Development of Adjectival Use and Meaning Structures in Swedish Students' Written production

This thesis is about the development of adjective use and meaning structures examined from a cognitive linguistic perspective. Adjectives modify nominal meanings and it is in context, in the interaction with the noun that the adjective meaning and configuration is determined. Nearly 13,000 adjective-noun combinations from texts written by Swedish students in grades 3, 5, 9, and 11/12 were analysed according to the LOC model (Ontologies and Construals in Lexical Semantics, Paradis, 2005) with regard to domains, noun ontology, adjective gradability, adjective position, and adjective function. Furthermore, the use of figurative language was studied. The results show a development from adjectives predominantly modifying concrete nouns to increasingly abstract meanings from a broad range of adjective and noun domains. The younger students use adjectives predominantly in the predicative position but there is a gradual shift towards attributive use, and attributive uses are the most common in the highest grade. Adjectives are primarily used in a descriptive function, but in the highest grade approximately one third of all adjectives are used in a classifying function. Scalar adjective construal is the most common in all grades, but the proportion of scalar uses decreases in favour of an increase in non-gradable uses. Figurative language is rare in all grades, but there is an increase in metaphorical language over the school years

Internal branding: social identity and social exchange perspectives on turning employees into brand champions

Prior research acknowledges employees' crucial role in building strong service brands, yet empirical research on how to turn employees into brand champions remains scarce and has been largely approached from an internal branding perspective. Drawing on social identity and social exchange theories, this study takes a broader organizational perspective to link internal branding outcomes (employee-brand fit, brand knowledge, and belief in the brand) and employees' perceptions of organizational support to a range of employee brand-building behaviors, with organizational identification as the key mediating mechanism. Both cross-sectional and longitudinal analyses of employee data from a major retail bank reveal organizational identification as a strong motivational force for employees to become brand champions, largely mediating the effects of internal branding outcomes. When organizational identification is low, perceived organizational support (as a quality indicator of employees' exchange-based relationship with the organization) constitutes an alternative, external motivator of on-the-job brand building behaviors; when organizational identification is high, perceived organizational support boosts employees' voluntary participation in brand development and positive word-ofmouth. These findings highlight the managerial relevance of the employee-organization relationship for turning employees into brand champions and show how organizational identification can be stimulated by means of internal branding. (authors' abstract

Simulation Optimization for the Stochastic Economic Lot Scheduling Problem with Sequence-Dependent Setup Times

We consider the stochastic economic lot scheduling problem (SELSP) with lost sales and random demand, where switching between products is subject to sequence-dependent setup times. We propose a solution based on simulation optimization using an iterative two-step procedure which combines global policy search with local search heuristics for the traveling salesman sequencing subproblem. To optimize the production cycle, we compare two criteria: minimizing total setup times and evenly distributing setups to obtain a more regular production cycle. Based on a numerical study, we find that a policy with a balanced production cycle leads to lower cost than other policies with unbalanced cycles. (authors' abstract

Optimization of stochastic-dynamic decision problems with applications in energy and production systems

Die vorliegende Arbeit beschäftigt sich mit der mathematischen Optimierung von stochastisch-dynamischen Entscheidungsproblemen. Diese Problemklasse stellt eine besondere Herausforderung für die mathematische Optimierung dar, da bislang kein Lösungsverfahren bekannt ist, das in polynomieller Zeit zu einer exakten Lösung konvergiert. Alle generischen Verfahren der dynamischen Optimierung unterliegen dem sogenannten "Fluch der Dimensionen", der dazu führt, dass die Problemkomplexität exponentiell in der Anzahl der Zustandsvariablen zunimmt. Da Entscheidungsprobleme von realistischer Größenordnung meist über eine Vielzahl von Zustandsvariablen verfügen, stoßen exakte Lösungsverfahren schnell an ihre Grenzen. Einen vielversprechenden Ausweg, um dem Fluch der Dimensionen zu entgehen, stellen Verfahren der "approximativ-dynamischen Optimierung" dar (engl.: "approximate dynamic programming"), welche versuchen eine Nährungslösung des stochastisch-dynamischen Problems zu berechnen. Diese Verfahren erzeugen eine künstliche Stichprobe des Entscheidungsprozesses mittels Monte-Carlo-Simulation und konstruieren basierend auf dieser Stichprobe eine Approximation der Wertfunktion des dynamischen Problems. Dabei wird die Stichprobe so gewählt, dass lediglich diejenigen Zustände in die Stichprobe aufgenommen werden, welche für den Entscheidungsprozess von Bedeutung sind, wodurch eine vollständige Enumeration des Zustandsraums vermieden wird. In dieser Arbeit werden Verfahren der approximativ-dynamischen Optimierung auf verschiedene Probleme der Produktions- und Energiewirtschaft angewendet und daraufhin überprüft, ob sie in der Lage sind, das zugrundeliegende mathematische Optimierungproblem nährungsweise zu lösen. Die Arbeit kommt zu dem Ergebnis, dass sich komplexe stochastisch-dynamische Bewirtschaftungsprobleme effizient lösen lassen, sofern das Optimierungsproblem konvex und der Zufallsprozess unabhängig vom Entscheidungsprozess ist. Handelt es sich hingegen um ein diskretes Optimierungsproblem, so stoßen auch Verfahren der approximativ-dynamischen Optimierung an ihre Grenzen. In diesem Fall sind gut kalibrierte, einfache Entscheidungsregeln möglicherweise die bessere Alternative.This thesis studies mathematical optimization methods for stochastic-dynamic decision problems. This problem class is particularly challenging, as there still exists no algorithm that converges to an exact solution in polynomial time. Existing generic solution methods are all subject to the "curse of dimensionality", which means that problem complexity increases exponentially in the number of state variables. Since problems of realistic size typically come with a large number of state variables, applying exact solution methods is impractical. A promising methodology to break the curse of dimensionality is "approximate dynamic programming". To avoid a complete enumeration of the state space, solution techniques based on this methodology use Monte Carlo simulation to sample states that are relevant to the decision process and then approximate the value function of the dynamic program by a function of much lower complexity. This thesis applies approximate dynamic programming techniques to different resource management problems that arise in production and energy settings and studies whether these techniques are capable of solving the underlying optimization problems. The thesis concludes that stochastic-dynamic resource management problems can be solved efficiently if the underlying optimization problem is convex and randomness independent of the resource states. If the optimization problem is discrete, however, the problem remains hard to solve, even for approximate dynamic programming techniques. In this case, simple but well-adjusted decision policies may be the better choice

