Seeking To Understand, Aspiring to Teach: Exploring How Life Shapes Emotional and Personal Development in Global Health Leaders

Thesis (Master's)--University of Washington, 2016-08

Using the interaural time difference and cross-correlation to localise short-term complex noises

The mammalian binaural cue of interaural time difference (ITD) and cross-correlation have long been used to determine the point of origin of a sound source. The ITD can be defined as the different points in time at which a sound from a single location arrives at each individual ear [1]. From this time difference, the brain can calculate the angle of the sound source in relation to the head [2]. Cross-correlation compares the similarity of each channel of a binaural waveform producing the time lag or offset required for both channels to be in phase with one another. This offset corresponds to the maximum value produced by the cross-correlation function and can be used to determine the ITD and thus the azimuthal angle θ of the original sound source. However, in indoor environments, cross-correlation has been known to have problems with both sound reflections and reverberations. Additionally, cross-correlation has difficulties with localising short-term complex noises when they occur during a longer duration waveform, i.e. in the presence of background noise. The crosscorrelation algorithm processes the entire waveform and the short-term complex noise can be ignored. This paper presents a technique using thresholding which enables higher-localisation abilities for short-term complex sounds in the midst of background noise. To determine the success of this thresholding technique, twenty-five sounds were recorded in a dynamic and echoic environment. The twenty-five sounds consist of hand-claps, finger-clicks and speech. The proposed technique was compared to the regular cross-correlation function for the same waveforms, and an average of the azimuthal angles determined for each individual sample. The sound localisation ability for all twenty-five sound samples is as follows: average of the sampled angles using cross-correlation: 44%; cross-correlation technique with thresholding: 84%. From these results, it is clear that this proposed technique is very successful for the localisation of short-term complex sounds in the midst of background noise and in a dynamic and echoic indoor environment.

Older Adult Injury Risk Assessment in the Driving and Occupational Environments

Thesis (Ph.D.)--University of Washington, 2016-08

IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

Scheduling of track inspection and maintenance activities in railroad networks

The U.S. railroad companies spend billions of dollars every year on railroad track maintenance in order to ensure safety and operational efficiency of their railroad networks. Besides maintenance costs, other costs such as train accident costs, train and shipment delay costs and rolling stock maintenance costs are also closely related to track maintenance activities. Optimizing the track maintenance process on the extensive railroad networks is a very complex problem with major cost implications. Currently, the decision making process for track maintenance planning is largely manual and primarily relies on the knowledge and judgment of experts. There is considerable potential to improve the process by using operations research techniques to develop solutions to the optimization problems on track maintenance. In this dissertation study, we propose a range of mathematical models and solution algorithms for three network-level scheduling problems on track maintenance: track inspection scheduling problem (TISP), production team scheduling problem (PTSP) and job-to-project clustering problem (JTPCP). TISP involves a set of inspection teams which travel over the railroad network to identify track defects. It is a large-scale routing and scheduling problem where thousands of tasks are to be scheduled subject to many difficult side constraints such as periodicity constraints and discrete working time constraints. A vehicle routing problem formulation was proposed for TISP, and a customized heuristic algorithm was developed to solve the model. The algorithm iteratively applies a constructive heuristic and a local search algorithm in an incremental scheduling horizon framework. The proposed model and algorithm have been adopted by a Class I railroad in its decision making process. Real-world case studies show the proposed approach outperforms the manual approach in short-term scheduling and can be used to conduct long-term what-if analyses to yield managerial insights. PTSP schedules capital track maintenance projects, which are the largest track maintenance activities and account for the majority of railroad capital spending. A time-space network model was proposed to formulate PTSP. More than ten types of side constraints were considered in the model, including very complex constraints such as mutual exclusion constraints and consecution constraints. A multiple neighborhood search algorithm, including a decomposition and restriction search and a block-interchange search, was developed to solve the model. Various performance enhancement techniques, such as data reduction, augmented cost function and subproblem prioritization, were developed to improve the algorithm. The proposed approach has been adopted by a Class I railroad for two years. Our numerical results show the model solutions are able to satisfy all hard constraints and most soft constraints. Compared with the existing manual procedure, the proposed approach is able to bring significant cost savings and operational efficiency improvement. JTPCP is an intermediate problem between TISP and PTSP. It focuses on clustering thousands of capital track maintenance jobs (based on the defects identified in track inspection) into projects so that the projects can be scheduled in PTSP. A vehicle routing problem based model and a multiple-step heuristic algorithm were developed to solve this problem. Various side constraints such as mutual exclusion constraints and rounding constraints were considered. The proposed approach has been applied in practice and has shown good performance in both solution quality and efficiency.

