In today's advanced technology world, enterprises are in a constant state of competition. As the intensity of competition increases the need to continuously improve organizational performance has never been greater. Managers at all levels must be on a constant quest for finding ways to maximize their enterprises' strategic resources. Enterprises can develop sustained competitiveness only if their activities create value in unique ways. There should be an emphasis to transfer this competitiveness to the resources it has on hand and the resources it can develop to be used in this environment. The significance of human capital is even greater now, as the intangible value and the tacit knowledge of enterprises' resources should be strategically managed to achieve a greater level of continuous organizational success. This research effort seeks to provide managers with means for accurate decision making for their workforce management. A framework for modeling and managing human capital to achieve effective workforce planning strategies is built to assist enterprise in their long term strategic organizational goals.

This dissertation consists of three articles about colorism and its relevance to public administration (PA), with specific focus on local policing. The overarching arguments are: 1) our lack of focus on the nuanced factors related to race have hindered our ability to adequately respond to biased criminal justice (CJ) outcomes; and 2) there are hidden patterns of biased behaviors that originate at the street-level, and these patterns have the propensity to impact every aspect of CJ. Colorism could serve as a more comprehensive approach to addressing racial bias. Colorism is a system of disadvantage and privilege based on skin color, with a bias for lighter skin. Article I introduces colorism to the field of PA, and it uses data on workplace colorism complaints to illustrate how colorism currently intersects with PA. In addition, the article uses scenarios to demonstrate the potential impact colorism might have at the street-level. Article II builds upon the descriptions of colorism provided in Article I by simulating a conceptual model of colorism and local policing. The major finding of this study is that, counter to the expectations of the experiment, those in the middle of the skin color spectrum experienced higher rates of incarceration when aggressive steps were taken to counter colorism. The major contributions from this project include a conceptual model that describes the relationship between the distinct levels of colorism�"individual, interactive and institutional. In Article III, I explore two conceptual models of interactive colorism in a local policing context. In the first model, bias behaviors are less likely to receive a challenge. In the second model, biased behaviors are likely to be challenged by counter-behaviors (e.g., fair policing). Subject-matter experts and non-subject-matter experts were used to select the model that most accurately depicts the phenomenon. I used online focus groups and phone interviews with police officers, theorists (e.g., sociologists, psychologists), and non-subject-matter experts to gather feedback. Majority of the informants recommended that future research on interactive colorism be framed as a bidirectional phenomenon. The informants provided additional considerations for future research, such as the variation in police culture across police departments. / PHD

Yes / Membrane computing is a new natural computing paradigm inspired by the functioning and structure of biological cells, and has been successfully applied to many different areas, from biology to engineering. In this paper, we present kPWorkbench, a software framework developed to support membrane computing and its applications. kPWorkbench offers unique features, including modelling, simulation, agent-based high performance simulation and verification, which allow modelling and computational analysis of membrane systems. The kPWorkbench formal verification component provides the opportunity to analyse the behaviour of a model and validate that important system requirements are met and certain behaviours are observed. The platform also features a property language based on natural language statements to facilitate property specification. / EPSRC

The key objectives of this research were to develop an integrated design and analysis methodology for sheet-metal product development based on agent-based technology, feature-based design, optimization and finite element analysis techniques, and to study the performance of prototype systems developed based on such a methodology. To achieve the research objectives, an agent-based framework was proposed for integrating and coordinating activities of participants involved in sheet-metal product development based on the investigation of the industrial requirements and the procedures of the development of sheet-metal products. Prototype systems were developed based on the proposed framework to answer research problems outlined for the design and implementation of agent-based systems, such as agent encapsulation, system architecture, agent communication and agent coordination. The performance of such prototype systems demonstrates that communication and coordination among domain agents can facilitate product development and reduce product cost. An agent-based optimization approach based on an "A-Teams" approach (Talukdar et al, 1996) was proposed for process optimization in the tooling design stage to combine the utilization of the traditional optimization techniques used to solve sheet-metal forming problems and agent-based approaches. Three test cases were used of varying complexity from a rectangular cup to the NUMISHEET'99 automobile front door panel simulation benchmark for the determination of optimal drawbead restraining forces and blankholder forces when designing draw dies for stamped parts. A network of software agents, each implementing a different numerical optimization technique, was used in combination with metal forming simulation software to optimize process variables. It was found that the performance of each agent (and optimization technique) depended strongly on the complexity of the problem. For a given amount of computational effort, a network of collaborating agents using different optimization techniques always outperformed agents using a single technique in terms of both the best solution found and the variance of the collection of best solutions. To provide guidance for the design and implementation of real applications, static and dynamic attributes and metrics of such agent-based collaborative systems, which can be evaluated in the preliminary system design stage and the system implementation stage, were proposed to study the impact of system architectures and coordination strategies on system performance. In addition, real-time system performance was statistically studied based on the data collected by the visualiser agent generated with the agent building toolkit. The results of case studies for system performance evaluation demonstrate the applicability of evaluation strategies proposed and can be used as a reference model for performance and scalability analysis on agent-based sheet-metal product development systems. The proposed evaluation strategies are applicable to general applications for product development by taking into consideration other performance indicators. / Thesis / Doctor of Philosophy (PhD)

We are recently witnessing an increase in large-scale micro/individual/- granular level behavioural data. Such data has been proven to have the capacity to aid the development of more accurate simulations that will ef- fectively predict the behaviours of complex systems. Despite this increase, the literature has failed to produce a structured modelling approach that will effectively take advantage of such granular data, in modelling com- plex systems that involve social phenomenons (i.e. social complex sys- tems). In this thesis, we intend to bridge this gap by answering the question of how novel structural frameworks, that systematically guides the use of micro-level behaviour and attribute data, directly extracted from the ba- sic entities within a social complex system can be created. These frame- works should involve the systematic processes of using such data to di- rectly model agent attributes, and to create agent behaviour rules, that will directly represent the unique micro entities from which the data was ex- tracted. The objective of the thesis is to define generic frameworks, that would create agent based micro simulations that would directly reflect the target complex system, so that alternative scenarios, that cannot be inves- tigated in the real system, and social policies that need to be investigated before being applied on the social system can be explored. In answering this question, we take advantage of the pros of other model- ing techniques such as micro simulation and agent based techniques in cre- ating models that have a micro-macro link, such that the micro behaviour that causes the macro emergence at the simulation’s global level can be easily investigated. which is a huge advantage in policy testing. We also utilized machine learning in the creation of behavioural rules.This created agent behaviours that were empirically defined. Therefore, this thesis also answers the question of how such structural framework will empirically create agent behaviour rules through machine learning algorithms. In this thesis we proposed two novel frameworks for the creation of more accurate simulations. The concepts within these frameworks were proved using case studies, in which these case studies where from different so- cial complex systems, so as to prove the generic nature of the proposed frameworks. In concluding of this thesis, it was obvious that the questions posed in the first chapter had been answered. The generic frameworks had been created, which bridged the existing gap in the creation of accurate mod- els from the presently available granular attribute and behavioral data, al- lowing the simulations created from these models accurately reflect their target social complex systems from which the data was extracted from.

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