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Entry into kindergarten marks the beginning of formal education and has the potential to pave the way for future academic success or failure. The transition into school is expected to be a challenging time for children and their families and these challenges are likely to be enhanced for children with developmental delays (DD). Despite the importance of this period, school transition for children with DD has not been well researched. Twenty-nine parents of preschool aged children with DD, and 17 parents of children without DD participated in three one-hour phone interviews throughout the course of the child’s transition into school. The Double ABCX Model was used as a framework for the current study to measure the outcome of transition (X) (using quality of life and school readiness), which is influenced by characteristics of the child (A), resources (B) and parental perceptions (C). The objectives of the study were to: 1) describe a sample of children and their families who were transitioning into school, investigate the similarities and differences between children with DD and without DD, and investigate changes over the course of transition; and 2) determine which factors contribute to a successful transition for children with and without DD. Results showed that children with DD had lower adaptive and higher maladaptive behaviour; and were utilizing more formal services and participating in less social activities than children without DD. Parents of children with DD reported lower family income, higher parental stress, different patterns and types of perceptions, and different use of coping. Very few variables changed over the course of transition. There were no significant predictors of the child’s quality of life; and only adaptive behaviour predicted all aspects of school readiness, with family income also predicting the child’s social and emotional well-being. Implications and directions for future research are discussed. / Thesis (Master, Psychology) -- Queen's University, 2008-09-03 00:38:05.333

In recent years, there has been much discussion about the merits of the top-down design methodology. Studies show that a more successful design paradigm and, indeed, the one that human designers of circuits tend to use is one that combines bottom-up and top-down design. In this thesis we describe the development of a system that is able to combine the process of top-down refinement of a high-level design specification with the bottom-up process of speed assessment. The system is able to do so by virtue of the fact that its refinement algorithms always partition the circuit in a well-defined manner. We can therefore pre-characterize the speed of all such partition possibilities and use this information to guide the choice of partition. We then focus upon the problem of the accurate and efficient estimation of speed in VLSI circuits. Speed estimation has traditionally been performed by simulators and static timing analysers. Circuit simulation is both expensive and may exercise impossible paths, due to the fact that impossible input data was fed to the circuit or signals were diverted in the wrong direction through the circuit components. The path which a simulator tells us is the critical (slowest) path, may never be exercised during the circuit's normal use. Analysing the propagation of impossible data may therefore expose false critical paths and lead to pessimistic speed estimates. Static timing analysis is less expensive but assumes that every component in the circuit contributes its slowest possible delay. Pessimistic speed estimates result and, since the <I>slowest</I> rather than the <I>actual</I> delay contributions of some of the components are used, false critical paths may be discovered.

This thesis concerns the development of a method for the detection of small solutions to delay differential equations. The detection of small solutions is important because their presence has significant influence on the analytical prop¬erties of an equation. However, to date, analytical methods are of only limited practical use. Therefore this thesis focuses on the development of a reliable new method, based on finite order approximations of the underlying infinite dimen¬sional problem, which can detect small solutions. Decisions (concerning the existence, or otherwise, of small solutions) based on our visualisation technique require an understanding of the underlying methodol¬ogy behind our approach. Removing this need would be attractive. The method we have developed can be automated, and at the end of the thesis we present a prototype Matlab code for the automatic detection of small solutions to delay differential equations.

Thesis (M.S.)--University of Wisconsin--Madison, 1982. / Typescript. Includes bibliographical references (leaves 68-83).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1981. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 1993. / Typescript. Includes bibliographical references (leaves 152-153).

Delay discounting involves a hypothetical choice between a smaller-sooner value and a larger-later value. Past research has demonstrated the hypothetical choices made in delay discounting correlate with actual money choices and predict impulsivity with drug use, gambling, and food choices. Though delayed discounting has been studied widely, it is unknown whether impulsivity is a characteristic trait or is influenced by contextual cues. Mindfulness has been demonstrated to improve psychological well-being in various contexts. The present study explored the effect of brief mindfulness exercises on impulsivity through a multiple baseline design across 5 participants. Results were mixed, with some participant’s AUCs increasing post-treatment and others remaining the same or decreasing. The current study raised some questions for future research regarding the contextual control of mindfulness and impulsivity.

In this thesis some numerical techniques for obtaining the time optimal control of a class of time delay systems are studied and compared. The delays may be fixed or time varying. The delay systems considered, which need not be linear or time invariant, are those for which the time optimal control is bang-bang. The optimal control is found by carrying out a search in switching interval space. The method of Rosenbrock⁽²’³⁾ is used to find the switching intervals which maximize a performance index of the final states and terminal time. Kelly's⁽²¹⁾ method of gradients is shown to be applicable to systems with time varying time delays by using the costate equations of ref. [10]. The perturbations in the control are chosen in such a way that the descent in function space is changed to a steepest descent in switching interval space. In a third approach, a technique similar to that of Bryson and Denham⁽¹⁹⁾ is used to account for the terminal conditions directly. All the methods are illustrated by examples. The advantages of the direct search based on Rosenbrock's method are a) ease of programming and b) rapid convergence close to the optimum. However, initial convergence is slow when compared to that of either gradient method. Of the two gradient methods, that based on a penalty function approach was superior in ease of programming and convergence close to the optimum to that based on a descent to the final target set. Neither gradient scheme could match the rapid convergence of the Rosenbrock method close to the optimum / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Academic procrastination is a highly prevalent issue among students of all education levels and is associated with negative outcomes across many domains (e.g., grades, and physical and mental health, Zentall, 2021). Currently, the majority of research on academic procrastination and its impact on educational outcomes implements questionnaires or self-reports, which are not cohesive with a behavior-analytic approach to procrastination. This situation limits a behavioral understanding of procrastination, and thus the development of effective related interventions. The present study aimed to contribute to this gap by testing the relationship between performance in a systematic replication of the academic discounting task (ADT) designed by Olsen et al. (2018) and three temporally-based measures of academic procrastination, which were collected via the students’ course progress in their Learning Management System platforms (D2L): (a) latency to turn assignments in hours (LTA; average time in hours that elapsed between when the assignments were made available by the instructor and the student turned them in), (b) latency of starting to work on assignments in hours (LWA; average time in hours it takes a student to start working on assignments after the instructor has made them available), and (c) time-to-deadline of submitting assignments in hours (TTD; average time in hours between the time assignments were due and when they were submitted). An association between TTD and ADT k values (a measure of rate of discounting), as well as an association between the three behavioral measures was found. Also, a significant difference in ADT k values between students who reported being employed versus unemployed students was observed. Lastly, a positive association between TTD and ADT k values, and a negative association between TTD and ADT AUC values was found; namely, high rates of discounting during the ADT predicted less postponement of assignment submission. These findings altogether provide additional support for the validity of the ADT as a measure of hyperbolic discounting of academic outcomes and the relevance of the three behavioral measures of academic procrastination. However, the unexpected finding that participants who submitted their assignments earlier displayed higher rates of academic discounting during the ADT does not support Olsen et al.’s prediction that delayed academic rewards are the key contributor to student procrastination. Alternatively, it seems that more research is needed to explore the role of aversive factors in procrastination (e.g., effort required to complete the assignment and/or difficulty of the assignment or probability that the hypothetical assignment would produce the related reinforcers, such as a good grade).