105 resultados para formal human behavior model

em Queensland University of Technology - ePrints Archive


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Effective digital human model (DHM) simulation of automotive driver packaging ergonomics, safety and comfort depends on accurate modelling of occupant posture, which is strongly related to the mechanical interaction between human body soft tissue and flexible seat components. This paper presents a finite-element study simulating the deflection of seat cushion foam and supportive seat structures, as well as human buttock and thigh soft tissue when seated. The three-dimensional data used for modelling thigh and buttock geometry were taken on one 95th percentile male subject, representing the bivariate percentiles of the combined hip breadth (seated) and buttock-to-knee length distributions of a selected Australian and US population. A thigh-buttock surface shell based on this data was generated for the analytic model. A 6mm neoprene layer was offset from the shell to account for the compression of body tissue expected through sitting in a seat. The thigh-buttock model is therefore made of two layers, covering thin to moderate thigh and buttock proportions, but not more fleshy sizes. To replicate the effects of skin and fat, the neoprene rubber layer was modelled as a hyperelastic material with viscoelastic behaviour in a Neo-Hookean material model. Finite element (FE) analysis was performed in ANSYS V13 WB (Canonsburg, USA). It is hypothesized that the presented FE simulation delivers a valid result, compared to a standard SAE physical test and the real phenomenon of human-seat indentation. The analytical model is based on the CAD assembly of a Ford Territory seat. The optimized seat frame, suspension and foam pad CAD data were transformed and meshed into FE models and indented by the two layer, soft surface human FE model. Converging results with the least computational effort were achieved for a bonded connection between cushion and seat base as well as cushion and suspension, no separation between neoprene and indenter shell and a frictional connection between cushion pad and neoprene. The result is compared to a previous simulation of an indentation with a hard shell human finite-element model of equal geometry, and to the physical indentation result, which is approached with very high fidelity. We conclude that (a) SAE composite buttock form indentation of a suspended seat cushion can be validly simulated in a FE model of merely similar geometry, but using a two-layer hard/soft structure. (b) Human-seat indentation of a suspended seat cushion can be validly simulated with a simplified human buttock-thigh model for a selected anthropomorphism.

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When working with the world’s most vulnerable populations there are questions surrounding the salience of physical activity promotion programs given the multitude of basic needs that must first be met. Indeed, physical activity may be a low priority for individuals seeking safety, reunification with loved ones, and food for their families, as a subsistence lifestyle makes excess weight gain, diabetes, and cardiovascular disease irrelevant. Yet, when working with people from a refugee background for whom these challenges all too frequently apply, opportunities for sport and activity have repeatedly surfaced as desirable and needed, yet are utterly deficient. If we conceptualize physical activity purely as a chronic disease prevention tool, its significance within under-resourced communities is most assuredly lost; however, if we harness the power of physical activity to serve as an agent of positive social change, then it instantly becomes more meaningful and necessary.

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Alexander’s Ecological Dominance and Social Competition (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality (Alexander, 1990; Finn, Geary & Ward, 2005; Irons, 2005). His model provides a basis for explaining the evolution of human socio-cognitive abilities. Our paper examines the extension of Alexander’s model to incorporate the human trait of information behavior in synergy with ecological dominance and social competition as a human socio-cognitive competence. This paper discusses the various interdisciplinary perspectives exploring how evolution has shaped information behavior and why information behavior is emerging as an important human socio-cognitive competence. This paper outlines these issues, including the extension of Spink and Currier’s (2006a,b) evolution of information behavior model towards a more integrated understanding of how information behaviors have evolved (Spink & Cole, 2006).

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Alexander’s Ecological Dominance and Social Competition (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality (Alexander, 1990; Finn, Geary & Ward, 2005; Irons, 2005). His model provides a basis for explaining the evolution of human socio-cognitive abilities. Our paper examines the extension of Alexander’s model to incorporate the human trait of information behavior in synergy with ecological dominance and social competition as a human socio-cognitive competence. This paper discusses the various interdisciplinary perspectives exploring how evolution has shaped information behavior and why information behavior is emerging as an important human socio-cognitive competence. This paper outlines these issues, including the extension of Spink and Currier’s (2006a,b) evolution of information behavior model towards a more integrated understanding of how information behaviors have evolved (Spink & Cole, 2006).

