Moodle-based data mining potentials of MOOC systems at the University of Szeged

In today's world virtual online educational platforms emerge literally on daily bases and many offer MOOC-based courses. With the appearance of MOOC, educational platforms have gained an additional boost, a new aspect in their evolutionary process, which has opened a new field of research thanking to the extraction of logging information within the frames of data mining. It has become clear that educators will be able to tailor their courses by merging the two previously mentioned fields and by carrying out MOOC-based data mining, targeting pedagogical aspects. This field of research seems promising and important, thus a faculty at the University of Szeged has created its own MOOC educational platform which has been set to facilitate data mining by implementing a wide range of logging algorithms. The data would be processed through a complex Artificial Intelligence program, which, in the short term, could reveal new and exciting pedagogical findings, while in the long run, the supervisors could put together a platform that would help and notify educators about relevant information. It would become possible to create adaptive educational materials, as well. This work aims at clarifying how such platforms function and what the steps of data collection and evaluation are

A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching

Selecting the most appropriate heuristic for solving a specific problem is not easy, for many reasons. This article focuses on one of these reasons: traditionally, the solution search process has operated in a given manner regardless of the specific problem being solved, and the process has been the same regardless of the size, complexity and domain of the problem. To cope with this situation, search processes should mould the search into areas of the search space that are meaningful for the problem. This article builds on previous work in the development of a multi-agent paradigm using techniques derived from knowledge discovery (data-mining techniques) on databases of so-far visited solutions. The aim is to improve the search mechanisms, increase computational efficiency and use rules to enrich the formulation of optimization problems, while reducing the search space and catering to realistic problems.Izquierdo Sebastián, J.; Montalvo Arango, I.; Campbell, E.; Pérez García, R. 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Extended Comprehensive Study of Association Measures for Fault Localization

To cite the data package, please use the following citation: Lucia, L., Lo, D., Jiang, L., Thung, F., & Budi, A. (2014). Data from: Extended Comprehensive Study of Association Measures for Fault Localization. InK Repository at Singapore Management University. http://ink.library.smu.edu.sg/sis_research/1818</p

Porosity and Surface Properites of SBA-15 with Grafted PNIPAAM: A Water Sorption Calorimetry Study

Mesoporous silica SBA-15 was modified in a three-step process to obtain a material with poly-N-isopropylacrylamide (PNIPAAM) grafted onto the inner pore surface. Water sorption calorimetry was implemented to characterize the materials obtained after each step regarding the porosity and surface properties. The modification process was carried out by (i) increasing the number of surface silanol groups, (ii) grafting 1-(trichlorosilyl)-2-(m-/p-(chloromethylphenyl) ethane, acting as an anchor for (iii) the polymerization of N-isopropylacrylamide. Water sorption isotherms and the enthalpy of hydration are presented. Pore size distributions were calculated on the basis of the water sorption isotherms by applying the BJH model. Complementary measurements with nitrogen sorption and small-angle X-ray diffraction are presented. The increase in the number of surface silanol groups occurs mainly in the intrawall pores, the anchor is mainly located in the intrawall pores, and the intrawall pore volume is absent after the surface grafting of PNIPAAM. Hence, PNIPAAM seals off the intrawall pores. Water sorption isotherms directly detect the presence of intrawall porosity. Pore size distributions can be calculated from the isotherms. Furthermore, the technique provides information regarding the hydration capability (i.e., wettability of different chemical surfaces) and thermodynamic information