Modeling and predicting students' engagement behaviors using mixture Markov models

Students' engagements reflect their level of involvement in an ongoing learning process which can be estimated through their interactions with a computer-based learning or assessment system. A pre-requirement for stimulating student engagement lies in the capability to have an approximate representation model for comprehending students' varied (dis)engagement behaviors. In this paper, we utilized model-based clustering for this purpose which generates K mixture Markov models to group students' traces containing their (dis)engagement behavioral patterns. To prevent the Expectation-Maximization (EM) algorithm from getting stuck in a local maxima, we also introduced a K-means-based initialization method named as K-EM. We performed an experimental work on two real datasets using the three variants of the EM algorithm: the original EM, emEM, K-EM; and, non-mixture baseline models for both datasets. The proposed K-EM has shown very promising results and achieved significant performance difference in comparison with the other approaches particularly using the Dataset. Hence, we suggest to perform further experiments using large dataset(s) to validate our method. Additionally, visualization of the resultant clusters through first-order Markov chains reveals very useful insights about (dis)engagement behaviors depicted by the students. We conclude the paper with a discussion on the usefulness of our approach, limitations and potential extensions of this work

CoSMo: a Framework for Implementing Conditioned Process Simulation Models

Process simulation is an analysis tool in process mining that allows users to measure the impact of changes, prevent losses, and update the process without risks or costs. In the literature, several process simulation techniques are available and they are usually built upon process models discovered from a given event log or learned via deep learning. Each group of approaches has its own strengths and limitations. The former is usually restricted to the control-flow but it is more interpretable, whereas the latter is not interpretable by nature but has a greater generalization capability on large event logs. Despite the great performance achieved by deep learning approaches, they are still not suitable to be applied to real scenarios and generate value for users. This issue is mainly due to fact their stochasticity is hard to control. To address this problem, we propose the CoSMo framework for implementing process simulation models fully based on deep learning. This framework enables simulating event logs that satisfy a constraint by conditioning the learning phase of a deep neural network. Throughout experiments, the simulation is validated from both control-flow and data-flow perspectives, demonstrating the proposed framework's capability of simulating cases while satisfying imposed conditions

Selecting Optimal Trace Clustering Pipelines with Meta-learning

Trace clustering has been extensively used to discover aspects of the data from event logs. Process Mining techniques guide the identification of sub-logs by grouping traces with similar behaviors, producing more understandable models and improving conformance indicators. Nevertheless, little attention has been posed to the relationship among event log properties, the pipeline of encoding and clustering algorithms, and the quality of the obtained outcome. The present study contributes to the understanding of the aforementioned relationships and provides an automatic selection of a proper combination of algorithms for clustering a given event log. We propose a Meta-Learning framework to recommend the most suitable pipeline for trace clustering, which encompasses the encoding method, clustering algorithm, and its hyperparameters. Our experiments were conducted using a thousand event logs, four encoding techniques, and three clustering methods. Results indicate that our framework sheds light on the trace clustering problem and can assist users in choosing the best pipeline considering their environment

Identification of the hysteretic behaviour of a partial-strength steel-concrete moment-resisting frame structure subject to pseudodynamic tests

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Testing social network metrics for measuring electoral success in the italian municipal campaign of 2011

It is often argued that the bias hidden in Social Media data prevent from using them for any statistical inference. In this paper, we investigate the practicability of a new method for predicting electoral outcomes that is less affected by demographics and self-selection bias. In particular, we put in place a first test to understand which social network analysis metrics can exhibit positive correlation with electoral success. Our analysis is not intended to use social media audience as a sample of the whole electorate but just as a sample of the supporters of a candidate. In conclusion, we speculate on the information we can extract measuring the social network of the groups of supporters. Essentially, we get an overview on the variety and extent of the segments of the population represented in these groups, and this probably correlates with the capacity to attract consensus

Sensitivity analysis of damaged monumental structures: the example of S. Maria del Suffragio in L'Aquila

In Italy, which accounts for an impressive number of architectural heritage sites, a large part of the territory is subject to seismic risk. Nonetheless, also the two recent examples of the 2009 L'Aquila earthquake and 2012 Emilia earthquake confirmed and highlighted the vulnerability of cultural heritage structures to these types of events. In this paper the church of Santa Maria del Suffragio (Anime Sante) in L'Aquila is used as a benchmark for the experimental validation of a finite element model on the basis of the data gathered by the permanent structural health monitoring system installed on the building by IUAV in 2009. Structural health monitoring techniques have been largely applied to cultural Heritage buildings in recent times, mostly because of their non-destructive nature, and they have proven to be a valid tool in assessing the damage evolution and in characterising the global dynamic behaviour of the structure. In particular, a global sensitivity analysis technique has been applied to a finite element model. The model underwent a model updating procedure on the parameters chosen in the sensitivity analysis. The calibrated model is an invaluable tool in assessing the dynamic behaviour of the structure and may serve for several purpose

