Current research on network use in the labor market focuses primarily on network morphology. In this dissertation, I use hierarchical regression to examine the influence of macro-level context on network use in job search.This study relies on a unique data set that combines individual job history data for years 1985 through 2001 collected by the Survey of Social Dynamics and Migration in Russia (SSMDR) in 40 regions in 2001-2002 and corresponding regional macro-economic data published by Goskomstat, the State Statistical Committee of the Russian Federation.The first question of this study focuses on what accounts for the temporal and regional variation in personal network use in the Russian labor market. I find that, for the post-Soviet period, increase in network use in job search can be attributed to the growth of the private sector: Russian employers are becoming "social capitalists" who take advantage of the resources personal connections can offer. I also find that the chances of finding a new job through personal ties are higher in the regions with larger small business sectors and in the regions with lower economic performance.Next I examine how regional economic performance and unemployment affect workers' chances of getting new jobs in the private sector and in smaller size organizations by means of personal networks. The analysis shows that social networks do lead to employment in the private sector and that this relationship is positively affected by regional economic performance, but not by unemployment rate. I also find here that social ties are likely to lead to new jobs in small organizations, but that this relationship does not vary by region.Finally, I investigate how regional economic performance and unemployment rates affect wages for jobs found through personal networks in the private sector and in small organizations. I find that while the private sector rewards network use, small organizations do not. The relationship between network use and wages does not vary by region. That is, regional economic performance does not have an effect on this relationship.

Hierarchical task decompositions play an essential role in the design of complex simulation and decision systems, such as the ones that arise in video games. Game designers find it very natural to adopt a divide-and-conquer philosophy of specifying hierarchical policies, where decision modules can be constructed somewhat independently. The process of choosing the parameters of these modules manually is typically lengthy and tedious. The hierarchical reinforcement learning (HRL) field has produced elegant ways of decomposing policies and value functions using semi-Markov decision processes. However, there is still a lack of demonstrations in larger nonlinear systems with discrete and continuous variables. To narrow this gap between industrial practices and academic ideas, we address the problem of designing efficient algorithms to facilitate the deployment of HRL ideas in more realistic settings. In particular, we propose Bayesian active learning methods to learn the relevant aspects of either policies or value functions by focusing on the most relevant parts of the parameter and state spaces respectively. To demonstrate the scalability of our solution, we have applied it to The Open Racing Car Simulator (TORCS), a 3D game engine that implements complex vehicle dynamics. The environment is a large topological map roughly based on downtown Vancouver, British Columbia. Higher level abstract tasks are also learned in this process using a model-based extension of the MAXQ algorithm. Our solution demonstrates how HRL can be scaled to large applications with complex, discrete and continuous non-linear dynamics.

The choice of firm boundaries is one of the most fundamental elements of organizational strategy. It determines industry positioning, enables the development and leverage of distinctive capabilities, and ultimately establishes the basis for sustainable competitive advantage. In the modern economy, organizational unbundling and vertical disintegration has become a recurrent theme across many industries, reflecting a major transformation in industrial organization and firm strategy. What are the drivers of this modern trend of vertical disintegration? How do we reconcile this modern phenomenon with the vertical integration logic of previous decades? Beginning with Transaction Cost Economics (TCE) as the underlying framework, we draw from the Information Processing, Coordination and Capabilities literatures to develop an integrated theoretical framework for examining and rationalizing the determinants of vertical disintegration. The recent restructuring of the US electric utility industry provides a suitable empirical context to undertake a rigorous examination of this theoretical framework: a context that manifests institutional heterogeneity, high levels of uncertainty, intense coordination requirements, and a variety of competing market and organizational institutions in transition. We employ multi-level modeling techniques, to account for firm heterogeneity and time-variant institutional parameters in our longitudinal panel data, thus allowing for a richer analysis of institutional effects. The results show that there has been systematic vertical disintegration in the electric utility industry over the period of study, 1994-2002, influenced by both firm-level and state/federal-level institutional factors as well as structural market attributes, which serve as proxies for demand and supply uncertainty. Using IT investment intensity as a proxy for firm-level IT Capability, we also established an overall significant negative effect of IT on vertical integration, consistent with previous studies about the effects of IT on firm size. The main findings confirmed several standard TCE propositions, and also address several known shortcomings, most notably the ambiguity in the treatment of uncertainty. In addition, the robust examination of the empirical evidence associated with the restructuring of the Electric Utility industry allowed us to isolate the relative effects of various institutional mechanisms and structural market attributes. These findings help to illuminate the understanding and ultimately the programming of deregulation effects.

