Using mouse dynamics to assess stress during online exams

"Lecture notes in computer science series", ISSN 0302-9743, vol. 9121Stress is a highly complex, subjective and multidimensional phenomenon. Nonetheless, it is also one of our strongest driving forces, pushing us forward and preparing our body and mind to tackle the daily challenges, independently of their nature. The duality of the effects of stress, that can have positive or negative effects, calls for approaches that can take the best out of this biological mechanism, providing means for people to cope effectively with stress. In this paper we propose an approach, based on mouse dynamics, to assess the level of stress of students during online exams. Results show that mouse dynamics change in a consistent manner as stress settles in, allowing for its estimation from the analysis of the mouse usage. This approach will allow to understand how each individual student is affected by stress, providing additional valuable information for educational institutions to efficiently adapt and improve their teaching processes.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012) and project PEst-OE/EEI/UI0752/2014

Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleo data

A hierarchical framework for incorporating modes of climate variability into stochastic simulations of hydrological data is developed, termed the climate-informed multi-time scale stochastic (CIMSS) framework. A case study on two catchments in eastern Australia illustrates this framework. To develop an identifiable model characterizing long-term variability for the first level of the hierarchy, paleoclimate proxies, and instrumental indices describing the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO) are analyzed. A new paleo IPO-PDO time series dating back 440 yr is produced, combining seven IPO-PDO paleo sources using an objective smoothing procedure to fit low-pass filters to individual records. The paleo data analysis indicates that wet/dry IPO-PDO states have a broad range of run lengths, with 90% between 3 and 33 yr and a mean of 15 yr. The Markov chain model, previously used to simulate oscillating wet/dry climate states, is found to underestimate the probability of wet/dry periods >5 yr, and is rejected in favor of a gamma distribution for simulating the run lengths of the wet/dry IPO-PDO states. For the second level of the hierarchy, a seasonal rainfall model is conditioned on the simulated IPO-PDO state. The model is able to replicate observed statistics such as seasonal and multiyear accumulated rainfall distributions and interannual autocorrelations. Mean seasonal rainfall in the IPO-PDO dry states is found to be 15%-28% lower than the wet state at the case study sites. In comparison, an annual lag-one autoregressive model is unable to adequately capture the observed rainfall distribution within separate IPO-PDO states. Copyright © 2011 by the American Geophysical Union.Benjamin J. Henley, Mark A. Thyer, George Kuczera and Stewart W. Frank

Mouse dynamics correlates to student behaviour in computer-based exams

Nowadays, it is common for higher education institutions to use computer-based exams, partly or integrally, in their evaluation processes. These exams, much like their paper-based counterparts, are one of the most significant sources of stress in the life of students. However, the fact that exams are undertaken in a computer allows for new features to be acquired that may provide more reliable insights into the behaviour and state of the student during the exam. In this article we analyse these novel behavioural features and explore, to which extent, they can point out previously unknown phenomena. Specifically, we show that the time a student takes to complete an exam is correlated with mouse dynamics features. In practical terms, we are able to predict the duration of each individual exam with a satisfying error based on the interaction patterns of the student.COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013. This work was funded by ‘EUSTRESS – Sistema de Informação para a monitorização e avaliação ̧ dos níveis do stress e previsão de stress cónico’, N◦2015/017832 P2020 SI I&DT, (NUP, NORTE-01-0247-FEDER-017832) in co-promotion between Optimizer-Lda and ICVS/3B’s-Uminhoinfo:eu-repo/semantics/publishedVersio

Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleo data

A hierarchical framework for incorporating modes of climate variability into stochastic simulations of hydrological data is developed, termed the climate-informed multi-time scale stochastic (CIMSS) framework. A case study on two catchments in eastern Australia illustrates this framework. To develop an identifiable model characterizing long-term variability for the first level of the hierarchy, paleoclimate proxies, and instrumental indices describing the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO) are analyzed. A new paleo IPO-PDO time series dating back 440 yr is produced, combining seven IPO-PDO paleo sources using an objective smoothing procedure to fit low-pass filters to individual records. The paleo data analysis indicates that wet/dry IPO-PDO states have a broad range of run lengths, with 90% between 3 and 33 yr and a mean of 15 yr. The Markov chain model, previously used to simulate oscillating wet/dry climate states, is found to underestimate the probability of wet/dry periods >5 yr, and is rejected in favor of a gamma distribution for simulating the run lengths of the wet/dry IPO-PDO states. For the second level of the hierarchy, a seasonal rainfall model is conditioned on the simulated IPO-PDO state. The model is able to replicate observed statistics such as seasonal and multiyear accumulated rainfall distributions and interannual autocorrelations. Mean seasonal rainfall in the IPO-PDO dry states is found to be 15%-28% lower than the wet state at the case study sites. In comparison, an annual lag-one autoregressive model is unable to adequately capture the observed rainfall distribution within separate IPO-PDO states. Copyright © 2011 by the American Geophysical Union.Benjamin J. Henley, Mark A. Thyer, George Kuczera and Stewart W. Frank