Parenting and professional childcare in Chile : relations with child developmental outcomes in preschoolers

This dissertation examined the associations between parenting processes, childcare experiences, contextual factors (ethnicity, socioeconomic status [SES]) and preschool children’s socioemotional adjustment and cognitive development in Chile. After the general introduction in Chapter 1, Chapter 2 gives a historical review of child-rearing and education in Chile. Chapter 3 showed that the quality of the home environment predicted children’s receptive and expressive vocabulary after taking ethnicity, SES, and parental caregiver status into account. Furthermore, it was found that the quality of the home environment mediated the relation between SES and receptive and expressive vocabulary, which is in agreement with the Family Investment Model. Chapter 4 revealed that maternal supportive discipline both predicted school readiness and mediated the relation between SES and school readiness, in accordance with the Family Stress Model. Chapter 5 demonstrated that the quality of the home environment and child executive functions were positively associated with language ability, and that quantity of childcare was inversely related to language ability. No predictors of socioemotional adjustment emerged. The average quality of preschools was inadequate and did not predict child outcomes. Chapter 6 integrates the findings of this dissertation discussing theoretical implications, limitations, directions for future research, and implications for policy and practice. This research was supported by a grant awarded to the author by the National Commission for Scientific and Technological Research CONICYT, Chile (Becas Chile).Development Psychopathology in context: famil

Quantifying Semantic Linguistic Maturity in Children

We propose a method to quantify semantic linguistic maturity (SELMA) based on a high dimensional semantic representation ofwords created from the co-occurrence of words in a large text corpus. The method was applied to oral narratives from 108 children aged 4;0–12;10. By comparing the SELMA measure with maturity ratings made by human raters we found that SELMA predicted the rating of semantic maturity made by human raters over and above the prediction made using a child’s age and number of words produced. We conclude that the semantic content of narratives changes in a predictable pattern with children’s age and argue that SELMA is a measure quantifying semantic linguistic maturity. The study opens up the possibility of using quantitative measures for studying the development of semantic representation in children’s narratives, and emphasizes the importance of word co-occurrences for understanding the development of meaning

Semantic profiles of antonymic adjectives in discourse

This study has two goals: Firstly, to give an account of the semantic organization of individually used antonymic adjectives in discourse, and secondly, based on these finding, and previous work on antonymic meanings, contribute to a comprehensive theoretical account of their representation within the framework of Cognitive Linguistics. The hypothesis is that the members of the pairs are used in the same contexts and in the same type of constructions, not only when they co-occur and are used to express binary opposition as shown in previous work, but also otherwise. The manually coded corpus data from the BNC are analyzed along four semantic parameters: (i) the configuration of the adjectives in terms of gradability, (ii) the way they modify the nominal meanings, i.e. attributively or predicatively (iii) the meaning type of the modified nouns, and (iv) the status of the constructions with respect to whether their meanings are what we refer to as ‘basic’, metaphorical or metonymical. Multi-dimensional correspondence analysis technique is used to identify similarity spaces on the basis of the totality of the data. As predicted, our findings confirm a high degree of pairwise similarity – and some differences. On the basis of these results, it can be argued that the long-standing controversy within Structuralism between proponents of the co-occurrence hypothesis and the substitutability hypothesis in antonym research is a non-issue