Current deficits in the rehabilitation psychology literature involving longitudinal studies investigating positive outcomes following acquired disabilities have deserved research attention. In the current study, data on happiness as an enduring mood tone, as measured by the Life Satisfaction Index (LSI) was collected from 1271 individuals (“insiders”) having incurred either a traumatic brain injury (TBI), spinal cord injury (SCI), severe burn, or intra-articular fracture (IAF) or from someone who felt close enough to speak on their behalf (“outsiders”). Data on happiness, functional independence as measured by the Functional Independence Measure (FIM), and other variables of interest were collected at 12 months, 24 months, 48 months, and 60 months after being medically discharged. Hierarchical Linear Modeling (HLM) analyses showed that trajectories of happiness remained stable across participants and did not change significantly over five years post-discharge regardless of injury type, FIM, or insider/outsider status. Happiness was significantly predicted by FIM, injury type, and whether the respondent was an insider or outsider. Those who were more impaired and less functionally independent were less happy. Those with a TBI were consistently less happy than those with an IAF or SCI and outsiders reported greater happiness on behalf of the insider than did the insiders themselves. This study shows that there is stability in happiness levels that can be sustained at least five years post-discharge and that there are discrepancies between insider and outsider reports of subjective happiness. Proxy reports can be used as valuable and valid secondary sources of information but should not be used as substitutes for first hand reports unless absolutely necessary.

The need to compactly represent 3D data is motivated by the ever-increasing size of these data. Furthermore, for large data sets it is useful to randomly access and process a small part of the data. In this thesis we propose two methods of compactly representing 3D data while allowing random access. The first is the multiresolution sphere-packing tree (MSP-tree). The MSP-tree is a multiresolution 3D hierarchy on regular grids based on sphere-packing arrangements. The grids of the MSP-tree compactly represent underlying point-sampled data by using more efficient grids than existing methods while maintaining high granularity and a hierarchical structure that allows random access. The second is distance-ranked random-accessible mesh compression (DR-RAMC). DR-RAMC is a lossless simplicial mesh compressor that allows random access and decompression of the mesh data based on a spatial region-of-interest. DR-RAMC encodes connectivity based on relative proximity of vertices to each other and organizes both this proximity data and vertex coordinates using a k-d tree. DR-RAMC is insensitive to a variety of topological mesh problems (e.g. holes, handles, non-orientability) and can compress simplicial meshes of any dimension embedded in spaces of any dimension. Testing of DR-RAMC shows competitive compression rates for triangle meshes and first-ever random accessible compression rates for tetrahedral meshes. / Thesis (Ph.D, Computing) -- Queen's University, 2012-07-17 15:28:39.406

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In this thesis we propose a technique to preserve the temporal properties of realtime components during their integration and reuse. We propose a new concept of runnable virtual node which is a coarse-grained real-time component that provides functional and temporal isolation with respect to its environment. A virtual node’s interaction with the environment is bounded by both a functional and a temporal interface, and the validity of its internal temporal behaviour is preserved when integrated with other components or when reused in a new environment.   The first major contribution of this thesis is the implementation of a Hierarchical Scheduling Framework (HSF) on an open source real-time operating system (FreeRTOS) with the emphasis of doing minimal changes to the underlying FreeRTOS kernel and keeping its API intact to support the temporal isolation between a numbers of applications, on a single processor. Temporal isolation between the components during runtime prevents failure propagation between different components.   The second contribution of the thesis is with respect to the integration of components, where we first illustrate how the concept of the runnable virtual node can be integrated in several component technologies and, secondly, we perform a proof-of-concept case study for the ProCom component technology where we demonstrate the runnable virtual node’s real-time properties for temporal isolations and reusability.   We have performed experimental evaluations on EVK1100 AVR based 32-bit micro-controller and have checked the system behaviour during heavy-load and over-load situations by visualizing execution traces in both hierarchical scheduling and virtual node contexts. The results for the case study demonstrate temporal error containment within a runnable virtual node as well as reuse of the node in a new environment without altering its temporal behaviour. / PROGRESS

