Scenario-based preparedness plan for floods

The increasing trend of disaster victims globally is posing a complex challenge for disaster management authorities. Moreover, to accomplish successful transition between preparedness and response, it is important to consider the different features inherent to each type of disaster. Floods are portrayed as one of the most frequent and harmful disasters, hence introducing the necessity to develop a tool for disaster preparedness to perform efficient and effective flood management. The purpose of the article is to introduce a method to simultaneously define the proper location of shelters and distribution centers, along with the allocation of prepositioned goods and distribution decisions required to satisfy flood victims. The tool combines the use of a raster geographical information system (GIS) and an optimization model. The GIS determines the flood hazard of the city areas aiming to assess the flood situation and to discard floodable facilities. Then, the multi-commodity multimodal optimization model is solved to obtain the Pareto frontier of two criteria: distance and cost. The methodology was applied to a case study in the flood of Villahermosa, Mexico, in 2007, and the results were compared to an optimized scenario of the guidelines followed by Mexican authorities, concluding that the value of the performance measures was improved using the developed method. Furthermore, the results exhibited the possibility to provide adequate care for people affected with less facilities than the current approach and the advantages of considering more than one distribution center for relief prepositioning.

Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View

The length of stay of preterm infants in a neonatology service has become an issue of a growing concern, namely considering, on the one hand, the mothers and infants health conditions and, on the other hand, the scarce healthcare facilities own resources. Thus, a pro-active strategy for problem solving has to be put in place, either to improve the quality-of-service provided or to reduce the inherent financial costs. Therefore, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a case-based problem solving methodology to computing, that caters for the handling of incomplete, unknown, or even contradictory in-formation. The proposed model has been quite accurate in predicting the length of stay (overall accuracy of 84.9%) and by reducing the computational time with values around 21.3%.

Understanding conceptual schemas: exploring the role of application and IS domain knowledge

Although information systems (IS) problem solving involves knowledge of both the IS and application domains, little attention has been paid to the role of application domain knowledge. In this study, which is set in the context of conceptual modeling, we examine the effects of both IS and application domain knowledge on different types of schema understanding tasks: syntactic and semantic comprehension tasks and schema-based problem-solving tasks. Our thesis was that while IS domain knowledge is important in solving all such tasks, the role of application domain knowledge is contingent upon the type of understanding task under investigation. We use the theory of cognitive fit to establish theoretical differences in the role of application domain knowledge among the different types of schema understanding tasks. We hypothesize that application domain knowledge does not influence the solution of syntactic and semantic comprehension tasks for which cognitive fit exists, but does influence the solution of schema-based problem-solving tasks for which cognitive fit does not exist. To assess performance on different types of conceptual schema understanding tasks, we conducted a laboratory experiment in which participants with high- and low-IS domain knowledge responded to two equivalent conceptual schemas that represented high and low levels of application knowledge (familiar and unfamiliar application domains). As expected, we found that IS domain knowledge is important in the solution of all types of conceptual schema understanding tasks in both familiar and unfamiliar applications domains, and that the effect of application domain knowledge is contingent on task type. Our findings for the EER model were similar to those for the ER model. Given the differential effects of application domain knowledge on different types of tasks, this study highlights the importance of considering more than one application domain in designing future studies on conceptual modeling.

An Artificial Intelligence Approach to Dyscalculia

Dyscalculia stands for a brain-based condition that makes it hard to make sense of numbers and mathematical concepts. Some adolescents with dyscalculia cannot grasp basic number concepts. They work hard to learn and memorize basic number facts. They may know what to do in mathematical classes but do not understand why they are doing it. In other words, they miss the logic behind it. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work focuses on the development of an Intelligent System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming framework to Knowledge Representation and Reasoning, complemented with a Case-Based problem solving approach to computing, that allows for the handling of incomplete, unknown, or even contradictory information.

Ecological Literacy And Beyond: Problem-based Learning For Future Professionals.

Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

Using problem-based learning for introducing producer theory and market structure in intermediate microeconomics

This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role isto provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

Engendering Group Support Based Foresight for Capital Intensive Manufacturing Industries - Case Paper and Steel Industry Scenarios by 2018

In recent times of global turmoil, the need for uncertainty management has become ever momentous. The need for enhanced foresight especially concerns capital-intensive industries, which need to commit their resources and assets with long-term planning horizons. Scenario planning has been acknowledged to have many virtues - and limitations - concerning the mapping of the future and illustrating the alternative development paths. The present study has been initiated to address both the need of improved foresight in two capital-intensive industries, i.e. the paper and steel industries and the imperfections in the current scenario practice. The research problem has been approached by engendering a problem-solving vehicle, which combines, e.g. elements of generic scenario process, face-to-face group support methods, deductive scenario reasoning and causal mapping into a fully integrated scenario process. The process, called the SAGES scenario framework, has been empirically tested by creating alternative futures for two capital-intensive industries, i.e. the paper and steel industries. Three scenarios for each industry have been engendered together with the identification of the key megatrends, the most important foreign investment determinants, key future drivers and leading indicators for the materialisation of the scenarios. The empirical results revealed a two-fold outlook for the paper industry, while the steel industry future was seen as much more positive. The research found support for utilising group support systems in scenario and strategic planning context with some limitations. Key perceived benefits include high time-efficiency, productivity and lower resource-intensiveness. Group support also seems to enhance participant satisfaction, encourage innovative thinking and provide the users with personalised qualitative scenarios.

Using problem-based learning for introducing producer theory and market structure in intermediate microeconomics

This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role is to provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

Measuring the influence of Cooperative Learning and Project Based Learning on problem solvin skill.

The aim of this study is to evaluate the effects obtained after applying two active learning methodologies (cooperative learning and project based learning) to the achievement of the competence problem solving. This study was carried out at the Technical University of Madrid, where these methodologies were applied to two Operating Systems courses. The first hypothesis tested was whether the implementation of active learning methodologies favours the achievement of ?problem solving?. The second hypothesis was focused on testing if students with higher rates in problem solving competence obtain better results in their academic performance. The results indicated that active learning methodologies do not produce any significant change in the generic competence ?problem solving? during the period analysed. Concerning this, we consider that students should work with these methodologies for a longer period, besides having a specific training. Nevertheless, a close correlation between problem solving self appraisal and academic performance has been detected.

A Computer-Based Strategy for Practical Skills Teaching

An adaptive learning technology embedded in e-learning environments ensures choice of the structure, content, and activities for each individual learner according to the teaching team’s domain and didactic knowledge and skills. In this paper a computer-based scenario for application of an adaptive navigation technology is proposed and demonstrated on an example course topic.

A qualitative study of the clinical practice of graduates of a problem-based physical therapy program

The purpose of this study was to examine the perspectives of three graduates of a problem-based leaning (PBL) physical therapy (PT) program about their clinical practice. The study used the qualitative methods of observations, interviews, and journaling to gather the data. Three sessions of audiotaped interviews and two observation sessions were conducted with three exemplars from Nova Southeastern University PBL PT program. Each participant also maintained a reflective journal. The data were analyzed using content analysis. A systematic filing system was used by employing a mechanical means of maintaining and indexing coded data and sorting data into coded classifications of subtopics or themes. All interview transcripts, field notes from observations, and journal accounts were read, and index sheets were appropriately annotated. From the findings of the study, it was noted that, from the participants' perspectives, they were practicing at typically expected levels as clinicians. The attributes that governed the perspectives of the participants about their physical therapy clinical practice included flexibility, reflection, analysis, decision-making, self-reliance, problem-solving, independent thinking, and critical thinking. Further, the findings indicated that the factors that influenced those attributes included the PBL process, parents' value system, self-reliant personality, innate personality traits, and deliberate choice. Finally, the findings indicated that the participants' perspectives, for the most part, appeared to support the espoused efficacy of the PBL educational approach. In conclusion, there is evidence that the physical therapy clinical practice of the participants were positively impacted by the PBL curriculum. Among the many attributes they noted which governed these perspectives, problem-solving, as postulated by Barrows, was one of the most frequently mentioned benefits gained from their PBL PT training. With more schools adopting the PBL approach, this research will hopefully add to the knowledge base regarding the efficacy of embracing a problem-based learning instructional approach in physical therapy programs. ^

Subject -centered and problem -based approaches to teaching clinical competence in physical therapy

