The development of temperament and character during adolescence: The processes and phases of change

AbstractWe studied the pattern of personality development in a longitudinal population-based sample of 752 American adolescents. Personality was assessed reliably with the Junior Temperament and Character Inventory at 12, 14, and 16 years of age. The rank-order stability of Junior Temperament and Character Inventory traits from age 12 to 16 was moderate (r = .35). Hierarchical linear modeling of between-group variance due to gender and within-group variance due to age indicated that harm avoidance and persistence decreased whereas self-directedness and cooperativeness increased from age 12 to 16. Novelty seeking, reward dependence, and self-transcendence increased from age 12 to 14 and then decreased. This biphasic pattern suggests that prior to age 14 teens became more emancipated from adult authorities while identifying more with the emergent norms of their peers, and after age 14 their created identity was internalized. Girls were more self-directed and cooperative than boys and maintained this advantage from age 12 to 16. Dependability of temperament at age 16 was mainly predicted by the same traits at earlier ages. In contrast, maturity of character at age 16 was predicted by both temperament and character at earlier ages. We conclude that character develops rapidly in adolescence to self-regulate temperament in accord with personally valued goals shaped by peers.</jats:p

Techniques for the Fast Simulation of Models of Highly dependable Systems

With the ever-increasing complexity and requirements of highly dependable systems, their evaluation during design and operation is becoming more crucial. Realistic models of such systems are often not amenable to analysis using conventional analytic or numerical methods. Therefore, analysts and designers turn to simulation to evaluate these models. However, accurate estimation of dependability measures of these models requires that the simulation frequently observes system failures, which are rare events in highly dependable systems. This renders ordinary Simulation impractical for evaluating such systems. To overcome this problem, simulation techniques based on importance sampling have been developed, and are very effective in certain settings. When importance sampling works well, simulation run lengths can be reduced by several orders of magnitude when estimating transient as well as steady-state dependability measures. This paper reviews some of the importance-sampling techniques that have been developed in recent years to estimate dependability measures efficiently in Markov and nonMarkov models of highly dependable system

A synthesis of logic and biology in the design of dependable systems

The technologies of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, have advanced in recent years. Much of this development can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that combines effectively and throughout the design lifecycle these two techniques which are schematically founded on the two pillars of formal logic and biology. Such a design paradigm would apply these techniques synergistically and systematically from the early stages of design to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems that brings these technologies together to realise their combined potential benefits

A synthesis of logic and bio-inspired techniques in the design of dependable systems

Much of the development of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that effectively combines these two techniques, schematically founded on the two pillars of formal logic and biology, from the early stages of, and throughout, the design lifecycle. Such a design paradigm would apply these techniques synergistically and systematically to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems, presented in the scope of the HiP-HOPS tool and technique, that brings these technologies together to realise their combined potential benefits. The paper begins by identifying current challenges in model-based safety assessment and then overviews the use of meta-heuristics at various stages of the design lifecycle covering topics that span from allocation of dependability requirements, through dependability analysis, to multi-objective optimisation of system architectures and maintenance schedules