The objective of modeling, verification, and synthesis of hierarchical hybrid mission control for underwater vehicle is to (i) propose a hierarchical architecture for mission control for an autonomous system, (ii) develop extended hybrid state machine models for the mission control, (iii) use these models to verify for logical correctness, (iv) check the feasibility of a simulation software to model the mission executed by an autonomous underwater vehicle (AUV) (v) perform synthesis of high-level mission coordinators for coordinating lower-level mission controllers in accordance with the given mission, and (vi) suggest further design changes for improvement. The dissertation describes a hierarchical architecture in which mission level controllers based on hybrid systems theory have been, and are being developed using a hybrid systems design tool that allows graphical design, iterative redesign, and code generation for rapid deployment onto the target platform. The goal is to support current and future autonomous underwater vehicle (AUV) programs to meet evolving requirements and capabilities. While the tool facilitates rapid redesign and deployment, it is crucial to include safety and performance verification into each step of the (re)design process. To this end, the modeling of the hierarchical hybrid mission controller is formalized to facilitate the use of available tools and newly developed methods for formal verification of safety and performance specifications. A hierarchical hybrid architecture for mission control of autonomous systems with application to AUVs is proposed and a theoretical framework for the models that make up the architecture is outlined. An underwater vehicle like any other autonomous system is a hybrid system, as the dynamics of the vehicle as well as its vehicle level control is continuous whereas the mission level control is discrete, making the overall system a hybrid system i.e., one possessing both continuous and discrete states. The hybrid state machine models of the mission controller modules is derived from their implementation done using TEJA, a software for representing hybrid systems with support for auto code generation. The verification of their logical correctness properties has been done using UPPAAL, a software tool for verification of timed automata a special kind of hybrid system. A Teja to Uppaal converter, called dem2xml, has been created at Applied Reserarch Lab that converts a hybrid (timed) autonomous system description in Teja to an Uppaal system description. Verification work involved developing abstract models for the lower level vehicle controllers with which the mission controller modules interact and follow a hierarchical approach: Assuming the correctness of level-zero or vehicle controllers, we establish the correctness of level-one mission controller modules, and then the correctness of level-two modules, etc. The goal of verification is to show that any valid meaning for a mission formalized in our research verifies the safe and correct execution of actions. Simulation of the sequence of actions executed for each of the operations give a better view of the combined working of the mission coordinators and the low level controllers. So we next looked into the feasibility of simulating the operations executed during a mission. A Perl program has been developed to convert the UPPAAL files in .xml format to OpenGL graphic files. The graphic files simulate the steps involved in the execution of a sequence of operations executed by an AUV. The highest level coordinators send mission orders to be executed by the lower level controllers. So a more generalized design of the highest level controllers would help to incorporate the execution of a variety of missions for a vast field of applications. Initially, we consider manually synthesized mission coordinator modules. Later we design automated synthesis of coordinators. This method synthesizes mission coordinators which coordinate the lower level controllers for the execution of the missions ordered and can be used for any autonomous system.

Minicell-based manufacturing system is used in identifying best minicell designs. The existing method of minicell design generates best minicell designs by designing and scheduling minicells simultaneously. While in this research designing of minicells and scheduling of jobs in minicells is done separately. This research evaluates the effectiveness of hierarchical approach and compares with simultaneous method. Minicell designs with respect to average flow times and machine capacities and both are identified in a multi-stage flow shop environment. Rules for the extraction of good minicell designs in mass customization manufacturing systems are also established.