Video streaming over the best-effort networks is a challenging problem due to the time-varying and uncertain characteristics of the links. When multiple video streams are present in a network, they share and compete for the common bandwidth. In such a setting, a bandwidth allocation algorithm is required to distribute the available resources among the streams in a fair and efficient way. Specifically, it is desired to establish fairness across end-users' Quality of Experience (QoE). In this research, we propose three novel methods to provide QoE-fair network bandwidth allocation among multiple video streaming sessions. First, we formulate the problem of bandwidth allocation for video flows in the context of Network Utility Maximization (NUM) framework, using sigmoidal utility functions, rather than conventional but unrealistic concave functions. An approximation algorithm for Sigmoidal Programming (SP) is utilized to solve the resulting nonconvex optimization problem, called NUM-SP. Simulation results indicate improvements of at least 60% in average utility/QoE and 45% in fairness, while using slightly less network resources, compared to two representative methods. Subsequently, we take a collaborative decision-theoretic approach to the problem of rate adaptation among multiple video streaming sessions, and design a multi-objective foresighted optimization model for network resource allocation. A social welfare function is constructed to capture both fairness and efficiency objectives at the same time. Then, assuming a common altruistic goal for all network users, we use multi-agent decision processes to find the optimal policies for all players. We propose a Decentralized Partially Observable Markov Decision Process (Dec-POMDP) model for the conventional IP networks and a Multi-agent Markov Decision Process (MMDP) model for the SDN-enabled wireless networks. By planning these cooperative decision process models, we find the optimal network bandwidth allocation that leads to social welfare maximization. Distributed multi-agent reinforcement learning algorithms are also designed and proposed as a low-complexity model-free solution to these optimization problems. Simulations of the proposed methods show that the resulting optimal policies of the novel Social Utility Maximization (SUM) framework outperform existing approaches in terms of both efficiency and fairness. The Dec-POMDP model applied to a server-side rate adaptation results in 25% improvement in efficiency and 13% improvement in fairness, compared to one popular protocol of congestion control for multimedia streaming. Our performance evaluations also show that the MMDP model applied to a client-side rate adaptation like DASH improves efficiency, fairness, and social welfare by as much as 18%, 24%, and 25%, respectively compared to current state-of-the-art.

The present study sought to identify the effects that derived relational training had on simulated gambling behavior with slot machines. Prior to conducting any relational training procedures, participants' relational responses in each contextual condition was probed. Each of the four backgrounds/conditions (red, blue, green, yellow) were presented with various stimuli from differing stimulus classes. Twenty trials were presented with no feedback for correct responding. Upon completion of the probes, pretest preference assessments were administered with blue and red slot machines being concurrently available for twenty trials then green and yellow slot machines doing the same. Following the pretest preference assessment, relational training began, here stimuli from each of the stimulus classes were presented on screen for three of the contextual conditions with the blue contextual condition left out to assess for possible derived relational responses. After completion, the second set of relational probes and posttest preference assessments began to assess if relational training altered the response allocation of slot machines and accuracy of responding during probes. After relational training, all participants showed an increase in response allocation to the red slot machine and a decrease to the blue. The yellow slot machine was selected increasingly with three participants while green was selected more often with one individual, one staying at the same number, and two selecting it less than in the pretest.