EXPLORING THE EFFECTS OF THE RELATIONSHIP BETWEEN SCHOOL CHARACTERISTICS, TEACHER CHARACTERISTICS, ADMINISTRATIVE SUPPORT, AND SCHOOL CLIMATE ON VOLUNTARY INTRA-DISTRICT TEACHER MIGRATION

This quantitative research study utilized a binary logistic regression in a block design to investigate exogenous and endogenous factors influencing a teacher’s decision to make an intra-district move. The research focused on the following exogenous factors: classroom characteristics (size of class, percent minority, percent of students with an individualized education plan, and percent of students that are English language learners) and teacher characteristics (experience and gender). The following endogenous factors were examined: direct administrative influence (administrative support, rules enforced, school vision, teacher recognition, and job security) and indirect administrative influence (school climate, student misbehavior, parental support, materials, staff collaboration). The research was conducted by using information available from the National Center for Educational Statistics, the SASS from 2011-2012 and TFS from 2012-2013. The 2012-2013 Teacher Follow-up Survey identified 60 teachers who made a voluntary intra-district move. Results illustrate there is a statistically significant relationship between percentage of English Language Learners and overall job satisfaction and teachers choosing to make an intra-district move.

Development and pharmacological evaluation of ropivacaine-2-hydroxypropyl-beta-cyclodextrin inclusion complex

Ropivacaine (RVC) is an enantiomerically pure local anesthetic (LA) largely used in surgical procedures, which presents physico-chemical and therapeutic properties similar to those of bupivacaine (BPV), but associated to less systemic toxicity This study focuses on the development and pharmacological evaluation of a RVC in 2-hydroxypropyl-beta-cyclodextrin (HP-P-CD) inclusion complex. Phase-solubility diagrams allowed the determination of the association constant between RVC and HP-beta-CD (9.46 M-1) and showed an increase on RVC solubility upon complexation. Release kinetics revealed a decrease on RVC release rate and reduced hemolytic effects after complexation. (onset at 3.7 mM and 11.2 mM for RVC and RVCHP-beta-CD, respectively) were observed. Differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and X-ray analysis (X-ray) showed the formation and the morphology of the complex. Nuclear magnetic resonance (NMR) and job-plot experiments afforded data regarding inclusion complex stoichiometry (1:1) and topology. Sciatic nerve blockade studies showed that RVCHP-beta-CD was able to reduce the latency without increasing the duration of motor blockade, but prolonging the duration and intensity of the sensory blockade (p < 0.001) induced by the LA in mice. These results identify the RVCHP-beta-CD complex as an effective novel approach to enhance the pharmacological effects of RVC, presenting it as a promising new anesthetic formulation. (c) 2007 Elsevier B.V All rights reserved.

Inteligência emocional nas organizações: Colaboradores motivados e com desempenho emocionalmente inteligente?

Dissertação de Mestrado apresentada ao Instituto Superior de Psicologia Aplicada para obtenção de grau de Mestre na especialidade de Psicologia Social e das Organizações.

Long-term Success of Family Firms: Investigating Specific Aspects of Firm-level Entrepreneurship and Individual-level Antecedents

Long-term success of family firms is of utmost social and economic importance. Three of its determinants are in the center of this Dissertation: firmlevel entrepreneurial orientation (EO), managers' entrepreneurial behavior, and value-creating attitudes of non-family employees. Each determinant and respective research gaps are addressed by one paper of this cumulative dissertation. Referring to firm-level EO, scholars claim that EO is a main antecedent to firms' both short- and long-term success. However, family firms seem to be successful across generations despite rather low levels of EO. The first paper addresses this paradox by investigating EO patterns of long-lived family firms in three Swiss case studies. The main finding is that the key to success is not to be as entrepreneurially as possible all the time, but to continuously adapt the EO profile depending on internal and external factors. Moreover, the paper suggest new subcategories to different EO dimensions. With regard to entrepreneurial behavior of managers, there is a lack of knowledge how individual-level and organizational level factors affect its evolvement. The second paper addresses this gap by investigating a sample of 403 middle-level managers from both family and non-family firms. It introduces psychological ownership of managers as individual-level antecedent and investigates the interaction with organizational factors. As a central insight, management support is found to strengthen the psychological ownership-entrepreneurial behavior relationship. The third paper is based on the fact that employees' justice perceptions are established antecedents of value-creating employee attitudes such as affective commitment and job satisfaction. Even though family firms are susceptible to nonfamily employees´ perceptions of injustice, corresponding research is scarce. Moreover, the mechanism connecting justice perceptions and positive outcomes is still unclear. Addressing these gaps, the analysis of a sample of 310 non-family employees reveals that psychological ownership is a mediator in the relationships between distributive justice perceptions and both affective commitment and job satisfaction. Altogether, the three papers offer valuable contributions to family business literature with respect to EO, entrepreneurial behavior, and value-creating employee attitudes. Thus, they increase current understanding about important determinants of family firms' long-term success, while opening up numerous ways of future research.

