This work focuses on automated incremental development of biological networks. The incremental approach is demonstrated on two use cases. First, a simple plant defence network created manually is extended in two incremental steps, yielding the final model with 183 relations. Second, a complex published network of plant defence response is incrementally updated with 104 new relations automatically extracted from recently published articles. The results show that using the demonstrated incremental approach it is possible to automatically extract new knowledge about the selected biological relations published in recent scientific literature.
F.15 Development of a new information system/databases
COBISS.SI-ID: 28591655In the area of development and use of knowledge technologies for improving education approaches, we developed a mobile application QTvity that encourages and supports real-time interaction between instructor and students during lectures. It also allows for the collection of data on students' understanding and communication, while the analysis of these data provides an additional insight into the learning process and the basis for its improvement. The application was presented at the International Conference CompSysTech 2015 in Dublin where we received an award for the best contribution.
F.15 Development of a new information system/databases
COBISS.SI-ID: 29039143Surface and ground waters are exposed to pesticides used in agronomy. To prevent water pollution by pesticides, the reliable predictions of the water outflows from fields are needed. The most frequently used models are difficult to apply due to the lack of required data about local soil properties and climate. To improve the performance and applicability of water outflow modeling we used a modeling approach based on machine learning techniques applied to data obtained from long-term experimental agronomic station La Jaillière, France. The results show overall improvement in the prediction of discharge through sub-surface drainage systems, and partial improvement in the prediction of the surface runoff. Using predictions of our models for decision support about the application time and dosage of pesticides will significantly improve the efficacy of water protection from pollution with pesticides.
F.15 Development of a new information system/databases
COBISS.SI-ID: 28041255In collaboration with the Department of Environmental Sciences, JSI, we developed a method and a decision support system for the assessement of electric energy production technologies in Slovenia in the period 2014-2050. The approach is based on two hierarchical qualitative multi-criteria models for the evaluation of individual technologies and technology mixtures, respectively. We assessed eight individual technologies (coal fired, gas fired, biomass fired, oil fired, nuclear, hydro, wind, and photovoltaic) in the context of 64 possible long-term scenarios of electric energy production in Slovenia. The purpose of the method and the decision support system is to contribute to an informed debate on the future development of the energy sector in Slovenia and formulation of a national strategy.
F.15 Development of a new information system/databases
COBISS.SI-ID: 29295911The IMP project produced a large set of resources of historical Slovene works, including a digital library , dictionary and an annotated corpus, all available on the Web (http://nl.ijs.si/imp/). The paper reports on the compilation of these resources and the methods we used to annotate them with linguistic information. A study of user experience showed that most users (predominantly teachers and students) consider the IMP resources important for their work and for Slovene linguistics in general.
F.15 Development of a new information system/databases
COBISS.SI-ID: 28321575