This dissertation aims to apply non-zero attitude and position setpoint tracking to a quadrotor aircraft, achieved by solving the problem of a quadrotor’s inherent underactuation. The introduction of extra actuation aims to mechanically accommodate for stable tracking of non-zero state trajectories. The requirement of the project is to design, model, simulate and control a novel quadrotor platform which can articulate all six degrees of rotational and translational freedom (6-DOF) by redirecting and vectoring each propeller’s individually produced thrust. Considering the extended articulation, the proposal is to add an additional two axes (degrees) of actuation to each propeller on a traditional quadrotor frame. Each lift propeller can be independently pitched or rolled relative to the body frame. Such an adaptation, to what is an otherwise well understood aircraft, produces an over-actuated control problem. Being first and foremost a control engineering project, the focus of this work is plant model identification and control solution of the proposed aircraft design. A higher-level setpoint tracking control loop designs a generalized plant input (net forces and torques) to act on the vehicle. An allocation rule then distributes that virtual input in solving for explicit actuator servo positions and rotational propeller speeds. The dissertation is structured as follows: First a schedule of relevant existing works is reviewed in Ch:1 following an introduction to the project. Thereafter the prototype’s design is detailed in Ch:2, however only the final outcome of the design stage is presented. Following that, kinematics associated with generalized rigid body motion are derived in Ch:3 and subsequently expanded to incorporate any aerodynamic and multibody nonlinearities which may arise as a result of the aircraft’s configuration (changes). Higher-level state tracking control design is applied in Ch:4 whilst lower-level control allocation rules are then proposed in Ch:5. Next, a comprehensive simulation is constructed in Ch:6, based on the plant dynamics derived in order to test and compare the proposed controller techniques. Finally a conclusion on the design(s) proposed and results achieved is presented in Ch:7. Throughout the research, physical tests and simulations are used to corroborate proposed models or theorems. It was decided to omit flight tests of the platform due to time constraints, those aspects of the project remain open to further investigation. The subsequent embedded systems design stemming from the proposed control plant is outlined in the latter of Ch:2, Sec:2.4. Such implementations are not investigated here but design proposals are suggested. The primary outcome of the investigation is ascertaining the practicality and feasibility of such a design, most importantly whether or not the complexity of the mechanical design is an acceptable compromise for the additional degrees of control actuation introduced. Control derivations and the prototype design presented here are by no means optimal nor the most exhaustive solutions, focus is placed on the whole system and not just a single aspect of it.

The purpose of this study was to explore workload allocation, what informed workload allocation in secondary schools and analyse documents relevant to educator workload. A qualitative interpretive approach using a case study as a research design was used to complete the study. Sixteen educators which consist of 6 heads of departments, principal and 9 post level one educators were purposively sampled and interviewed from different types of schools( rural, township and former model C schools). The findings of the study suggested that, workload in the secondary schools under study was allocated in a transparent and flexible manner. Educators were consulted and their inputs were regarded imperative in decision making. Further, it was found that experience, specialisation and qualifications informed workload allocation in schools. During the analysis of data, themes such as educator reputation meaning their competence, learner results and commitment emerged as factors that also informed workload allocation in schools. Allocators considered factors like the number of subjects, number of preparations and number of classes but ignored the number of learners in classes when allocating work in schools. Therefore, the differences in terms of number of learners would mean there was no equity in allocation of educators because the number of learners affected marking of assessments, feedback to learner, reaching gifted and not gifted learners, discipline in classrooms, timeous submissions of marks, and regular control of learner books. Majority of educators were allocated teaching time below the requirements as stipulated in the Personnel Administration Measures (PAM) Government Gazette No. 24948 dated 21 February 2003. Therefore workload of most educators was manageable. The majority of post level one educators were allocated teaching time below 85%. Only one post level one educator from school A and B was allocated within the stipulated teaching time as expected by the department and most educators were allocated below. From the allocation of school C only 3 post level one educators out of a maximum of twenty five paid by the government were allocated within the stipulated time. Allocation changed throughout the year because promotions and redeployment of educators were done at any time during the year. / Dissertation (MEd)--University of Pretoria, 2014. / tm2015 / Education Management and Policy Studies / MEd / Unrestricted

