Structured Approaches for Exploring Interpersonal Relationships in Natural Language Text

Human relationships have long been studied by scientists from domains like sociology, psychology, literature, etc. for understanding people's desires, goals, actions and expected behaviors. In this dissertation we study inter-personal relationships as expressed in natural language text. Modeling inter-personal relationships from text finds application in general natural language understanding, as well as real-world domains such as social networks, discussion forums, intelligent virtual agents, etc. We propose that the study of relationships should incorporate not only linguistic cues in text, but also the contexts in which these cues appear. Our investigations, backed by empirical evaluation, support this thesis, and demonstrate that the task benefits from using structured models that incorporate both types of information. We present such structured models to address the task of modeling the nature of relationships between any two given characters from a narrative. To begin with, we assume that relationships are of two types: cooperative and non-cooperative. We first describe an approach to jointly infer relationships between all characters in the narrative, and demonstrate how the task of characterizing the relationship between two characters can benefit from including information about their relationships with other characters in the narrative. We next formulate the relationship-modeling problem as a sequence prediction task to acknowledge the evolving nature of human relationships, and demonstrate the need to model the history of a relationship in predicting its evolution. Thereafter, we present a data-driven method to automatically discover various types of relationships such as familial, romantic, hostile, etc. Like before, we address the task of modeling evolving relationships but don't restrict ourselves to two types of relationships. We also demonstrate the need to incorporate not only local historical but also global context while solving this problem. Lastly, we demonstrate a practical application of modeling inter-personal relationships in the domain of online educational discussion forums. Such forums offer opportunities for its users to interact and form deeper relationships. With this view, we address the task of identifying initiation of such deeper relationships between a student and the instructor. Specifically, we analyze contents of the forums to automatically suggest threads to the instructors that require their intervention. By highlighting scenarios that need direct instructor-student interactions, we alleviate the need for the instructor to manually peruse all threads of the forum and also assist students who have limited avenues for communicating with instructors. We do this by incorporating the discourse structure of the thread through latent variables that abstractly represent contents of individual posts and model the flow of information in the thread. Such latent structured models that incorporate the linguistic cues without losing their context can be helpful in other related natural language understanding tasks as well. We demonstrate this by using the model for a very different task: identifying if a stated desire has been fulfilled by the end of a story.

Modeling the impact of social discrimination on the physical and mental health of portuguese gay, lesbian and bisexual people

Background: Despite growing acceptance of same-sex sexuality in Portugal, identity development of lesbian, gay and bisexual (LGB) individuals is still restricted by negative societal attitudes, which maintain the experience of stigmatization and discrimination. The purpose of this study is to document the frequency of discriminatory events experienced by sexual minorities and their association with indicators of physical and mental health in Portugal. Methods: A total of 610 LGB participants completed an online survey (mean age = 34.48, SD = 11.54). Most participants were single and self-identified as gay (73.8%). The survey included five categories of survey items: demographic information, social support, physical health, mental health, and discrimination experiences. Results: Physical and mental health results revealed that bisexual people were more likely to report higher levels of psychological distress than gay men. Overall, between one-fifth and one-fourth of the participants in this sample frequently felt the need to hide their sexual orientation to prevent discrimination experiences across the different settings. Regarding actual discrimination experiences, close to 20% reported having suffered from verbal abuse, followed by close to 10% who suffered from written threats, harassment, and physical threats. A hierarchical multiple regression analysis was performed to assess the effects of anticipated and actual discrimination on mental health. Possible confounding variables were added in the first block – age, sexual orientation, being in a relationship, body mass index, and HIV status. Anticipated and actual discrimination experiences were added in the second block. The first block of the analysis explained 6% of the overall variance, while the second block – discrimination experiences – explained an additional 17%. Conclusion: Portuguese culture and stigma/discrimination create discriminatory experiences which impact LGB people’s health. Unless policies are changed to allow for the acceptance of LGB people, they will continue to experience violence and discrimination as a result of homophobia.

