"Last-Mile" preparation for a potential disaster - Interdisciplinary approach towards tsunami early warning and an evacuation information system for the coastal city of Padang, Indonesia

Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of smallscale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socioeconomic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity. © Author(s) 2009.

A Soft Computing Approach to Quality Evaluation of General Chemistry Learning in Higher Education

In contemporary societies higher education must shape individuals able to solve problems in a workable and simpler manner and, therefore, a multidisciplinary view of the problems, with insights in disciplines like psychology, mathematics or computer science becomes mandatory. Undeniably, the great challenge for teachers is to provide a comprehensive training in General Chemistry with high standards of quality, and aiming not only at the promotion of the student’s academic success, but also at the understanding of the competences/skills required to their future doings. Thus, this work will be focused on the development of an intelligent system to assess the Quality-of-General-Chemistry-Learning, based on factors related with subject, teachers and students.

Integer Linear Programming for Sequence Problems: A general approach to reduce the problem size

Sequence problems belong to the most challenging interdisciplinary topics of the actuality. They are ubiquitous in science and daily life and occur, for example, in form of DNA sequences encoding all information of an organism, as a text (natural or formal) or in form of a computer program. Therefore, sequence problems occur in many variations in computational biology (drug development), coding theory, data compression, quantitative and computational linguistics (e.g. machine translation). In recent years appeared some proposals to formulate sequence problems like the closest string problem (CSP) and the farthest string problem (FSP) as an Integer Linear Programming Problem (ILPP). In the present talk we present a general novel approach to reduce the size of the ILPP by grouping isomorphous columns of the string matrix together. The approach is of practical use, since the solution of sequence problems is very time consuming, in particular when the sequences are long.

A REMOTE SENSING APPROACH TO CHARACTERIZE THE HYDROGEOLOGY OF MOUNTAINOUS AREAS: APPLICATION TO THE QUITO AQUIFER SYSTEM (QAS), ECUADOR

Climate change, intensive use, and population growth are threatening the availability of water resources. New sources of water, better knowledge of existing ones, and improved water management strategies are of paramount importance. Ground water is often considered as primary water source due to its advantages in terms of quantity, spatial distribution, and natural quality. Remote sensing techniques afford scientists a unique opportunity to characterize landscapes in order to assess groundwater resources, particularly in tectonically influenced areas. Aquifers in volcanic basins are considered the most productive aquifers in Latin America. Although topography is considered the primary driving force for groundwater flows in mountainous terrains, tectonic activity increases the complexity of these groundwater systems by altering the integrity of sedimentary rock units and the overlying drainage networks. Structural controls affect the primary hydraulic properties of the rock formations by developing barriers to flow in some cases and zones of preferential infiltration and subterranean in others. The study area focuses on the Quito Aquifer System (QAS) in Ecuador. The characterization of the hydrogeology started with a lineament analysis based on a combined remote sensing and digital terrain analysis approach. The application of classical tools for regional hydrogeological evaluation and shallow geophysical methods were useful to evaluate the impact of faulting and fracturing on the aquifer system. Given the spatial extension of the area and the complexity of the system, two levels of analysis were applied in this study. At the regional level, a lineament map was created for the QAS. Relationships between fractures, faults and lineaments and the configuration of the groundwater flow on the QAS were determined. At the local level, on the Plateaus region of the QAS, a detailed lineament map was obtained by using high-spatial-resolution satellite imagery and aspect map derived from a digital elevation model (DEM). This map was complemented by the analysis of morphotectonic indicators and shallow geophysics that characterize fracture patterns. The development of the groundwater flow system was studied, drawing upon data pertaining to the aquifer system physical characteristics and topography. Hydrochemistry was used to ascertain the groundwater evolution and verify the correspondence of the flow patterns proposed in the flow system analysis. Isotopic analysis was employed to verify the origin of groundwater. The results of this study show that tectonism plays a very important role for the hydrology of the QAS. The results also demonstrate that faults influence a great deal of the topographic characteristics of the QAS and subsequently the configuration of the groundwater flow. Moreover, for the Plateaus region, the results demonstrate that the aquifer flow systems are affected by secondary porosity. This is a new conceptualization of the functioning of the aquifers on the QAS that will significantly contribute to the development of better strategies for the management of this important water resource.