In this dissertation, we discuss various aspects of scheduling and resource allocation in multi-user wireless systems. This work starts from how to utilize advanced physical-layer technology to improve the system performance in a multi-user environment. We show that by using superposition coding (SPC) and successive interference cancellation, the system performance can be greatly improved with utility-based scheduling. Several observations are made as the design guideline for such system. Scheduling algorithms are designed for a system with hierarchical modulation which is a practical implementation of SPC. However, when the utility-based scheduling is designed, it is based on the assumption that the system is saturated, {\em i.e.}, users in the system always have data to transmit. It is pointed out in the literature that in a system with stochastic traffic, even if the arrival rate lies inside the capacity region, the system in terms of queue might not be stable with the utility-based scheduling. Motivated by this, we have studied the stability region of a general utility-based scheduling in a multi-user system with stochastic traffic. We show that the stability region is generally less than the capacity region, depends on how to interpret an intermediate control variable, and the resultant stability region may be even non-convex and exhibits undesirable properties which should be avoided. As the utility-based scheduling cannot achieve throughput-optimal, we turn our attentions to the throughput-optimal scheduling algorithms, whose stability region is identical to the capacity region. The limiting properties of an overloaded wireless system with throughput-optimal scheduling algorithms are studied. The results show that the queue length is unstable however the scheduling function of the queue length is stable, and the average throughput of the system converges. Finally we study how to schedule users in a multi-user wireless system with information-theoretic security support, which is focused on the secrecy outage probability. The problem is essentially about how to schedule users, and allocate resources to stabilize the system and minimize the secrecy outage probability. We show that there is a tradeoff between the arrival rate of the traffic and the secrecy outage probability. The relative channel condition of the eavesdropper also plays an important role to the secrecy outage probability. In summary, we showed utility-based scheduling using SPC can improve the system performance greatly, but the utility-based scheduling has limitations: the stability region might not have desired properties. On the contrary throughput-optimal scheduling has its own drawbacks: the traffic cannot be handled properly if the system is overloaded. The further study on the secrecy outage probability gives guideline on how to design a scheduler in a system with information-theoretic security support. / Graduate

The primary objective of this study was to examine changes in resource productivity and factor shares as irrigation was introduced on small rice farms using traditional management techniques. Average output on irrigated farms was double that of dry farms. This was because irrigated farms produced two crops as opposed to one crop on farms without irrigation. Examination of marginal products showed that farmers with irrigation could profitably use more land. Dry farmers could profitably use more labor. The low labor input and high MP of labor on dry farms occurs because these farmers are undercapitalized and are obliged to accept off-farm employment at crucial periods of the rice . growing season. On both farm types, irrigated and dry, factor shares of land were high suggesting that a redistribution of land would also redistribute income. This information provides criteria for formation of rice production policy in Ecuador.

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The American School Counselor Association (ASCA) recommends a shift from traditional to comprehensive, developmental counseling programs focusing on prevention programs to assist the "whole" child (e.g., meeting social, emotional, academic, and career needs). This shift has been slow and inconsistent, bringing great variability to the role of school counselor. This study investigates the current functions of school counselors in Northern Virginia. Five research questions are posed: (1) How do counselors spend their time? (2) In what way do counselors want to change their allocation of time to various counseling activities? (3) How do school counselors feel about their preparation to perform various counseling activities? (4) What factors (work setting, gender, level of education, teaching experience, counseling experience, student-to-counselor ratio, desire to change time allocation, and level of preparation) affect how counselors allocate their time? (5) Do differences exist between school counselors' allocation of time to various counseling activities and the mandate of the Virginia Department of Education? Seventy-three Northern Virginia school counselors (45% response rate) responded to a survey on activities in the four major categories recommended by ASCA (counseling, consulting, guidance, and coordination) and in administrative/support services. Participants also were asked to fill-out a one-day log describing their typical counseling functions on any chosen workday. Results indicated that, on an average, Northern Virginia school counselors feel well prepared to conduct counseling activities and allocate 46% of their time to counseling, 17% to consultation, 12% to guidance, 7% to coordination, and 18% to administrative/support services. Counselors desire to spend more time working with students individually and in small groups, and less time in test coordination and administrative tasks. Statistical analyses (p< .05) indicate that allocation of time was significantly affected by work setting, gender, desire to change present time allocation, and level of preparation. These results suggest that Northern Virginia school counselors in this study are performing the functions recommended by the American School Counselor Association and by the Virginia Department of Education. Implications for future research are explored. / Ph. D.

