Syftet var att undersöka högkänslighet och stress hos studenter. Metoden var en kvantitativ jämförande studie mellan grupper (kvinnor och män). Undersökningen genomfördes genom en elektronisk enkät. Urvalet var ett tillfällighetsurval av kvinnor och män i åldrarna 19 – 56 som studerade vid ett universitet, totalt 122 stycken deltagare, 31 män och 91 kvinnor. Deltagarna besvarade en enkät som bestod av bakgrundsfrågor och mätinstrument som mätte stress och högkänslighet. Resultatet visade på att högkänslighet och stress var skattad högst bland kvinnorna. Slutsatsen är att kvinnor och män skiljer sig i högkänslighet och stress samt att stress och högkänslighet korrelerar med varandra. / The aim was to investigate high sensitivity and stress among students. The method was a quantitative comparative study between groups (women and men). The survey was conducted through an electronic questionnaire. The selection was an opportunity sample of women and men who studied at a university and was between the ages of 19-56, a total of 122 participants 31 men and 91 women. The participants answered a questionnaire that consisted of background questions and instruments to measure stress and high sensitivity. The results showed that high sensitivity and stress was underestimated highest among women. The conclusion is that women and men differ in high sensitivity and stress, and that stress and high sensitivity correlate.

The sustainability of grouper culture as an alternative livelihood option for coastal fishers was investigated in the southern provinces of Thailand. A sequenced approach using qualitative and quantitative research methods was used to explore factors that could undermine the potential for grouper culture to contribute to a sustainable livelihood. A study was initially conducted in 28 villages in 6 provinces in southern Thailand to provide baseline information on grouper aquaculture and fisheries, focusing on culture practice, the actors and institutions involved in grouper culture and beneficiaries. Factors contributing to the variation in levels of uptake of grouper culture between provinces was explored. This initial overview facilitated the description of the grouper culture system in terms of its boundaries, hierarchies, interconnections and processes and the development of a framework for the assessment of the sustainability of the grouper culture system. A case study approach was used to investigate in-depth the role and sustainability of grouper culture at the community and household level. Three communities were selected for study in Trang and Satun provinces. Research was guided by the sustainability assessment framework, which comprised five components: Livelihoods, Institutions, Environment, Markets and Production Systems. Data was collected using qualitative, participatory methods and a quantitative survey. The research found that grouper culture has the potential to contribute to a sustainable livelihood for coastal fishers in southern Thailand, although problems with fish disease and mortality, fluctuations in the availability of seed fish and water quality undermine the ability of most farmers to obtain the maximum benefit from grouper culture. Non-technical factors including motivation and incentive, access to financial capital and levels of social capital were also observed to influence sustainability of grouper culture. Grouper culture was found to be an activity in which members of all wealth groups could participate with institutional support, access to credit, and access to wild sources of seed and feed. It is unlikely to provide a suitable alternative to fishing, as the two activities contribute in different ways to the livelihoods of coastal households, but may support livelihood diversification.

The present study tested the hypothesis that contiguity, regarding time of administration of the Tellegen Absorption Scale (TAS), differentially influences hypnotic susceptibility. Forty-eight subjects were administered the TAS immediately prior to assessment of hypnotic susceptibility versus 43 subjects who received the TAS one to three days before assessment of hypnotic susceptibility. Absorption, when measured in the temporally versus nontemporally contiguous context did not appear to affect hypnotic susceptibility. Absorption did, however, correlate significantly with hypnotic susceptibility in the temporally contiguous group as compared to a non-significant correlation in the nontemporally contiguous group. This finding suggests is a relationship between differential administration of the TAS with regard to time of administration and hypnotic susceptibility.

This investigation represents an attempt to employ the Devries Suicide Prediction Scale and the Rorschach Inkblot Test in a two-stage predictive model which was designed to decrease the high false positive rate associated with the Devries and to design a way in which the Rorschach could be used efficiently in suicide prediction in a large mental hospital setting. The Rorschach was not found to significantly improve the predictive ability of the Devries. An unexpectedly high percentage of mental patients in the study, thirty-eight percent, admitted to previous suicide attempts, raising the question of whether suicidal behavior is not more common than is usually thought.

This study hypothesized that paranoid schizophrenia and schizo-affective, depressed type schizophrenia could be differentiated by the Internalizer-Externalizer, Regulated- Flexible, and Role Uniform-Role Adaptable dimensions of the Personality Assessment System. The Personality Assessment System methodology utilizes the Wechsler Adult Intelligence Scale to measure these dimensions. All hypotheses were statistically confirmed. The difficulty of applying the Personality Assessment System to psychopathological regressive states is cited. Recommendations include utilizing the Personality Assessment System with other groups in the institutional setting and within diagnostic categories.