Physical therapy students must apply the relevant information learned in their academic and clinical experience to problem solve in treating patients. I compared the clinical cognitive competence in patient care of second-year masters students enrolled in two different curricular programs: modified problem-based (M P-B; n = 27) and subject-centered (S-C; n = 41). Main features of S-C learning include lecture and demonstration as the major teaching strategies and no exposure to patients or problem solving learning until the sciences (knowledge) have been taught. Comparatively, main features of M P-B learning include case study in small student groups as the main teaching strategy, early and frequent exposure to patients, and knowledge and problem solving skills learned together for each specific case. Basic and clinical orthopedic knowledge was measured with a written test with open-ended items. Problem solving skills were measured with a written case study patient problem test yielding three subscores: assessment, problem identification, and treatment planning. ^ Results indicated that among the demographic and educational characteristics analyzed, there was a significant difference between groups on ethnicity, bachelor degree type, admission GPA, and current GPA, but there was no significant difference on gender, age, possession of a physical therapy assistant license, and GRE score. In addition, the M P-B group achieved a significantly higher adjusted mean score on the orthopedic knowledge test after controlling for GRE scores. The S-C group achieved a significantly higher adjusted mean total score and treatment management subscore on the case study test after controlling for orthopedic knowledge test scores. These findings did not support their respective research hypotheses. There was no significant difference between groups on the assessment and problem identification subscores of the case study test. The integrated M P-B approach promoted superior retention of basic and clinical science knowledge. The results on problem solving skills were mixed. The S-C approach facilitated superior treatment planning skills, but equivalent patient assessment and problem identification skills by emphasizing all equally and exposing the students to more patients with a wider variety of orthopedic physical therapy needs than in the M P-B approach. ^

How does problem based learning fit with cognitive load theory?

This paper reports on an investigation with first year undergraduate Product Design and Management students within a School of Engineering. The students at the time of this investigation had studied fundamental engineering science and mathematics for one semester. The students were given an open ended, ill formed problem which involved designing a simple bridge to cross a river. They were given a talk on problem solving and given a rubric to follow, if they chose to do so. They were not given any formulae or procedures needed in order to resolve the problem. In theory, they possessed the knowledge to ask the right questions in order to make assumptions but, in practice, it turned out they were unable to link their a priori knowledge to resolve this problem. They were able to solve simple beam problems when given closed questions. The results show they were unable to visualise a simple bridge as an augmented beam problem and ask pertinent questions and hence formulate appropriate assumptions in order to offer resolutions.

Problem-Based SRS: método para especificação de requisitos de software baseado em problemas

Requirements specification has long been recognized as critical activity in software development processes because of its impact on project risks when poorly performed. A large amount of studies addresses theoretical aspects, propositions of techniques, and recommended practices for Requirements Engineering (RE). To be successful, RE have to ensure that the specified requirements are complete and correct what means that all intents of the stakeholders in a given business context are covered by the requirements and that no unnecessary requirement was introduced. However, the accurate capture the business intents of the stakeholders remains a challenge and it is a major factor of software project failures. This master’s dissertation presents a novel method referred to as “Problem-Based SRS” aiming at improving the quality of the Software Requirements Specification (SRS) in the sense that the stated requirements provide suitable answers to real customer ́s businesses issues. In this approach, the knowledge about the software requirements is constructed from the knowledge about the customer ́s problems. Problem-Based SRS consists in an organization of activities and outcome objects through a process that contains five main steps. It aims at supporting the software requirements engineering team to systematically analyze the business context and specify the software requirements, taking also into account a first glance and vision of the software. The quality aspects of the specifications are evaluated using traceability techniques and axiomatic design principles. The cases studies conducted and presented in this document point out that the proposed method can contribute significantly to improve the software requirements specification.

Three-phase harmonic distortion state estimation algorithm based on evolutionary strategies

This paper presents a new methodology to estimate unbalanced harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The problem solving algorithm herein proposed makes use of data from various power quality meters, which can either be synchronized by high technology GPS devices or by using information from a fundamental frequency load flow, what makes the overall power quality monitoring system much less costly. The ES based harmonic estimation model is applied to a 14 bus network to compare its performance to a conventional Monte Carlo approach. It is also applied to a 50 bus subtransmission network in order to compare the three-phase and single-phase approaches as well as the robustness of the proposed method. (C) 2010 Elsevier B.V. All rights reserved.