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Elaborated Intrusion theory (Kavanagh, Andrade & May 2005) distinguishes between unconscious, associative processes as the precursors of desire, and controlled processes of cognitive elaboration that lead to conscious sensory images of the target of desire and associated affect. We argue that these mental images play a key role in motivating human behavior. Consciousness is functional in that it allows competing goals to be compared and evaluated. The role of effortful cognitive processes in desire helps to explain the different time courses of craving and physiological withdrawal.

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In the quest for shorter time-to-market, higher quality and reduced cost, model-driven software development has emerged as a promising approach to software engineering. The central idea is to promote models to first-class citizens in the development process. Starting from a set of very abstract models in the early stage of the development, they are refined into more concrete models and finally, as a last step, into code. As early phases of development focus on different concepts compared to later stages, various modelling languages are employed to most accurately capture the concepts and relations under discussion. In light of this refinement process, translating between modelling languages becomes a time-consuming and error-prone necessity. This is remedied by model transformations providing support for reusing and automating recurring translation efforts. These transformations typically can only be used to translate a source model into a target model, but not vice versa. This poses a problem if the target model is subject to change. In this case the models get out of sync and therefore do not constitute a coherent description of the software system anymore, leading to erroneous results in later stages. This is a serious threat to the promised benefits of quality, cost-saving, and time-to-market. Therefore, providing a means to restore synchronisation after changes to models is crucial if the model-driven vision is to be realised. This process of reflecting changes made to a target model back to the source model is commonly known as Round-Trip Engineering (RTE). While there are a number of approaches to this problem, they impose restrictions on the nature of the model transformation. Typically, in order for a transformation to be reversed, for every change to the target model there must be exactly one change to the source model. While this makes synchronisation relatively “easy”, it is ill-suited for many practically relevant transformations as they do not have this one-to-one character. To overcome these issues and to provide a more general approach to RTE, this thesis puts forward an approach in two stages. First, a formal understanding of model synchronisation on the basis of non-injective transformations (where a number of different source models can correspond to the same target model) is established. Second, detailed techniques are devised that allow the implementation of this understanding of synchronisation. A formal underpinning for these techniques is drawn from abductive logic reasoning, which allows the inference of explanations from an observation in the context of a background theory. As non-injective transformations are the subject of this research, there might be a number of changes to the source model that all equally reflect a certain target model change. To help guide the procedure in finding “good” source changes, model metrics and heuristics are investigated. Combining abductive reasoning with best-first search and a “suitable” heuristic enables efficient computation of a number of “good” source changes. With this procedure Round-Trip Engineering of non-injective transformations can be supported.

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The popularity of social networking sites (SNSs) among adolescents has grown exponentially, with little accompanying research to understand the influences on adolescent engagement with this technology. The current study tested the validity of an extended theory of planned behaviour model (TPB), incorporating the additions of group norm and self-esteem influences, to predict frequent SNS use. Adolescents (N = 160) completed measures assessing the standard TPB constructs of attitude, subjective norm, perceived behavioural control (PBC), and intention, as well as group norm and self-esteem. One week later, participants reported their SNS use during the previous week. Support was found for the standard TPB variables of attitude and PBC, as well as group norm, in predicting intentions to use SNS frequently, with intention, in turn, predicting behaviour. These findings provide an understanding of the factors influencing frequent engagement in what is emerging as a primary tool for adolescent socialisation.

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This paper describes the development and evaluation of a tactical lane change model using the forward search algorithm, for use in a traffic simulator. The tactical lane change model constructs a set of possible choices of near-term maneuver sequences available to the driver and selects the lane change action at the present time to realize the best maneuver plan. Including near term maneuver planning in the driver behavior model can allow a better representation of the complex interactions in situations such as a weaving section and high-occupancy vehicle (HOV) lane systems where drivers must weave across several lanes in order to access the HOV lanes. To support the investigation, a longitudinal control model and a basic lane change model were also analyzed. The basic lane change model is similar to those used by today's commonly-used traffic simulators. Parameters in all models were best-fit estimated for selected vehicles from a real-world freeway vehicle trajectory data set. The best-fit estimation procedure minimizes the discrepancy between the model vehicle and real vehicle's trajectories. With the best fit parameters, the proposed tactical lane change model gave a better overall performance for a greater number of cases than the basic lane change model.