Work, Professional Development And Teaching Commitment: Deconstructing Meanings

The paper we present is part of the research project "The professional identity of teacher studies", that we are development for last 3 years. The third phase of this research put the focus on the experience of job placement of novel teachers, graduated no more than 5 years. We work with focal groups and professional experience and teacher education accounts of teachers implied in this research. Also, for any teachers, we do biographical interviews to deepen on processes of construction of professional identity. In this paper we present the Ana Belen History, a female teacher of pre-school education with an experience of 4 years in school, working in a urban school with students in risk of exclusion. This school have a educative project, commitment with the neighbourhood, joint with the community and other social groups. Ana Belen story, from professional perspective, is linked with the social politic and educational commitment of this school. Our interest is focused in the comprehension of professional identity that Ana Belen has gone forging along her personal story and how her education and job placement has contributed for it. Also we are interested in knowing how early professional experiences have influenced in her professional development as teacher. Specifically we ask ourselves about what influence have for her professional identity, that her career starts in this particular school. In consequence, this paper leads us to question the current teacher education model. In particular we are interested on the kind of professional experience that have place and, so, the kinds of commitments that enables. We understand that frameworks in which professional education and experience have place are relevant to enable more or less transformer understandings about teaching. From conceptual perspective this paper adopts a socio-critical point of view (Gergen, 1985; Kincheloe, 2001; Wenger, 1988, etc.). We understand that teaching has to be analysing according work contexts and personal stories of teachers, because we face processes historical and collective building. Teaching is the result of action of their actors, over time, and in specific stage. So, with this research we intend to break with the old gap between pre and in-service education. We think that both of them are part of the same process and are formed according similar logical; although scenes change. We understand that they are part of a continuous process in which is giving sense to different and complex settings where teaching profession is built, but they are not differenced and independent stages. The teacher work, so, is subject to particular conditions, generated from such different fields as institutional, corporative, cultural, social, political, moral, etc. It displays a kaleidoscopic view on space, time, context, ... These are the axis in which the teaching is formed, from the complexity and heterogeneity. How this complexity is articulated results in different ways to face the teacher work, according different personal and professional stories. The teacher acts with subjects in instituted contexts from relationships he has with them, which gives a situated and contingent character. But, these contexts are strongly structured and ruled according centralized and generalized positions; which is, at the very least, paradoxical. Possibly, from our point of view, same of the crisis of teaching have to explain from this paradoxical perspective and the conflict, which characterize this job (Rivas, Leite y Cortés, 2011)

Développement d’un système d’appariement pour l’e-recrutement

Ce mémoire tente de répondre à une problématique très importante dans le domaine de recrutement : l’appariement entre offre d’emploi et candidats. Dans notre cas nous disposons de milliers d’offres d’emploi et de millions de profils ramassés sur les sites dédiés et fournis par un industriel spécialisé dans le recrutement. Les offres d’emploi et les profils de candidats sur les réseaux sociaux professionnels sont généralement destinés à des lecteurs humains qui sont les recruteurs et les chercheurs d’emploi. Chercher à effectuer une sélection automatique de profils pour une offre d’emploi se heurte donc à certaines difficultés que nous avons cherché à résoudre dans le présent mémoire. Nous avons utilisé des techniques de traitement automatique de la langue naturelle pour extraire automatiquement les informations pertinentes dans une offre d’emploi afin de construite une requête qui nous permettrait d’interroger notre base de données de profils. Pour valider notre modèle d’extraction de métier, de compétences et de d’expérience, nous avons évalué ces trois différentes tâches séparément en nous basant sur une référence cent offres d’emploi canadiennes que nous avons manuellement annotée. Et pour valider notre outil d’appariement nous avons fait évaluer le résultat de l’appariement de dix offres d’emploi canadiennes par un expert en recrutement.

Work creativity as a dimension of job performance

To stay competitive, many employers are looking for creative and innovative employees to add value to their organization. However, current models of job performance overlook creative performance as an important criterion to measure in the workplace. The purpose of this dissertation is to conduct two separate but related studies on creative performance that aim to provide support that creative performance should be included in models of job performance, and ultimately included in performance evaluations in organizations. Study 1 is a meta-analysis on the relationship between creative performance and task performance, and the relationship between creative performance and organizational citizenship behavior (OCB). Overall, I found support for a medium to large corrected correlation for both the creative performance-task performance (ρ = .51) and creative performance-OCB (ρ = .49) relationships. Further, I also found that both rating-source and study location were significant moderators. Study 2 is a process model that includes creative performance alongside task performance and OCB as the outcome variables. I test a model in which both individual differences (specifically: conscientiousness, extraversion, proactive personality, and self-efficacy) and job characteristics (autonomy, feedback, and supervisor support) predict creative performance, task performance, and OCB through engagement as a mediator. In a sample of 299 employed individuals, I found that all the individual differences and job characteristics were positively correlated with all three performance criteria. I also looked at these relationships in a multiple regression framework and most of the individual differences and job characteristics still predicted the performance criteria. In the mediation analyses, I found support for engagement as a significant mediator of the individual differences-performance and job characteristics-performance relationships. Taken together, Study 1 and Study 2 support the notion that creative performance should be included in models of job performance. Implications for both researchers and practitioners alike are discussed.^