This dissertation is concerned with the development of algorithmic approaches for solving the minisum location and location-allocation problems in which the Euclidean metric is used to measure distances. To overcome the nondifferentiability difficulty associated with the Euclidean norm function, specialized solution procedures are developed for both the location and the location-allocation problems. For the multifacility location problem (EMFLP), two equivalent convex differentiable reformulations are proposed. The first of these is formulated directly in the primal space, and relationships between its Karush-Kuhn-Tucker (KKT) conditions and the necessary and sufficient optimality conditions for EMFLP are established in order to explore the use of standard convex differentiable nonlinear programming algorithms that are guaranteed to converge to KKT solutions. The second equivalent differentiable formulation is derived via a Lagrangian dual approach based on the optimum of a linear function over a unit ball (circle). For this dual approach, which recovers Francis and Cabot's (1972) dual problem, we also characterize the recovery of primal location decisions, hence settling an issue that has remained open since 1972. In another approach for solving EMFLP, conjugate or deflected subgradient based algorithms along with suitable line-search strategies are proposed. The subgradient deflection method considered is the Average Direction Strategy (ADS) imbedded within the Variable Target Value Method (VTVM). The generation of two types of subgradients that are employed in conjunction with ADS are investigated. The first type is a simple valid subgradient that assigns zero components corresponding to the nondifferentiable terms in the objective function. The second type expends more effort to derive a low-norm member of the subdifferential in order to enhance the prospect of obtaining a descent direction. Furthermore, a Newton-based line-search is also designed and implemented in order to enhance the convergence behavior of the developed algorithm. Various combinations of the above strategies are composed and evaluated on a set of test problems. Computational results for all the proposed algorithmic approaches are presented, using a set of test problems that include some standard problems from the literature. These results exhibit the relative advantages of employing the new proposed procedures. Finally, we study the capacitated Euclidean distance location-allocation problem. There exists no global optimization algorithm that has been developed and tested for this class of problems, aside from a total enumeration approach. We develop a branch-and-bound algorithm that implicitly/partially enumerates the vertices of the feasible region of the transportation constraints in order to determine a global optimum for this nonconvex problem. For deriving lower bounds on node subproblems, a specialized variant of the Reformulation-Linearization Technique (RLT) is suitably designed which transforms the representation of this nonconvex problem from the original defining space into a higher dimensional space associated with a lower bounding (largely linear) convex program. The maximum of the RLT relaxation based lower bound that is obtained via a deflected subgradient strategy applied to a Lagrangian dual formulation of this problem, and another readily computed lower bound in the projected location space is considered at each node of the branch-and-bound tree for fathoming purposes. In addition, certain cut-set inequalities in the allocation space, and objective function based cuts in the location space are generated to further tighten the lower bounding relaxation. Computational experience is provided on a set of randomly generated test problems to investigate both the RLT-based and the projected location- space lower bounding schemes. The results indicate that the proposed global optimization approach for this class of problem offers a promising viable solution procedure. In fact, for two instances available available in the in the literature, we report significantly improved solutions. The dissertation concludes with recommendations for further research for this challenging class of problems. Data for the collection of test problems is provided in the Appendix to facilitate further testing in this area. / Ph. D.

The study of choice and allocation has often focused on certain parameters of reinforcement, but rarely on historical variables. The goal of this study was to investigate the potential effects of gradual vs. abrupt teaching methods on future response allocation. A secondary goal was to see if the results of teaching-method manipulations might be correlated with the parameters that the teaching method produced, specifically unit costs, rate of reinforcement, or error rates. Results indicate that these teaching procedures can produce transient shifts in allocation, but not in a consistent direction. Neither unit cost nor rate or reinforcement alone can account for observed response allocation shifts after training. Researchers saw that subjects reliably shifted towards a manipulanda that produced higher rates of errors, therefore investigating the influence that error rate (or types of errors) may have on response allocation may aid in general teaching method preferences. Future research could focus on the combination of historical procedural variables and current variables that could determine response allocation.