Education of physical and rehabilitation medicine specialists across Europe: a call for harmonization

BACKGROUND: Physical and rehabilitation medicine (PRM) is well established in Europe and officially recognized by the European Union of Medical Specialists (UEMS). The European PRM Board works to promote patient safety and quality of care through the development of the highest standards of medical training and healthcare across Europe as well as the harmonization of PRM specialists' qualifications. In its Action Plan for 2014-2018, the UEMS PRM Board has included the harmonization of the PRM curriculum among the EU countries, as one of its main goals. Based on a European Directive, the Belgian Superior Council is envisaging a reform of the PRM curriculum. AIM: The aim of this paper is to present the current situation of PRM education in Europe according to the survey carried out by the Belgium Task Force. DESIGN: An online survey was posted on May 3rd 2015 to all delegates of the UEMS PRM Section and Board. Two questions were formulated: 1) What is the duration and curriculum of PRM training in your country? 2) Does a Postgraduate Rehabilitation training exist for other medical specialties? RESULTS: The majority of the PRM training programs in Europe have a duration ranging from 4 to 5 years, and are not aiming at downsizing the duration to the European minimal training period of 3 years. The vast majority (70%) of the responding countries don't offer an additional accreditation of Rehabilitation for other medical specialties CONCLUSIONS: Comparing PRM training programs in Europe can support the long-awaited reform of the PRM postgraduate curriculum in Belgium and gives perspective to agree on a transparent and comparable specialty training throughout Europe. Providing a more comparable training promotes the establishment of PRM and its rehabilitation service provisions in the world

Documenting Complexity for the 20TH Century Heritage: the Enriched 3d Models of the Turin Exposition Nervi's Halls Digitization

Abstract. Great attention is increasingly paid to the heritage belonging to the XX century, particularly for the spatial structures made of concrete, that are a significant trait of this modern movement architecture. Since they demand today urgent conservation plans sustaining their deterioration, the multidisciplinary researches should devotes a profound investigations for tailored approaches providing a clear indication of best practices and recommendation for correct 3D documentation, information management and structural assessment and monitoring. In this framework, the Geomatics approaches are advancing the interests toward the multi-scale and multi-sensor digitization and for supporting management of complex information in enriched 3D models. The iconic halls B and C in Torino Esposizioni (Italy), designed by Pier Luigi Nervi, is the case study presented. It was recently awarded by the Getty Keeping it Modern grant. The multi-disciplinary research conducted, still in progress, focuses a particularly into the investigation of the structural analysis and consistency of ferrocement elements of the vaulted system finalized to the structural condition assessment. Here the role of multi-scale and multi-sensor 3D models is investigated, such as the development of a digital twin of the halls as a starting point to create an enriched informative system. The reconstruction of this model particularly considering the large extension and the complexity of the spaces, is addressed to works as a collector of 3D multi-sensor data and information related to the diagnostic investigation on structural health monitoring for the durability of ferrocement elements

In-Operation Experimental Modal Analysis of a Three Span Open-Spandrel RC Arch Bridge

This paper presents the results of the dynamic tests conducted on a historical reinforced concrete arch bridge located in the Tuscan-Emilian Apennines, in the province of Parma (Italy). The design of the sensors location was determined in order to investigate the possible separation into bodies operated by the joints between the different spans. The ambient vibration data allowed the dynamic characterization of the 3-span arch bridge with the total length of 146 m and 18 m in width. The interpretation of the main global modes, distinctly detected through time domain identification methods, indicates that the horizontal response is governed by the deformability of the joints. The results show that the obtained modal features provide a reliable reference for the subsequent updating of the bridge FE model

" Sensitivity analysis of damaged monumental structures: the example of S. Maria del Suffragio in L'Aquila "

In Italy, which accounts for an impressive number of architectural heritage sites, a large part of the territory is subject to seismic risk. Nonetheless, also the two recent examples of the 2009 L'Aquila earthquake and 2012 Emilia earthquake confirmed and highlighted the vulnerability of cultural heritage structures to these types of events. In this paper the church of Santa Maria del Suffragio (Anime Sante) in L'Aquila is used as a benchmark for the experimental validation of a finite element model on the basis of the data gathered by the permanent structural health monitoring system installed on the building by IUAV in 2009. Structural health monitoring techniques have been largely applied to cultural Heritage buildings in recent times, mostly because of their non-destructive nature, and they have proven to be a valid tool in assessing the damage evolution and in characterising the global dynamic behaviour of the structure. In particular, a global sensitivity analysis technique has been applied to a finite element model. The model underwent a model updating procedure on the parameters chosen in the sensitivity analysis. The calibrated model is an invaluable tool in assessing the dynamic behaviour of the structure and may serve for several purposes