E-learning represents novel learning way, which increase teaching flexibility and availability of learning resources. This paper explores the evaluation of student success at e-learning platform. Authors used multi-method approach for data analysis (i.e. Social Network Analysis, K-means Clustering and Linear Regression). This approach presents novelty in the field of e-learning, which provides more detailed analysis that enable more relevant results. The research was conducted with student group at the University of Novi Sad, Faculty of Technical Sciences, Serbia. Results indicate that digital resources at the e-learning platform make strong effects on student success. Moreover, results indicate that students with the similar grades belongs to the same clusters.

In this paper, we present our software-supported method for analyzing the economic feasibility of business models. The method integrates the business models and business processes perspectives for analyzing how a company appropriates the financial cost and benefits. In this method, we use the Service-Dominant Business Model Radar to specify business models, then translate the specified business model into a business process for analyzing the financial feasibility of a business model. At the final step in our method, we use the generated business process in the previous step with a software-based tool, The Cost-Benefit Tracker, for analyzing the economic potential of the business model. We designed and developed the Cost-Benefit Tracker as a simple software-based BPMN 2.0 tool by integrating the concepts of the Service-Dominant Business Model Radar tightly. As a result, the software is simple and straightforward to use than enterprise BPMN 2.0 software. Hence, entrepreneurs can use the presented software-supported method to financially evaluate business model concepts specified with the Service-Dominant Business Model Radar.

When researchers formulate search queries to find relevant content on the Web, those queries typically consist of keywords that can only be matched in the content or its metadata. The Web of Data extends this functionality by bringing structure and giving well-defined meaning to the content and it enables humans and machines to work together using controlled vocabularies. Due the high degree of mismatches between the structure of the content and the vocabularies in different sources, searching over multiple heterogeneous repositories of structured data is considered challenging. Therefore, the authors present a semantic search engine for researchers facilitating search in research related Linked Data. To facilitate high-precision interactive search, they annotated and interlinked structured research data with ontologies from various repositories in an effective semantic model. Furthermore, the authors' system is adaptive as researchers can synchronize using new social media accounts and efficiently explore new datasets.

The paper presents an initial study and basic research of the state of the art systems and solutions for the simulation of the thermoregulatory sweating conditions. The simulation of the thermoregulatory sweating conditions has been treated by many researchers, and has become over the years a major area of interest for many industries (e.g. textile, protective garments, aeronautics, automotive industries and sports). The objective of this paper is to reflect and analyse the existing literature, for this purpose. Three existing systems and two thermoregulatory models will be characterized and critically discussed. The findings support the methodology for future applied scientific research (PhD thesis), which will use existing scientific knowledge to develop a practical application using suitable technology.

Recent developments on sharing research results and ideas on the Web, such as research collaboration platforms like Mendeley or ResearchGate, enable novel ways to explore research information. Current search interfaces in this field focus mostly on narrowing down the search scope through faceted search, keyword matching, or filtering. The interactive visual aspect and the focus on exploring relationships between items in the results has not sufficiently been addressed before. To facilitate this exploration, we developed ResXplorer, a search interface that interactively visualizes linked data of research-related sources. By visualizing resources such as conferences, publications and proceedings, we reveal relationships between researchers and those resources. We evaluate our search interface by measuring how it affects the search productivity of targeted lean users. Furthermore, expert users reviewed its information retrieval potential and compared it against both popular academic search engines and highly specialized academic search interfaces. The results indicate how well lean users perceive the system and expert users rate it for its main goal: revealing relationships between resources for researchers.

Project management within the automotive production in specific departments is still done separately and does not interact with engineering process. Our work aims on providing flexible data insights on collaboration tasks within such environments. We apply semantic technologies RDF, OWL and SPARQL with a specific domain related ontology PROTARES (PROject TAsks RESources) to interlink, describe and query domain knowledge. As proof of concept we are introducing an experimental visualisation interface called TaskRadar. Our application resides on domain ontology and allows knowledge based browsing and visualisation of tasks in development process. With this example we want to show, how semantically driven customized views can support monitoring and reflection as well as decision-making within the early phases of the automotive product lifecycle.