PREGNANCY-RELATED CHURN AND ACCESS TO CARE IN THE CONTEXT OF NARROW NETWORKS IN WASHINGTON STATE

Thesis (Master's)--University of Washington, 2016-03

Regeneration: the inner city in context

This chapter (12) reviews key publications by Sir Peter Hall in the period 1967-79. In this period he was particularly interested in the 'inner city' and how problems of deprivation, unemployment, poor housing, and increasingly immigration might best be addressed by public policy. Each chapter in the book reviews Sir Peter's publications over a long and distinguished career in research and policy advice to government in honour of his 80th birthday in 2013.

Georg Lukács as a Communications Scholar: Cultural and Digital Labour in the Context of Lukács’ Ontology of Social Being

The task of this work is to apply thoughts from Georg Lukács’ final book, the Ontology of Social Being, for the theoretical analysis of cultural and digital labour. It discusses Lukács’ concepts of work and communication and relates them to the analysis of cultural and digital work. It also analyses his conception of the relation of labour and ideology and points out how we can make use of it for critically understanding social media ideologies. Lukács opposes the dualist separation of the realms of work and ideas. He introduces in this context the notion of teleological positing that allows us to better understand cultural and digital labour as well as associated ideologies, such as the engaging/connecting/sharing-ideology, today. The analysis shows that Lukács’ Ontology is in the age of Facebook, YouTube, and Twitter still a very relevant book, although it has thus far not received the attention that it deserves. This article also introduces the Ontology’s main ideas on work and culture, which is important because large parts of the book have not been translated from the German original into English. Lukács’ notion of teleological positing is crucial for understanding the common features of the economy and culture.

Context-aware Approach for Determining the Threshold Price in Name-Your-Own-Price Channels

Key feature of a context-aware application is the ability to adapt based on the change of context. Two approaches that are widely used in this regard are the context-action pair mapping where developers match an action to execute for a particular context change and the adaptive learning where a context-aware application refines its action over time based on the preceding action’s outcome. Both these approaches have limitation which makes them unsuitable in situations where a context-aware application has to deal with unknown context changes. In this paper we propose a framework where adaptation is carried out via concurrent multi-action evaluation of a dynamically created action space. This dynamic creation of the action space eliminates the need for relying on the developers to create context-action pairs and the concurrent multi-action evaluation reduces the adaptation time as opposed to the iterative approach used by adaptive learning techniques. Using our reference implementation of the framework we show how it could be used to dynamically determine the threshold price in an e-commerce system which uses the name-your-own-price (NYOP) strategy.

A Social Institutionalist Perspective on HR Diffusion: Histrorical and Cultural Receptivity to HRM in a Post-Comminist Context

This research considers cross-national diffusion of international human resource management (IHRM) ideas and practices by applying an emergent frame of sociological conceptualisation – ‘social institutionalism’ (SI). We look at cultural filters to patterns of diffusion, assimilation and adoption of IHRM, using Romania as a case study. The paper considers the former Communist system of employment relations, suggesting that through institutionalisation former ways of thinking continued to influence definitions and practice of people management in post-Communist Eastern Europe. The paper provides a new perspective on HRM by discussing the value of SI as a general model for understanding cross-cultural receptivity to HR ideas, sensitising the HR practitioner and academic to institutionalised culture as a historical legacy influencing receptivity to international management ideas.

Teacher educators: proposing new professional development models within an English further education context

At a time of increasing public and government focus on the quality of teacher education, little is known about the professional development needs of those who teach teachers in further education (FE). Yet they are crucial players. Efforts are intensifying across a significant number of countries to promote the professional development of teacher educators, but there is little support for new or experienced practitioners and no substantive professional standards regarding this role in English FE. This has an impact on the professional practice and career trajectories of teacher educators themselves. Based on a series of semi-structured interviews, an online survey and focus groups, this mixed-methods study uses a sequential exploratory design. The study captures the voices of English FE teacher educators who identified mentoring, induction and a choice of continuous professional development sessions as important strategies to improve the effectiveness of their role over time. This article will propose flexible models of professional development, following an analysis of new and experienced teacher educators’ needs in FE in England. The article recommends that new professional standards for teacher educators could be written collaboratively by practitioners, within a policy and institutional framework which supports the scholarship and research requirements of teacher educators.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Remuneration and tariffs in the context of virtual power players

Power systems have been through deep changes in recent years, namely with the operation of competitive electricity markets in the scope and the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new player type which allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles, (V2G) and consumers), to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players` benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.