An interprofessional approach to improving paediatric medication safety

Safe drug prescribing and administration are essential elements within undergraduate healthcare curricula, but medication errors, especially in paediatric practice, continue to compromise patient safety. In this area of clinical care, collective responsibility, team working and communication between health professionals have been identified as key elements in safe clinical practice. To date, there is limited research evidence as to how best to deliver teaching and learning of these competencies to practitioners of the future.An interprofessional workshop to facilitate learning of knowledge, core competencies, communication and team working skills in paediatric drug prescribing and administration at undergraduate level was developed and evaluated. The practical, ward-based workshop was delivered to 4th year medical and 3rd year nursing students and evaluated using a pre and post workshop questionnaire with open-ended response questions.Following the workshop, students reported an increase in their knowledge and awareness of paediatric medication safety and the causes of medication errors (p < 0.001), with the greatest increase noted among medical students. Highly significant changes in students' attitudes to shared learning were observed, indicating that safe medication practice is learnt more effectively with students from other healthcare disciplines. Qualitative data revealed that students' participation in the workshop improved communication and teamworking skills, and led to greater awareness of the role of other healthcare professionals.This study has helped bridge the knowledge-skills gap, demonstrating how an interprofessional approach to drug prescribing and administration has the potential to improve quality and safety within healthcare.

Intersubjectivity and sentiment:from language to knowledge

Intersubjectivity is an important concept in psychology and sociology. It refers to sharing conceptualizations through social interactions in a community and using such shared conceptualization as a resource to interpret things that happen in everyday life. In this work, we make use of intersubjectivity as the basis to model shared stance and subjectivity for sentiment analysis. We construct an intersubjectivity network which links review writers, terms they used, as well as the polarities of the terms. Based on this network model, we propose a method to learn writer embeddings which are subsequently incorporated into a convolutional neural network for sentiment analysis. Evaluations on the IMDB, Yelp 2013 and Yelp 2014 datasets show that the proposed approach has achieved the state-of-the-art performance.

A probabilistic approach to user mobility prediction for wireless services.

Mobile and wireless networks have long exploited mobility predictions, focused on predicting the future location of given users, to perform more efficient network resource management. In this paper, we present a new approach in which we provide predictions as a probability distribution of the likelihood of moving to a set of future locations. This approach provides wireless services a greater amount of knowledge and enables them to perform more effectively. We present a framework for the evaluation of this new type of predictor, and develop 2 new predictors, HEM and G-Stat. We evaluate our predictors accuracy in predicting future cells for mobile users, using two large geolocation data sets, from MDC [11], [12] and Crawdad [13]. We show that our predictors can successfully predict with as low as an average 2.2% inaccuracy in certain scenarios.

Structured professional judgement approach to risk assessment: generalisability across patient groups for the prediction of adverse outcomes in secure mental health care

This is a redacted version of the the final thesis. Copyright material has been removed to comply with UK Copyright Law.

A literary approach to teaching english language in a multicultural classroom

Literature is not generally considered as a coherent branch of the curriculum in relation to language development in either native or foreign language teaching. As teachers of English in multicultural Indian classrooms, we come across students with varying degrees of competence in English language learning. Although language learning is a natural process for natives, students of other languages put in colossal efforts to learn it. Despite their sincere efforts, they face challenges regarding pronunciation, spelling, and vocabulary. Indian classrooms are a microcosm of the larger society, so teaching English language in a manner that equips the students to face the cutthroat competition has become a necessity and a challenge for English language teachers. English today has become the key determinant for being successful in their careers. The hackneyed and stereotypical methods of teaching are not acceptable now. Teachers are no longer arbitrary dispensers of knowledge, but they are playing the role of a guide and facilitator for the students. Teachers of English are using innovative ideas to make English language teaching and learning interesting and simple. Teachers have started using literary texts and their analyses to explore and ignite the imagination and creative skills of the students. One needs to think and rethink the contribution of literature to intelligent thinking as well as its role in the process of teaching/learning. This article is, therefore, an attempt at exploring the nature of the literary experience in the present-day classrooms and the broader role of literature in life.

A Microdata Analysis Approach to Transport Infrastructure Maintenance

Maintenance of transport infrastructure assets is widely advocated as the key in minimizing current and future costs of the transportation network. While effective maintenance decisions are often a result of engineering skills and practical knowledge, efficient decisions must also account for the net result over an asset's life-cycle. One essential aspect in the long term perspective of transport infrastructure maintenance is to proactively estimate maintenance needs. In dealing with immediate maintenance actions, support tools that can prioritize potential maintenance candidates are important to obtain an efficient maintenance strategy. This dissertation consists of five individual research papers presenting a microdata analysis approach to transport infrastructure maintenance. Microdata analysis is a multidisciplinary field in which large quantities of data is collected, analyzed, and interpreted to improve decision-making. Increased access to transport infrastructure data enables a deeper understanding of causal effects and a possibility to make predictions of future outcomes. The microdata analysis approach covers the complete process from data collection to actual decisions and is therefore well suited for the task of improving efficiency in transport infrastructure maintenance. Statistical modeling was the selected analysis method in this dissertation and provided solutions to the different problems presented in each of the five papers. In Paper I, a time-to-event model was used to estimate remaining road pavement lifetimes in Sweden. In Paper II, an extension of the model in Paper I assessed the impact of latent variables on road lifetimes; displaying the sections in a road network that are weaker due to e.g. subsoil conditions or undetected heavy traffic. The study in Paper III incorporated a probabilistic parametric distribution as a representation of road lifetimes into an equation for the marginal cost of road wear. Differentiated road wear marginal costs for heavy and light vehicles are an important information basis for decisions regarding vehicle miles traveled (VMT) taxation policies. In Paper IV, a distribution based clustering method was used to distinguish between road segments that are deteriorating and road segments that have a stationary road condition. Within railway networks, temporary speed restrictions are often imposed because of maintenance and must be addressed in order to keep punctuality. The study in Paper V evaluated the empirical effect on running time of speed restrictions on a Norwegian railway line using a generalized linear mixed model.