The relationship between crustal density and volcanic rocks in the Western United States including a comparison of isostatic compensation techniques for gravity data correction

Processes and properties controlling magma ascent may include magma viscosity, the stress regime in surrounding country rock, geometric relationship between the rising magma and connected source area (if any), and density contrast between the magma and country rock. The purpose of this study was to determine the role upper crustal density plays in the control of magma ascent through the use of gravity modeling to obtain estimates of crustal density and then relating that density to the type and location of late Tertiary and Quaternary volcanics. A comparison of commonly used isostatic correction techniques was conducted to assess the impact the differences in correction technique have on isostatic gravity anomaly values, and thus on the results of gravity modeling. The choice of isostatic correction method was found to change the isostatic correction value by as much as 30 mgal over 36 km in areas of rapidly changing elevation. However, in most areas the difference in isostatic correction values are long in wavelength and will not greatly impact gravity modeling. A new idea for preparing an isostatic correction is introduced in preliminary form. Models of crustal density contrasts were prepared for three study areas in California and Nevada through the use of forward gravity modeling on isostatic gravity anomaly datasets. The results of the gravity models were gridded layers of crustal density contrasts that would reproduce the value of the isostatic gravity anomaly in that area. The location, type and quantity of late Tertiary and Quaternary volcanics were evaluated with respect to the value of crustal density in the underlying "basement" (lowest layer). Approximately half of the late Tertiary and Quaternary basalt in the study areas has erupted through crust that is less dense than the magma was. It is likely that in these cases that a conduit exists connecting the erupting magma to a deep source to provide sufficient buoyancy force for eruption

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

Quantitative analysis of the receptor-induced apoptotic decision network

Thesis (Ph. D.)--Massachusetts Institute of Technology, Biological Engineering Division, 2008.Includes bibliographical references (p. 157-169).Cells use a complex web of protein signaling pathways to interpret extracellular cues and decide and execute cell fates such as survival, apoptosis, differentiation, and proliferation. Cell decisions can be triggered by subtle, transient signals that are context specific, making them hard to study by conventional experimental methods. In this thesis, we use a systems approach combining quantitative experiments with computational modeling and analysis to understand the regulation of the survival-vs-death decision. A second goal of this thesis was to develop modeling and analysis methods that enable study of signals that are transient or at intermediate activation levels. We addressed the challenge of balancing mechanistic detail and ease of interpretation in modeling by adapting fuzzy logic to analyze a previously published experimental dataset characterizing the dynamic behavior of kinase pathways governing apoptosis in human colon carcinoma cells. Simulations of our fuzzy logic model recapitulated most features of the data and generated several predictions involving pathway crosstalk and regulation. Fuzzy logic models are flexible, able to incorporate qualitative and noisy data, and powerful enough to generate not only quantitative predictions but also biological insights concerning operation of signaling networks. To study transient signals in differential-equation based models, we employed direct Lyapunov exponents (DLEs) to identify phase-space domains of high sensitivity to initial conditions. These domains delineate regions exhibiting qualitatively different transient activities that would be indistinguishable using steady-state analysis but which correspond to different outcomes.(cont.) We combine DLE analysis of a physicochemical model of receptor-mediated apoptosis with single cell data obtained by flow cytometry and FRET-based reporters in live-cell microscopy to classify conditions that alter the usage of two apoptosis pathways (Type I/II apoptosis). While it is generally thought that the control point for Type I/II occurs at the level of initiator caspase activation, we find that Type II cells can be converted to Type I by removal of XIAP, a regulator of effector caspases. Our study suggests that the classification of cells as Type I or II obscures a third variable category of cells that are highly sensitive to changes in the concentrations of key apoptotic network proteins.by Bree Beardsley Aldridge.Ph.D