Healthcare Network Modeling and Analysis

Part 20: Health and Care Networks

Photovoltaic power forecast modeling with artificial neural networks

Dissertação de Mestrado, Engenharia Eletrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

3D Block Modeling and Reserve Estimation of a Garnet Deposit

The purpose of this project is to develop a three-dimensional block model for a garnet deposit in the Alder Gulch, Madison County, Montana. Garnets occur in pre-Cambrian metamorphic Red Wash gneiss and similar rocks in the vicinity. This project seeks to model the percentage of garnet in a deposit called the Section 25 deposit using the Surpac software. Data available for this work are drillhole, trench and grab sample data obtained from previous exploration of the deposit. The creation of the block model involves validating the data, creating composites of assayed garnet percentages and conducting basic statistics on composites using Surpac statistical tools. Variogram analysis will be conducted on composites to quantify the continuity of the garnet mineralization. A three-dimensional block model will be created and filled with estimates of garnet percentage using different methods of reserve estimation and the results compared.

SYSTEM DYNAMICS MODELING AS A QUANTITATIVE-QUALITATIVE FRAMEWORK FOR SUSTAINABLE WATER RESOURCES MANAGEMENT: INSIGHTS FOR WATER QUALITY POLICY IN THE GREAT LAKES REGION

Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

VALIDATION OF A 'DISPLACEMENT TOMOGRAPHY' INVERSION METHOD FOR MODELING SHEET INTRUSIONS

The study of volcano deformation data can provide information on magma processes and help assess the potential for future eruptions. In employing inverse deformation modeling on these data, we attempt to characterize the geometry, location and volume/pressure change of a deformation source. Techniques currently used to model sheet intrusions (e.g., dikes and sills) often require significant a priori assumptions about source geometry and can require testing a large number of parameters. Moreover, surface deformations are a non-linear function of the source geometry and location. This requires the use of Monte Carlo inversion techniques which leads to long computation times. Recently, ‘displacement tomography’ models have been used to characterize magma reservoirs by inverting source deformation data for volume changes using a grid of point sources in the subsurface. The computations involved in these models are less intensive as no assumptions are made on the source geometry and location, and the relationship between the point sources and the surface deformation is linear. In this project, seeking a less computationally intensive technique for fracture sources, we tested if this displacement tomography method for reservoirs could be used for sheet intrusions. We began by simulating the opening of three synthetic dikes of known geometry and location using an established deformation model for fracture sources. We then sought to reproduce the displacements and volume changes undergone by the fractures using the sources employed in the tomography methodology. Results of this validation indicate the volumetric point sources are not appropriate for locating fracture sources, however they may provide useful qualitative information on volume changes occurring in the surrounding rock, and therefore indirectly indicate the source location.

Investigation of Escape and Negative Student Behaviors Related to Florida State High Stakes Test Preparation in Miami-Dade County Public High Schools, having been approved in respect to style and intellectual content, is referred to you for judgment

The purpose of this study was to determine whether there was a relationship between pressure to perform on state mandated, high-stakes tests and the rate of student escape behavior defined as the number of school suspensions and absences. The state assigned grade of a school was used as a surrogate measure of pressure with the assumption that pressure increased as the school grade decreased. Student attendance and suspension data were gathered from all 33 of the regular public high schools in Miami-Dade County Public Schools. The research questions were: Is the number of suspensions highest in the third quarter, when most FCAT preparation takes place for each of the 3 school years 2007-08 through 2009-10? How accurately does the high school’s grade predict the number of suspensions and number of absences during each of the 4 school years 2005-06 through 2008-09? The research questions were answered using repeated measures analysis of variance for research question #1 and non-linear multiple regression for research question #2. No significant difference could be found between the numbers of suspensions in each of the grading periods nor was there a relationship between the number of suspensions and school grade. A statistically significant relationship was found between student attendance and school grade. When plotted, this relationship was found to be quadratic in nature and formed a loose inverted U for each of the four years during which data were collected. This indicated that students in very high and very low performing schools had low levels of absences while those in the midlevel of the distribution of school performance (C schools) had the greatest rates of absence. Identifying a relationship between the pressures associated with high stakes testing and student escape behavior suggests that it might be useful for building administrators to reevaluate test preparation activities and procedures being used in their building and to include anxiety reducing strategies. As a relationship was found, it sets the foundation for future studies to identify whether testing related activities are impacting some students emotionally and are causing unintended consequences of testing mandates.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

Methods for Modeling and Analyzing Concurrent Software

Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.

