, and (re-)discover relevant learning resources by performing semantic search over the knowledge repository. Hence, this service effectively serves as a content management system and semantic search engine within the IntelLEO.

This paper presents the concept and the implementation of the Content and/or Knowledge Provision (CKP) service. The service is developed as a part of research within Intelligent Learning Extended Organization, an 7th Framework Program for R&D project in the area of technology-enhanced learning. The project aimed at enhancing cross-organizational Learning and Knowledge Building (LKB) practices at workplaces, leading to continuous growth of organization's intellectual capital. By using the CKP service, employees can upload different kinds of knowledge assets into a knowledge repository, annotate them and (re-)discover relevant ones by performing semantic search over the knowledge repository. Hence, the service effectively serves as a content and knowledge-sharing facility and semantic search engine within a learning organization. Furthermore, CKP enables collaborative manipulation and annotation of knowledge assets in the repository, thus supporting all three components of intellectual capital.

Purpose - This paper presents the concept and the implementation of the Content and/or Knowledge Provision service (CKP service, for short). The service is developed as a part of research related to content management and semantic search, within IntelLEO, an FP7 project in the area of technology-enhanced learning. Design/methodology/approach - The CKP service is developed to facilitate collaboration between workplace learners in discovering, annotating and using electronic resources. The service relies on the novel concept of Intelligent Learning Extended Organizations, presented in the paper in detail. Originality/value - The IntelLEO project aims at supporting workplace learning situations where employees are often faced with the need to efficiently find, browse, share, and otherwise use electronic learning resources, but are usually constrained by limited time and other factors when they perform all these activities on their own. The CKP service deploys a set of semantic technologies to alleviate this problem. Practical implications-By using the CKP service, employees can access semantically annotated heterogeneous resources. This reduces the time and effort needed to find, share, and recommend learning resources at workplaces efficiently.

The paper promotes the use of novel Web services in the daily work and research of social scientists and other professionals. The case presented in the paper pertains to demographers and their research, but the technology used is generic and can be easily instantiated for use by other social science researchers. Specifically, the case covers facilitating collaboration between a university research group in the field of demography and professionals in the field of demographic statistics. The technology used is a set of new Web services developed as parts of an EU research project. The paper explains the case itself and the motivation for using the services, describes the services themselves, and discusses the experience acquired and the benefits and lessons learned by using the services so far.

This paper presents the process of identifying and describing cases for Technology Enhanced Learning (TEL) in a Small/Medium Enterprise (SME), as a part of an ongoing international TEL project. It proposes a template for describing TEL cases in an SME that collaborates with other organizations, notably with a university/research group. An example case description is used to illustrate the template proposed. In addition, the paper discusses how such a case is supported by specific TEL services on the Web.

This chapter presents a framework for intelligent analysis of the students' knowledge in assessment systems, using description logics (DLs) reasoning techniques. The framework is based on Model Driven Architecture (MDA) software engineering standards. It starts from the IMS Question and Test Interoperability (QTI) standard and includes MDA-based metamodel and model transformations for QTI assessment systems. It also specifies an architecture for QTI assessment systems that is reusable, extensible, and facilitates interoperability between its component systems. An implementation of the QTI metamodel and the relevant example of transformations is provided in order to support developments according to the proposed framework.

Povećanjem količine znanja koju nastavno osoblje pruža studentima u savremenom školstvu, produžava se i vreme za testiranje znanja studenata. Pošto su ljudski resursi ograničeni, a troškovi evaluacije znanja studenata sve veći, potrebno je pronaći alternativne metode za efikasnu proveru studentskog znanja. Tom prilikom se nastavno osoblje sreće sa dodatnom teškoćom, a to je sve veći broj studenata. Da bi se navedeni problemi rešili razvijen je sistem za elektronsko ocenjivanje studenata za brzu i kvalitetnu evaluaciju znanja studenata. Ovaj rad prikazuje kako efikasno testirati znanje studenata uz istovremenu uštedu ljudskih resursa., Increasing of the amount of knowledge that the teaching staff gives to students, the time for testing of the students' knowledge increases, too. Since the human resources are limited, and the costs of student knowledge evaluation are larger, it is necessary to find the alternative methods for efficient evaluation of students' knowledge. There is another problem that the teacher staff meets: the growing number of students. In order to solve specified problems the software Evaluator Assessment System has been developed for quick and quality evaluation of the students' knowledge. This paper presents one of the method how to test the students knowledge on efficient way, saving the human resources, at the same time.