Workplace aggression: A reconceptualization of the construct & an exploration of strain based outcomes

The examination of Workplace Aggression as a global construct conceptualization has gained considerable attention over the past few years as organizations work to better understand and address the occurrence and consequences of this challenging construct. The purpose of this dissertation is to build on previous efforts to validate the appropriateness and usefulness of a global conceptualization of the workplace aggression construct. ^ This dissertation has been broken up into two parts: Part 1 utilized a Confirmatory Factor Analysis approach in order to assess the existence of workplace aggression as a global construct; Part 2 utilized a series of correlational analyses to examine the relationship between a selection of commonly experienced individual strain based outcomes and the global construct conceptualization assessed in Part 1. Participants were a diverse sample of 219 working individuals from Amazon’s Mechanical Turk participant pool. ^ Results of Part 1 did not show support for a one-factor global construct conceptualization of the workplace aggression construct. However, support was shown for a higher-order five-factor model of the construct, suggesting that it may be possible to conceptualize workplace aggression as an overarching construct that is made up of separate workplace aggression constructs. Results of Part 2 showed support for the relationships between an existing global construct workplace aggression conceptualization and a series of strain-based outcomes. Utilizing correlational analyses, additional post-hoc analyses showed that individual factors such as emotional intelligence and personality are related to the experience of workplace aggression. Further, utilizing moderated regression analysis, the results demonstrated that individuals experiencing high levels of workplace aggression reported higher job satisfaction when they felt strongly that the aggressive act was highly visible, and similarly, when they felt that there was a clear intent to cause harm. ^ Overall, the findings of this dissertation do support the need for a simplification of its current state of measurement. Future research should continue to examine workplace aggression in an effort to shed additional light on the structure and usefulness of this complex construct.^

Exploring Calling Work Orientation: Construct Clarity and Organizational Implications

Employees maintain a personal view toward their work, which can be referred to as their work orientation. Some employees view their work as their life’s purpose (i.e., calling work orientation) and they tend to be 1) prosocially motivated, 2) derive meaning from work, and 3) feel that their purpose is from beyond the self. The purpose of the current dissertation was to differentiate calling work orientation from other similar workplace constructs, to investigate the most common covariates of calling work orientation, and to empirically test two possible moderators of the relationship between calling work orientation and work-related outcomes of job satisfaction, job performance, and work engagement. Two independent samples were collected for the purpose of testing hypotheses: data were collected from 520 working students and from 520 non-student employees. Participants from the student sample were recruited at Florida International University, and participants from the employee sample were recruited via the Amazon Mechanical Turk website. Participants from the student sample answered demographic questions and responded to self-report measures of job satisfaction, job performance, work engagement, spirituality, meaningful work, prosocial motivation, and work orientation. The procedure was similar for the employee sample, but their survey also included measures of counterproductive work behaviors, organizational citizenship behaviors, conscientiousness, and numerical ability. Additionally, employees were asked whether they would be willing to have a direct supervisor, peer, co-worker, client, or subordinate rate their job performance. Hierarchical regression findings suggest calling work orientation was predictive of overall job performance above and beyond two common predictors of performance, conscientiousness and numerical ability. The results for the covariate analyses provided evidence that prosocial motivation, meaningful work, and spirituality do play a significant role in the development of an employees’ work orientation. Perceived career opportunities moderated the relationship between calling work orientation and job performance for the employee sample. Core self-evaluations moderated the relationship between calling work orientation and job performance, and core self-evaluations moderated the relationship between calling work orientation and work engagement. Collectively, findings from the current study highlight the benefits of examining work orientation in the prediction of workplace outcomes.

Collaborative filtering and deep learning based hybrid recommendation for cold start problem

Recommender systems (RS) are used by many social networking applications and online e-commercial services. Collaborative filtering (CF) is one of the most popular approaches used for RS. However traditional CF approach suffers from sparsity and cold start problems. In this paper, we propose a hybrid recommendation model to address the cold start problem, which explores the item content features learned from a deep learning neural network and applies them to the timeSVD++ CF model. Extensive experiments are run on a large Netflix rating dataset for movies. Experiment results show that the proposed hybrid recommendation model provides a good prediction for cold start items, and performs better than four existing recommendation models for rating of non-cold start items.