A NOVEL MODELING AND STATE OF CHARGE ESTIMATION SCHEME FOR LITHIUM-ION BATTERIES

Lithium Ion (Li-Ion) batteries have got attention in recent decades because of their undisputable advantages over other types of batteries. They are used in so many our devices which we need in our daily life such as cell phones, lap top computers, cameras, and so many electronic devices. They also are being used in smart grids technology, stand-alone wind and solar systems, Hybrid Electric Vehicles (HEV), and Plug in Hybrid Electric Vehicles (PHEV). Despite the rapid increase in the use of Lit-ion batteries, the existence of limited battery models also inadequate and very complex models developed by chemists is the lack of useful models a significant matter. A battery management system (BMS) aims to optimize the use of the battery, making the whole system more reliable, durable and cost effective. Perhaps the most important function of the BMS is to provide an estimate of the State of Charge (SOC). SOC is the ratio of available ampere-hour (Ah) in the battery to the total Ah of a fully charged battery. The Open Circuit Voltage (OCV) of a fully relaxed battery has an approximate one-to-one relationship with the SOC. Therefore, if this voltage is known, the SOC can be found. However, the relaxed OCV can only be measured when the battery is relaxed and the internal battery chemistry has reached equilibrium. This thesis focuses on Li-ion battery cell modelling and SOC estimation. In particular, the thesis, introduces a simple but comprehensive model for the battery and a novel on-line, accurate and fast SOC estimation algorithm for the primary purpose of use in electric and hybrid-electric vehicles, and microgrid systems. The thesis aims to (i) form a baseline characterization for dynamic modeling; (ii) provide a tool for use in state-of-charge estimation. The proposed modelling and SOC estimation schemes are validated through comprehensive simulation and experimental results.

Managing pressure: patterns of appraisals and coping strategies of non-elite and elite athletes during competition

The purpose of this study was to compare moment-to-moment appraisals and coping strategies of 4 non-elite and 2 elite male trap shooters during competitions and in particular during periods of competition perceived as critical to performance. Appraisals and coping patterns of trap shooters were captured via verbal reports of thinking provided between sets of shots during major competitions. Verbal reports were coded according to an appraisal and coping typology. Coded data as well as shooting performance data were subjected to a sequential analysis of probabilities of pairs of events. Fewer reports of negative appraisals (NEGAs) and more frequent reports of problem-focused coping (PFC) were observed among both elite athletes compared to non-elite athletes. After making a NEGA, non-elite shooters often progressed to the next target without attempting to cope, whereas elite shooters used both PFC and emotion-focused coping (EFC) before proceeding to the next target. After missing a target, the non-elite athletes used more EFC than expected. These results indicate that elite athletes are more likely to cope with NEGAs than non-elite athletes using a wider variety of coping strategies. Athletes might benefit from increased awareness of the potentially detrimental impact of NEGAs on performance and by integrating coping strategies within preparatory routines.

Une comparaison des journaux non structurés et des journaux structurés rédigés par les étudiants en hygiène dentaire