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The ability to detect unusual events in surviellance footage as they happen is a highly desireable feature for a surveillance system. However, this problem remains challenging in crowded scenes due to occlusions and the clustering of people. In this paper, we propose using the Distributed Behavior Model (DBM), which has been widely used in computer graphics, for video event detection. Our approach does not rely on object tracking, and is robust to camera movements. We use sparse coding for classification, and test our approach on various datasets. Our proposed approach outperforms a state-of-the-art work which uses the social force model and Latent Dirichlet Allocation.

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Unsafe acts of workers (e.g. misjudgment, inappropriate operation) become the major root causes of construction accidents when they are combined with unsafe working conditions (e.g. working surface conditions, weather) on a construction site. The overarching goal of the research presented in this paper is to explore ways to prevent unsafe acts of workers and reduce the likelihood of construction accidents occurring. The study specifically aims to (1) understand the relationships between human behavior related and working condition related risk factors, (2) identify the significant behavior and condition factors and their impacts on accident types (e.g. struck by/against, caught in/between, falling, shock, inhalation/ingestion/absorption, respiratory failure) and injury severity (e.g. fatality, hospitalized, non-hospitalized), and (3) analyze the fundamental accident-injury relationship on how each accident type contributes to the injury severity. The study reviewed 9,358 accidents which occurred in the U.S. construction industry between 2002 and 2011. The large number of accident samples supported reliable statistical analyses. The analysis identified a total of 17 significant correlations between behavior and condition factors and distinguished key risk factors that highly impacted on the determination of accident types and injury severity. The research outcomes will assist safety managers to control specific unsafe acts of workers by eliminating the associated unsafe working conditions and vice versa. They also can prioritize risk factors and pay more attention to controlling them in order to achieve a safer working environment.

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This research investigates the decision making process of individuals from revealed preferences in extreme environments or life-and-death situations, from a behavioral economics perspective. The empirical analysis of revealed behavioral preferences shows how the individual decision making process can deviate from the standard self-interested or “homo economicus” model in non-standard situations. The environments examined include: elite athletes in FIFA World and Euro Cups; climbing on Everest and the Himalaya; communication during 9/11 and risk seeking after the 2011 Brisbane floods. The results reveal that the interaction of culture and environment has a significant impact on the decision process, as social behaviors and institutions are intimately intertwined, which govern the processes of human behavior and interaction. Additionally, that risk attitudes are not set and that immediate environmental factors can induce a significant shift in an individuals risk seeking behaviors.

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This paper provides a detailed description of the current Australian e-passport implementation and makes a formal verification using model checking tools CASPER/CSP/FDR. We highlight security issues present in the current e-passport implementation and identify new threats when an e-passport system is integrated with an automated processing systems like SmartGate. Because the current e-passport specification does not provide adequate security goals, to perform a rational security analysis we identify and describe a set of security goals for evaluation of e-passport protocols. Our analysis confirms existing security issues that were previously informally identified and presents weaknesses that exists in the current e-passport implementation.

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The ineffectiveness of current design processes has been well studied and has resulted in widespread calls for the evolution and development of new management processes. Perhaps one problem is that with the advent of BIM we are moving from one stage to another without necessarily having resolved all the issues. CAD design technology, if well handled, could have significantly raised the level of quality and efficiency of current processes, but in practice this was not fully realized. Therefore, technology alone can´t solve all the problems and the advent of BIM could result in a similar bottleneck. For a precise definition of the problem to be solved we should start by understanding what are the main current bottlenecks that have yet to be overcome by either new technologies or management processes, and the impact of human behavior related issues despite the advent of new technologies. The fragmented and dispersed nature of the AEC sector and the huge number of small organizations that comprise it would probably be a major limiting factor. Several authors have addressed this issue and more recently IDDS has been defined as the highest level of achievement. However, what is written on IDDS shows an extremely ideal situation on a state to be achieved; it shows a holistic utopian proposition with the intent to create the research agenda to move towards that state. Key to IDDS is the framing of a new management model which should address the problems associated with key aspects: technology, processes, policies and people. One of the primary areas to be further studied is the process of collaborative work and understanding, together with the development of proposals to overcome the many cultural barriers that currently exist and impede the advance of new management methods. The purpose of this paper is to define and delimit problems to be solved so that it is possible to implement a new management model for a collaborative design process.

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Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams. It is necessary to consider human-factors in {CF} modeling for a more realistic representation of {CF} behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of {CF} models available in the literature, none of these specifically focuses on the human factors in these models. This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area.