The problem of this study was to factor-analyze Rokeach's Dogmatism Scale and examine the factor structures of the scale for differences in the solutions obtained for the male and female groups. It was hypothesized that the Dogmatism Scale consists of several discriminable dimensions of the construct dogmatism and that these dimensions differ significantly for males and females. The dogmatism scale was administered to 186 male and 115 female college students. The male and female solutions yielded thirteen and sixteen orthogonal factors, respectively. Six male factors and eleven female factors were unique to their respective sex groups, indicating that the Dogmatism Scale is multidimensional and that significant sex differences are found when these dimensions are examined.

The purpose of this study was to develop and test the Experience of Supervision Scale, which measures the experience of supervisory behaviors from the perspective of child welfare workers. Child welfare supervision is gaining increased attention as states struggle to improve performance measures of their child welfare systems. However, the lack of a standardized instrument which measures supervision through an analysis of supervisory behaviors from the supervisee’s perspective has hindered efforts in these areas. The Experience of Supervision Scale is based on Kadushin’s three function casework supervision model of supervision (administrative, educational, and supportive) which was chosen as the theoretical framework due to this model’s emphasis on public agency clinical case work practice. Scale items were generated through focus groups of child welfare workers and supervisors. Items were reviewed by an expert panel and the scale was then administered to a statewide sample of 165 child welfare workers. The refined Experience of Supervision Scale consists of 32 items. In this study, it demonstrated high internal consistency with a Cronbach’s alpha of .962. Factor analysis yielded a three factor solution consistent with the casework model of supervision’s structure, while also suggesting slight modifications to the model. The three factors derived included: Performance Support, Emotional support/Availability, and Administrative activities. The results of this study suggest that the Experience of Supervision Scale has appropriate psychometric properties for use in complex research in which casework supervision is a variable.

Manufacturing organisations have placed significant attention to the potential of industrial human-robot collaboration (HRC) as a means for enhancing productivity and product quality. This concept has predominantly been seen from an engineering and safety aspect, while the human related issues tend to be disregarded. As the key human factors relevant to industrial HRC have not yet been fully investigated, the research presented in this thesis sought to develop a human factors tool to enable the successful implementation of industrial HRC. First, a theoretical framework was developed which collected the key organisational and individual level human factors by reviewing comparable contexts to HRC. The human factors at each level were investigated separately. To identify whether the organisational human factors outlined in the theoretical framework were enablers or barriers, an industrial exploratory case study was conducted where traditional manual work was being automated. The implications provided an initial roadmap of the key organisational human factors that need to be considered as well as the critical inter-relations between them. From the list of individual level human factors identified in the theoretical framework, the focus was given on exploring the development of trust between human workers and industrial robots. A psychometric scale that measures trust specifically in industrial HRC was developed. The scale offers the opportunity to system designers to identify the key system aspects that can be manipulated to optimise trust in industrial HRC. Finally, the results were gathered together to address the overall aim of the research. A human factors guidance tool was developed which provides practitioners propositions to enable successful implementation of industrial HRC.

L'analyse de sensibilité globale basée sur la variance permet de hiérarchiser les sources d'incertitude présentes dans un modèle numérique et d'identifier celles qui contribuent le plus à la variabilité de la sortie du modèle. Ce type d'analyse peine à se développer dans les sciences de la Terre et de l'Environnement, en partie à cause de la dimension spatiale de nombreux modèles numériques, dont les variables d'entrée et/ou de sortie peuvent être des données distribuées dans l'espace. Le travail de thèse réalisé a pour ambition de montrer comment l'analyse de sensibilité globale peut être adaptée pour tenir compte des spécificités de ces modèles numériques spatialisés, notamment la dépendance spatiale dans les données d'entrée et les questions liées au changement d'échelle spatiale. Ce travail s'appuie sur une étude de cas approfondie du code NOE, qui est un modèle numérique spatialisé d'analyse coût-bénéfice de projets de prévention du risque d'inondation. On s'intéresse dans un premier temps à l'estimation d'indices de sensibilité associés à des variables d'entrée spatialisées. L'approche retenue du « map labelling » permet de rendre compte de l'auto-corrélation spatiale de ces variables et d'étudier son impact sur la sortie du modèle. On explore ensuite le lien entre la notion d'« échelle » et l'analyse de sensibilité de modèles spatialisés. On propose de définir les indices de sensibilité « zonaux » et « ponctuels » pour mettre en évidence l'impact du support spatial de la sortie d'un modèle sur la hiérarchisation des sources d'incertitude. On établit ensuite, sous certaines conditions, des propriétés formelles de ces indices de sensibilité. Ces résultats montrent notamment que l'indice de sensibilité zonal d'une variable d'entrée spatialisée diminue à mesure que s'agrandit le support spatial sur lequel est agrégée la sortie du modèle. L'application au modèle NOE des méthodologies développées se révèle riche en enseignements pour une meilleure prise en compte des incertitudes dans les modèles d'analyse coût-bénéfice des projets de prévention du risque d'inondation. / Variance-based global sensitivity analysis is used to study how the variability of the output of a numerical model can be apportioned to different sources of uncertainty in its inputs. It is an essential component of model building as it helps to identify model inputs that account for most of the model output variance. However, this approach is seldom applied in Earth and Environmental Sciences, partly because most of the numerical models developed in this field include spatially distributed inputs or outputs . Our research work aims to show how global sensitivity analysis can be adapted to such spatial models, and more precisely how to cope with the following two issues: i) the presence of spatial auto-correlation in the model inputs, and ii) the scaling issues. We base our research on the detailed study of the numerical code NOE, which is a spatial model for cost-benefit analysis of flood risk management plans. We first investigate how variance-based sensitivity indices can be computed for spatially distributed model inputs. We focus on the “map labelling” approach, which allows to handle any complex spatial structure of uncertainty in the modelinputs and to assess its effect on the model output. Next, we offer to explore how scaling issues interact with the sensitivity analysis of a spatial model. We define “block sensitivity indices” and “site sensitivity indices” to account for the role of the spatial support of model output. We establish the properties of these sensitivity indices under some specific conditions. In particular, we show that the relative contribution of an uncertain spatially distributed model input to the variance of the model output increases with its correlation length and decreases with the size of the spatial support considered for model output aggregation. By applying our results to the NOE modelling chain, we also draw a number of lessons to better deal with uncertainties in flood damage modelling and cost-benefit analysis of flood riskmanagement plans.