The Canadian Dental Hygienists Association (CDHA) has indicated that there is a need for research in education in the field of dental hygiene. It seems that when compared to the nursing profession, the profession of dental hygiene is only in the earliest stages of investigating ways of teaching critical thinking. The faculty of the dental hygiene program at John Abbott College has always valued the skill of self-assessment in the students, yet there are few specific learning activities provided whereby the students can learn how to perfect and work on this invaluable skill of self-reflection in order to better self-assess. Although self-assessment is required of the students upon the completion of each clinical experience in Clinic 1, 2 and 3, a modest amount of clinical time is allotted to reflect upon this most important skill. It appears that more could be done to prepare our students to assess their learning and clinical practice. Self-reflection as an essential element of practice has a valid place in professional education. The purpose of conducting this study was to find out whether unstructured or structured self-reflective journal writing is a sound pedagogical technique to encourage dental hygiene students’ self-assessment through self-reflection. The research design for the project was a single case study. The paradigm for the study was chosen with a purposeful selection of participants, involving twenty-seven, third-year dental hygiene students at John Abbott College. The students were arbitrarily enrolled in two sections, which for the purpose of this study were referred to as Group A and Group B. Three duplicated coded anonymous journal entries from each student were collected over a ten-week period during the Fall 2009 semester. To examine the students’ level of self-reflection, two methods were used. First a content analysis of reflective journals was used to ascertain the level and substance of the reflections from their clinical experiences with the intent of looking more specifically at the students’ self-assessment. The journal entries were coded and analyzed after the grades were submitted at the end of the school term. This was followed by the distribution of an anonymous questionnaire to the students in both sections. The responses of the questionnaire were tabulated and analyzed. An analysis was done on the data collected in order to determine whether age, education and or mother tongue of the students in both Groups A and B had an influence on their perceptions of journal writing, as well as the student’s opinions about the value of journal writing. This questionnaire included two open-ended questions to assist in gathering additional data on the student’s thoughts on writing journals. A content analysis of the qualitative data collected from the open-ended questions in the questionnaire was also analyzed. Results indicated there were very few differences in the level of self-reflection leading to self-assessment. However, students in Group B who were assigned structured journals showed more evidence of deeper learning. Taken as a whole, the journal entries clearly showed the students were involved in ‘reflection-on-action’ of their clinical experiences (Schon 1987, as cited in Asadoorian & Batty, 2005). The quality of the responses for the most part indicated the students took the time and effort to record their perceptions of their clinical experiences. It is important to note that the results do indicate that students did show a need to self-reflect and assess. The students did in fact validate the importance of reflection through journal writing, even though they did not particularly like it as an added assignment. The journals were found to be very helpful to the research in getting to know what the issues were that held the students’ attention. They explained how and to what extent the students developed relationships with their clients. It was obvious that clinicians have an impact and influence on student learning. The students value the help, role modeling, patience, encouraging words and or gestures, positive reinforcement, and understanding provided by their clinicians. This research provides some evidence that students do believe that self-reflection through structured journal writing helped them better prepare for future clinical sessions with their clients. Our goal as educators should be to encourage dental hygiene students to self-assess through written self-reflection as an established practice for deeper learning.

A complexity-based diagnostic on the democratic unity roundtable mud: problems and alternatives (2008-2016)

Este trabajo exploratorio estudia al movimiento político Mesa de la Unidad Democrática (MUD), creada con el fin de oponerse la Gobierno socialista existente en venezuela. La crítica que este documento realiza, parte desde el punto de vista de la Ciencia de la Complejidad. Algunos conceptos clave de sistemas complejos han sido utilizados para explicar el funcionamiento y organización de la MUD, esto con el objetivo de generar un diagnóstico integral de los problemas que enfrenta, y evidenciar las nuevas percepciones sobre comportamientos perjudiciales que el partido tiene actualmente. Con el enfoque de la complejidad se pretende ayudar a comprender mejor el contexto que enmarca al partido y, para, finalmente aportar una serie de soluciones a los problemas de cohesión que presen

Contexts and Factors Associated with Bullying

Introduction: School violence discloses a phenomenon that has acquired a marked visibility in today's society, becoming a reality in all schools. With these aggressive behaviors comes a new conception, which increasingly reveals a concern for the community, the bullying (Eiras, 2009). Objectives: Tidentify bullying as a health need in schools; identify the factors associated with bullying. Methods: Integrative Literature Review, and were analyzed 7 articles published in MEDLINE, Scientific Electronic Library Online (SciELO), the Online Knowledge Library (B -on) and the Repositório Científico de Acesso Aberto de Portugal (RCAAP), whereas inclusion criteria were established the Portuguese, English and Spanish and the interval 2011-2016. Results: After analyzing the articles selected for the preparation of this monograph, we identified the following contexts and factors associated with bullying. Conclusions: age with higher prevalence, where this phenomenon was found is between 12 and 13 years; gender, where there is no consensus on the influence of the same in bullying behaviors; family and socio-demographic context in which a family environment marked by cohesion and support promotes attitudes of non-violence and socioeconomic status are not directly related to find this type of episode; bullying characteristics, wherein said type of behavior is more verbal bullying; substance use and knowledge.