Reflections on using a community-based and multisystem approach to transforming school-based intervention for children with developmental motor disorders

Evidence-based management of Developmental Coordination Disorder (DCD) in school-age children requires putting into practice the best and most current research findings, including evidence that early identification, self-management, prevention of secondary disability, and enhanced participation are the most appropriate foci of school-based occupational therapy. Partnering for Change (P4C) is a new school-based intervention based upon these principles that has been developed and evaluated in Ontario, Canada over an 8-year period. Our experience to date indicates that its implementation in schools is highly complex with involvement of multiple stakeholders across health and education sectors. In this paper, we describe and reflect upon our team’s experience in using community-based participatory action research, knowledge translation, and implementation science to transform evidence-informed practice with children who have DCD.

The difference of Being in the early modern world: a relational-material approach to life in Scotland in the period of the witch trials

This thesis investigates how ways of being in different ontologies emerge from material and embodied practice. This general concern is explored through the particular case study of Scotland in the period of the witch trials (the 16th and 17th centuries C.E.). The field of early modern Scottish witchcraft studies has been active and dynamic over the past 15 years but its prioritisation of what people said over what they did leaves a clear gap for a situated and relational approach focusing upon materiality. Such an approach requires a move away from the Cartesian dichotomies of modern ontology to recognise past beliefs as real to those who experienced them, coconstitutive of embodiment and of the material worlds people inhabited. In theory, method and practice, this demands a different way of exploring past worlds to avoid flattening strange data. To this end, the study incorporates narratives and ‘disruptions’ – unique engagements with Contemporary Art which facilitate understanding by enabling the temporary suspension of disbelief. The methodology is iterative, tacking between material and written sources in order to better understand the heterogeneous assemblages of early modern (counter-) witchcraft. Previously separate areas of discourse are (re-)constituted into alternative ontic categories of newly-parallel materials. New interpretations of things, places, bodies and personhoods emerge, raising questions about early modern experiences of the world. Three thematic chapters explore different sets of collaborative agencies as they entwine into new things, co-fabricating a very different world. Moving between witch trial accounts, healing wells, infant burial grounds, animals, discipline artefacts and charms, the boundaries of all prove highly permeable. People, cloth and place bleed into one another through contact; trees and water emerge as powerful agents of magical-place-making; and people and animals meet to become single, hybrid-persons spread over two bodies. Life and death consistently emerge as protracted processes with the capacity to overlap and occur simultaneously in problematic ways. The research presented in this thesis establishes a new way of looking at the nature of Being as experienced by early modern Scots. This provides a foundation for further studies, which can draw in other materials not explored here such as communion wares and metal charms. Comparison with other early modern Western societies may also prove fruitful. Furthermore, the methodology may be suitable for application to other interdisciplinary projects incorporating historical and material evidence.

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.

A Case-Based Approach to Nosocomial Infection Detection

The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time.

A Soft Computing Approach to Acute Coronary Syndrome

Acute Coronary Syndrome (ACS) is transversal to a broad and heterogeneous set of human beings, and assumed as a serious diagnosis and risk stratification problem. Although one may be faced with or had at his disposition different tools as biomarkers for the diagnosis and prognosis of ACS, they have to be previously evaluated and validated in different scenarios and patient cohorts. Besides ensuring that a diagnosis is correct, attention should also be directed to ensure that therapies are either correctly or safely applied. Indeed, this work will focus on the development of a diagnosis decision support system in terms of its knowledge representation and reasoning mechanisms, given here in terms of a formal framework based on Logic Programming, complemented with a problem solving methodology to computing anchored on Artificial Neural Networks. On the one hand it caters for the evaluation of ACS predisposing risk and the respective Degree-of-Confidence that one has on such a happening. On the other hand it may be seen as a major development on the Multi-Value Logics to understand things and ones behavior. Undeniably, the proposed model allows for an improvement of the diagnosis process, classifying properly the patients that presented the pathology (sensitivity ranging from 89.7% to 90.9%) as well as classifying the absence of ACS (specificity ranging from 88.4% to 90.2%).