922 resultados para Goal programming


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The use of plain English in document writing, whether in correspondence, agreements and deeds, court documents or judicial writing, is an important goal for the legal profession in Sri Lanka.

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The purpose of the present study was to examine the extent to which Desire for Control (DFC) interacts with experimental manipulations of demand and control, and the consequences of these interactions on task satisfaction and perceived goal attainment (i.e. task performance and task mastery). It was expected that the proposed stress-buffering effects of control would be evident only for individuals high in DFC. Moreover, it was anticipated that control may have a stress-exacerbating effect for those low in DFC. These hypotheses were tested on a sample of 137 first year psychology students who participated in an in-basket activity under low and high conditions of demand and control. Results revealed that the proposed stress-buffering effect of control was found only for those high in DFC and a stress-exacerbating effect of increased control was evident for those low in DFC on task performance and task mastery perceptions. Future research directions and the implications of these findings to applied settings are discussed.

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This study models young people's moderate drinking decision-making using the Model of Goal-Directed Behaviour (MGB), thus presenting insights into young people's desires and intentions to drink responsibly. Testing the applicability of the MGB to quantitatively analyse responsible drinking, the explanatory sphere of the MGB is extended. An online survey resulted in 1522 completed questionnaires from respondents aged between 18 and 25 years. Collected data were analysed with structural equation modelling (SEM) using SPSS AMOS21 (IBM, New York, NY, USA) software. The key finding of this study is that an individual's desire to drink moderately is the most important predictor of young people's responsible drinking intentions. Our use of MGB provides further evidence that there is a strong distinction between consumer desires and intentions.

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The value of information technology (IT) is often realized when continuously being used after users’ initial acceptance. However, previous research on continuing IT usage is limited for dismissing the importance of mental goals in directing users’ behaviors and for inadequately accommodating the group context of users. This in-progress paper offers a synthesis of several literature to conceptualize continuing IT usage as multilevel constructs and to view IT usage behavior as directed and energized by a set of mental goals. Drawing from the self-regulation theory in the social psychology, this paper proposes a process model, positioning continuing IT usage as multiple-goal pursuit. An agent-based modeling approach is suggested to further explore causal and analytical implications of the proposed process model.

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We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model’s flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat’s point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond.

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Providing debtors with the opportunity for a fresh start is popularly regarded as one of the main goals of bankruptcy legislation. However, there has been limited analysis of this goal. This article confirms that the fresh start is one of the main goals of the Australian Bankruptcy Act, and argues that this fresh start focuses on discharge of debt and does not explicitly address debtor rehabilitation. A review of the key goals could examine whether, and to what extent, rehabilitation should also be a focus of the fresh start in Australian bankruptcy law.

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We examined goal importance, focusing on high, but not exclusive priority goals, in the theory of planned behaviour (TPB) to predict students’ academic performance. At the beginning of semester, students in a psychology subject (N = 197) completed TPB and goal importance items for achieving a high grade. Regression analyses revealed partial support for the TPB. Perceived behavioural control, but not attitude or subjective norm, significantly predicted intention, with intention predicting final grade. Goal importance significantly predicted intention, but not final grade, indicating that perceiving a performance goal as highly, but not necessarily exclusively, important impacts on students’ achievement intentions.

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Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This mobility prediction model is trained using sample executions of motion primitives on representative terrain, and predicts the future outcome of control actions on similar terrain. Using Gaussian process regression allows us to exploit its inherent measure of prediction uncertainty in planning. We integrate mobility prediction into a Markov decision process framework and use dynamic programming to construct a control policy for navigation to a goal region in a terrain map built using an on-board depth sensor. We consider both rigid terrain, consisting of uneven ground, small rocks, and non-traversable rocks, and also deformable terrain. We introduce two methods for training the mobility prediction model from either proprioceptive or exteroceptive observations, and report results from nearly 300 experimental trials using a planetary rover platform in a Mars-analogue environment. Our results validate the approach and demonstrate the value of planning under uncertainty for safe and reliable navigation.

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This tutorial is designed to help new users become familiar with using the Spartan-3E board. The tutorial steps through: writing a small program in VHDL which carries out simple combinational logic; connecting the program inputs and outputs to the switches, buttons and LEDs on the Spartan-3E board; downloading the program to the Spartan-3E board using version 14.7 of the Xilinx ISE; and simulating the program using the iSim Simulator.

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Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.

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In current practice, urban-rural development has been regarded as one of the key pillars in driving regenerative development that includes economic, social, and environmental balance. In association with rapid urbanization, an important contemporary issue in China is that its rural areas are increasingly lagging behind urban areas in their development and a coordinated provision of public facilities in rural areas is necessary to achieve a better balance. A model is therefore introduced for quantifying the effect of individual infrastructure projects on urban-rural balance (e-UR) by focusing on two attributes, namely, efficiency and equity. The model is demonstrated through a multi-criteria model, developed with data collected from infrastructure projects in Chongqing, with the criteria values for each project being scored by comparing data collected from the project involved with e-UR neutral “benchmark” values derived from a survey of experts in the field. The model helps evaluate the contribution of the projects to improving rural-urban balance and hence enable government decision-makers for the first time to prioritize future projects rigorously in terms of their likely contribution too.

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In the context of physical activity, intrinsic motivation refers to the inherent satisfaction associated with participation in the activity. Interest-enjoyment, perceived competence, and effort have been identified as three underlying components of intrinsic motivation. Achievement goal theory stipulates that achievement goals guide our beliefs and behavior. The two main achievement goal orientations identified in the sport and physical activity literature are task and ego orientations. A person with a strong task orientation defines success in self-referenced terms, as improving one’s own performance or mastering new skills. Someone with a strong ego orientation defines success normatively, as being better than others. The majority of research suggests that having a strong task orientation is a good thing, whether with regard to motivationally adaptive responses, sources of sport confidence, students’ satisfaction with learning, or the use of cognitive and self-regulatory strategies. Although the literature supporting the potential benefits of having a strong task orientation is vast, considerably less research has tested interventions designed to strengthen task orientations and intrinsic motivation. A climate that emphasises individual mastery has resulted in increased interest-enjoyment and perceived competence, whereas an emphasis on competition and comparison with others has resulted in a decrease in interest-enjoyment and an increase in tension-pressure. One possible intervention is the use of structured self-reflection. Using self-reflection sheets that cause respondents to focus on specific elements of technique or skills, and rate one’s own performance, should theoretically promote a task focus. Hanrahan suggested that engaging in self-reflection may enhance intrinsic motivation. Perceived competence could be positively affected, as self-analysis and self-monitoring have been found to positively influence the acquisition of physical skills. The purpose of this study was to determine if the use of structured self-reflection in community dance classes would influence achievement goal orientations or levels of intrinsic motivation.

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Introduction Measuring occupational performance is an essential part of clinical practice; however, there is little research on service user perceptions of measures. The aim of this investigation was to explore the acceptability and utility of one occupational performance outcome measure, Goal Attainment Scaling, with young people (12–25 years old) seeking psychological help. Method Semi-structured interviews were conducted with ten young people seeking help from a youth mental health clinic. Interviews were audio taped and a field diary kept. Interviews were transcribed verbatim and analysed using content analysis. Results were verified by member checking. Results All participants were able to engage in using Goal Attainment Scaling to set goals for therapy, and reported the process to be useful. The participants identified the physical location and ownership of the scale was important to help motivate them to work on their goals. Conclusion Young help-seekers see Goal Attainment Scaling as an acceptable tool to facilitate the establishment of functional goals. Young service users were particularly keen to maintain control over the physical location of completed forms.