Evaluating currency crises: A multivariate Markov regime switching approach

This paper provides an empirical framework to analyse the nature of currency crises byextending earlier work of Jeanne and Masson (2000) who suggest that a currency crisismodel with multiple equilibria can be estimated using Markov regime switching (MRS)models. However, Jeanne and Masson (2000) assume that the transition probabilitiesacross equilibria are constant and independent of fundamentals. Thus, currency crisis isdriven by a sunspot unrelated to fundamentals. This paper further contributes to theliterature by suggesting a multivariate MRS model to analyse the nature of currencycrises. In the new set up, one can test for the impact of the unobserved dynamics offundamentals on the probability of devaluation. Empirical evidence shows thatexpectations about fundamentals, which are reflected by their unobserved state variables,not only affect the probability of devaluation but also can be used to forecast a currencycrisis one period ahead

Perceived structure and achievement goals as predictors of student' self-regulated learning and affect and the mediating role of competence need satisfaction

Cataloged from PDF version of article.We investigated the extent to which perceived structure and personal achievement goals could explain students' effective learning strategies and affect-related experiences in a sample of Greek adolescent students (N=606; 45.4% males; mean age: M=15.05, SD=1.43). Having controlled for students' social desirability responses, we used multilevel analyses, and found that between-student (i.e., within class) differences in perceived structure related positively to learning strategies and positive affect and negatively to negative affect, with the relations being partially mediated by competence need satisfaction. In addition, we found between-student differences in the relations of mastery-approach, performance-approach, and performanceavoidance goals to the learning-strategy and affect outcomes. Moreover, at the between-class level, perceived structure related positively to learning strategies and positive affect, and negatively to depressive feelings. Finally, an interesting cross-level interaction between perceived structure and performance-avoidance goals for negative affect revealed that well-structured classrooms attenuated the positive, harmful relation between performance-avoidance goals and negative affect. These findings indicate the key role of structure and the endorsement of mastery-approach goals in the classroom

Personal and contextual antecedents of achievement goals: Their direct and indirect relations to students' learning strategies

Cataloged from PDF version of article.In this correlational research, we investigated to what extent achievement goals, in conjunction with need for achievement and fear of failure as well as perceived classroom goal structures, are related to learning strategies among upper elementary school students. After taking into account students' tendency to respond in a socially desirable way, we found, through path analysis, that mastery-approach goals partially mediated the relation of need for achievement and perceived mastery goal structures to learning strategies. These findings are discussed within the hierarchical model framework proposed by Elliot (1999). They suggest that the simultaneous examination of personal and contextual antecedents of achievement goals can enhance our understanding of the processes underlying achievement motivation and its outcomes

Within-person configurations and temporal relations of personal and perceived parent-promoted life goals to school correlates among adolescents

Cataloged from PDF version of article.Grounded in self-determination theory, this longitudinal study examined the academic correlates of middle and high school students' (N = 923; 33.4% male) intrinsic and extrinsic aspirations (i.e., life goals) and the type of aspirations that they perceive their parents to promote to them. Person-centered analysis revealed 3 meaningful groups: a relatively high intrinsic aspiration group, a relatively moderate intrinsic aspiration group, and a relatively high-intrinsic and high-extrinsic aspiration group. Tukey post hoc comparisons indicated that students in the high intrinsic aspiration group scored higher on mastery-approach goals, effort regulation, and grades than students in the other 2 groups and lower on performance-approach goals and test anxiety than students in the high-high aspiration group. A match between learners' own aspiration profile and the perceived parent-promoted aspiration profile did not alter these between-group differences. Further, intrapersonal fluctuations of intrinsic aspirations covaried with mastery-approach goals over a 1-year time interval, while extrinsic aspirations covaried with performance-approach goals and test anxiety in the same period; none of these within-person associations were consistently moderated by between-student differences in perceived parental aspiration promotion. Instead, perceived parent-promoted intrinsic and extrinsic aspirations were, respectively, positive and negative predictors of between-student differences in positive school functioning. The present results highlight the importance of endorsing and promoting intrinsic aspirations for school adjustment. © 2013 American Psychological Association

Vulnerability prediction for secure healthcare supply chain service delivery

Healthcare organisations are constantly facing sophisticated cyberattacks due to the sensitivity and criticality of patient health care information and wide connectivity of medical devices. Such attacks can pose potential disruptions to critical services delivery. There are number of existing works that focus on using Machine Learning(ML) models for pre-dicting vulnerability and exploitation but most of these works focused on parameterized values to predict severity and exploitability. This paper proposes a novel method that uses ontology axioms to define essential concepts related to the overall healthcare ecosystem and to ensure semantic consistency checking among such concepts. The application of on-tology enables the formal specification and description of healthcare ecosystem and the key elements used in vulnerabil-ity assessment as a set of concepts. Such specification also strengthens the relationships that exist between healthcare-based and vulnerability assessment concepts, in addition to semantic definition and reasoning of the concepts. Our work also makes use of Machine Learning techniques to predict possible security vulnerabilities in health care supply chain services. The paper demonstrates the applicability of our work by using vulnerability datasets to predict the exploitation. The results show that the conceptualization of healthcare sector cybersecurity using an ontological approach provides mechanisms to better understand the correlation between the healthcare sector and the security domain, while the ML algorithms increase the accuracy of the vulnerability exploitability prediction. Our result shows that using Linear Regres-sion, Decision Tree and Random Forest provided a reasonable result for predicting vulnerability exploitability

Sustainable transport modes, travel satisfaction, and emotions: Evidence from car-dependent compact cities

This study investigates how the use of sustainable transport modes relates to travel satisfaction (general evaluation of travel) and travel affect (emotions during travel) in car-dependent compact cities. Thereby, the study provides evidence on sustainable mobility and travel-related well-being in a context of compact urban form but inadequate provisions for public transport, walking, and cycling. A mixed-methods approach was applied comprising quantitative and qualitative analyses of data from the two major cities of Greece, i.e., Athens and Thessaloniki. Travel satisfaction and travel affect are found to be highest for those who walk for commuting, independently of travel time and other factors. Conversely, travel satisfaction and travel affect are lowest for public transport users, largely due to very long travel times but also poor public transport services in one of the two cities. Results indicate that the experience of traveling by public transport, car, and motorcycle within urban areas greatly depends on transport provision and policies. Overall, findings support the idea that to shift to pleasant, satisfying, and sustainable mobility in car-dependent compact cities, car restrictions should be accompanied by massive improvements in public transport, high-quality walking and cycling infrastructure, and an integrated coordination of different modes

An Agent-Based System to support Geo-Information Analysis

Geo-Information Systems (GIS) are software for the handling and analysis of spatial data and are at the heart of Geo-Information Science (GISc). Most GIS functions require interaction with human experts. This is considered problematic since it causes extra complexity and increases the amount of resources required. Agent Technology has the potential to assist in reducing this problem. However the current application of software agents to the GIS domain is very limited and fails to take into account the full functionality and advantages of Agent Technology. In this paper we discuss the application of agents in GIS and argue for the need to produce an agentbased framework for GIS. By way of context we define a novel agent-based system for one important aspect of GIS, the construction of a variogram. We quantitatively compare our architecture with two the existing agent-based tools: RePast for ArcGIS and Oracle Agents