We present an analysis framework for performance evaluation of large-scale resource-bound (LSRB) computer systems. LSRB systems are those whose resources are continually in demand to serve resource users, who appear in large populations and cause high contention. In these systems, the delivery of quality service is crucial, even in the event of resource failure. Therefore, various techniques have been developed for evaluating their performance. In this thesis, we focus on the technique of quantitative modelling, where in order to study a system, first its model is constructed and then the system’s behaviour is analysed via the model. A number of high level formalisms have been developed to aid the task of model construction. We focus on PEPA, a stochastic process algebra that supports compositionality and enables us to easily build complex LSRB models. In spite of this advantage, however, the task of analysing LSRB models still poses unresolved challenges. LSRB models give rise to very large state spaces. This issue, known as the state space explosion problem, renders the techniques based on discrete state representation, such as numerical Markovian analysis, computationally expensive. Moreover, simulation techniques, such as Gillespie’s stochastic simulation algorithm, are also computationally demanding, as numerous trajectories need to be collected. Furthermore, as we show in our first contribution, the techniques based on the mean-field theory or fluid flow approximation are not readily applicable to this case. In LSRB models, resources are not assumed to be present in large populations and models exhibit highly noisy and stochastic behaviour. Thus, the mean-field deterministic behaviour might not be faithful in capturing the system’s randomness and is potentially too crude to show important aspects of their behaviours. In this case, the modeller is unable to obtain important performance indicators, such as the reliability measures of the system. Considering these limitations, we contribute the following analytical methods particularly tailored to LSRB models. First, we present an aggregation method. The aggregated model captures the evolution of only the system’s resources and allows us to efficiently derive a probability distribution over the configurations they experience. This distribution provides full faithfulness for studying the stochastic behaviour of resources. The aggregation can be applied to all LSRB models that satisfy a syntactic aggregation condition, which can be quickly checked syntactically. We present an algorithm to generate the aggregated model from the original model when this condition is satisfied. Second, we present a procedure to efficiently detect time-scale near-complete decomposability (TSND). The method of TSND allows us to analyse LSRB models at a reduced cost, by dividing their state spaces into loosely coupled blocks. However, one important input is a partition of the transitions defined in the model, categorising them into slow or fast. Forming the necessary partition by the analysis of the model’s complete state space is costly. Our process derives this partition efficiently, by relying on a theorem stating that our aggregation preserves the original model’s partition and therefore, it can be derived by an efficient reachability analysis on the aggregated state space. We also propose a clustering algorithm to implement this reachability analysis. Third, we present the method of conditional moments (MCM) to be used on LSRB models. Using our aggregation, a probability distribution is formed over the configurations of a model’s resources. The MCM outputs the time evolution of the conditional moments of the marginal distribution over resource users given the configurations of resources. Essentially, for each such configuration, we derive measures such as conditional expectation, conditional variance, etc. related to the dynamics of users. This method has a high degree of faithfulness and allows us to capture the impact of the randomness of the behaviour of resources on the users. Finally, we present the advantage of the methods we proposed in the context of a case study, which concerns the performance evaluation of a two-tier wireless network constructed based on the femto-cell macro-cell architecture.