Spring-to-Spring Balancing as Energy-Free Adjustment Method in Gravity Equilibrators

Generally, adjustment of gravity equilibrator to a new payload requires energy, e.g. to increase the pre-load of the balancing spring. A novel way of energy-free adjustment of gravity equilibrators is possible by introducing the concept of a storage spring. The storage spring supplies or stores the energy necessary to adjust the balancer spring of the gravity equilibrator. In essence the storage spring mechanism maintains a constant potential energy within the spring mechanism; energy is exchanged between the storage and balancer spring when needed. Various conceptual designs using both zero-free-length springs and regular extension springs are proposed. Two models were manufactured demonstrating the practical embodiments and functionality.

Stereo display with time-multiplexed focal adjustment

In stereo displays, binocular disparity creates a striking impression of depth. However, such displays present focus cues - blur and accommodation - that specify a different depth than disparity, thereby causing a conflict. This conflict causes several problems including misperception of the 3D layout, difficulty fusing binocular images, and visual fatigue. To address these problems, we developed a display that preserves the advantages of conventional stereo displays, while presenting correct or nearly correct focus cues. In our new stereo display each eye views a display through a lens that switches between four focal distances at very high rate. The switches are synchronized to the display, so focal distance and the distance being simulated on the display are consistent or nearly consistent with one another. Focus cues for points in-between the four focal planes are simulated by using a depth-weighted blending technique. We will describe the design of the new display, discuss the retinal images it forms under various conditions, and describe an experiment that illustrates the effectiveness of the display in maximizing visual performance while minimizing visual fatigue. © 2009 SPIE-IS&T.

An automatic step adjustment method for average power analysis technique used in fiber amplifiers

An automatic step adjustment (ASA) method for average power analysis (APA) technique used in fiber amplifiers is proposed in this paper for the first time. In comparison with the traditional APA technique, the proposed method has suggested two unique merits such as a higher order accuracy and an ASA mechanism, so that it can significantly shorten the computing time and improve the solution accuracy. A test example demonstrates that, by comparing to the APA technique, the proposed method increases the computing speed by more than a hundredfold under the same errors. By computing the model equations of erbium-doped fiber amplifiers, the numerical results show that our method can improve the solution accuracy by over two orders of magnitude at the same amplifying section number. The proposed method has the capacity to rapidly and effectively compute the model equations of fiber Raman amplifiers and semiconductor lasers. (c) 2006 Optical Society of America

The effect of a life development intervention on sports career transition adjustment

Lavallee, D. (2005). The effect of a life development intervention on sports career transition adjustment. The Sport Psychologist. 19(2), pp.193-202 RAE2008

College adjustment, depressive symptoms and peer support among undergraduate university students

Background: College adjustment is a developmental milestone that can be stressful and may lead to mental health problems such as depression. Support during this adjustment period is seen as essential, however it is unknown if informal peer support from fellow students has any impact on either college adjustment or depressive symptoms. Aim: To identify levels of social and personal college adjustment, depressive symptoms and peer support among students, and to examine the relationship between the variables. Design: A quantitative correlational design was used Instruments: Data were collected using two subscales of the Student Adaptation to College Questionnaire; the Centre for Epidemiology Depressive Symptoms Scale and a subscale of the Peer Support Evaluation Inventory. Sample: The sample consisted of 417, first (n=188), second (n=134) and fourth (n=94) year nursing and midwifery students from one University in Ireland. Findings: The findings indicated that 20% of participants were poorly personally adjusted and 9% poorly socially adjusted. Furthermore, 34% of participants experienced significant depressive symptoms. Most students had good levels of peer support. Statistically significant relationships were found between all key variables, the strongest of which were between personal adjustment and depressive symptoms and social adjustment and depressive symptoms. Differences in adjustment and depressive symptom scores were found based on year of study, with second year students experiencing more depressive symptoms and having poorer personal adjustment scores. Participants who had poor relationships with their father’s experienced greater depressive symptoms and had more difficulties personally and socially adjusting to college. The alcohol consumption of participants had a statistically significant correlation with college adjustment, depressive symptoms and peer support, with higher consumption having a positive impact on the variables.

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham's-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between the two approaches are found. In particular, we prove a theorem that characterizes a surprising aymptotic discrepancy between fully Bayes and empirical Bayes. This discrepancy arises from a different source than the failure to account for hyperparameter uncertainty in the empirical-Bayes estimate. Indeed, even at the extreme, when the empirical-Bayes estimate converges asymptotically to the true variable-inclusion probability, the potential for a serious difference remains. © Institute of Mathematical Statistics, 2010.

Flexible self-adjustment of task deployment in dynamic environments

This paper presents an investigation into dynamic self-adjustment of task deployment and other aspects of self-management, through the embedding of multiple policies. Non-dedicated loosely-coupled computing environments, such as clusters and grids are increasingly popular platforms for parallel processing. These abundant systems are highly dynamic environments in which many sources of variability affect the run-time efficiency of tasks. The dynamism is exacerbated by the incorporation of mobile devices and wireless communication. This paper proposes an adaptive strategy for the flexible run-time deployment of tasks; to continuously maintain efficiency despite the environmental variability. The strategy centres on policy-based scheduling which is informed by contextual and environmental inputs such as variance in the round-trip communication time between a client and its workers and the effective processing performance of each worker. A self-management framework has been implemented for evaluation purposes. The framework integrates several policy-controlled, adaptive services with the application code, enabling the run-time behaviour to be adapted to contextual and environmental conditions. Using this framework, an exemplar self-managing parallel application is implemented and used to investigate the extent of the benefits of the strategy