Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (p. 89-95).

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002. / Includes bibliographical references (leaves 126-129). Also available in electronic version. Access restricted to campus users.

Thesis (Ph.D.)--University of Texas at Austin, 2008. / Includes vita. Includes bibliographical references (p. 200-216). Also available online.

by Stanley B. Gershwin and Loren K. Platzman. / "September, 1984." / Bibliography: leaf 4.

Process-oriented organisations need to manage the different types of responsibilities their employees may have w.r.t. the activities involved in their business processes. Despite several approaches provide support for responsibility modelling, in current Business Process Management Systems (BPMS) the only responsibility considered at runtime is the one related to performing the work required for activity completion. Others like accountability or consultation must be implemented by manually adding activities in the executable process model, which is time-consuming and error-prone. In this paper, we address this limitation by enabling current BPMS to execute processes in which people with different responsibilities interact to complete the activities. We introduce a metamodel based on Responsibility Assignment Matrices (RAM) to model the responsibility assignment for each activity, and a flexible template-based mechanism that automatically transforms such information into BPMN elements, which can be interpreted and executed by a BPMS. Thus, our approach does not enforce any specific behaviour for the different responsibilities but new templates can be modelled to specify the interaction that best suits the activity requirements. Furthermore, libraries of templates can be created and reused in different processes. We provide a reference implementation and build a library of templates for a well-known set of responsibilities.

This thesis is dedicated to the problems of gender assignment to English loan words in Italian. The thesis is divided into two parts. In the first, theoretical part, attention is paid to the definition of gender category in Italian, to the rules describing the formation of gender in Italian and then the gender assignment rules for English loan words are presented in detail. The second, analytical part, is dedicated to the research which is carried out via Italian text corpus itWaC. The application of the presented rules for gender assignment is being verified on a sample of English loan words.The aim of the thesis is to introduce the problems of gender assignment to English loan words in Italian, to provide a detailed overview of the individual rules for gender assignment and to verify how much are these rules observed in practice.

In this research, we consider the impact of spectrum fragmentation in optical single-/multi-path routing transmission on the efficiency of the elastic optical networks. O-OFDM multicarrier transmission is a promising technique that makes it possible to choose just an adequate portion of available spectrum to satisfy the requested capacity. This involves focusing on the work to reduce the fragmentation effects by dynamically updating and controlling the minimum bandwidth allocation granularity. that serves the light path requests over multipath networks. We adopt linear and nonlinear dynamic mechanisms, which are denoted as LDAɡ and NLDAɡ that are proportional to the optical link/path bandwidth fragmentation status. Simulation results show that the minimum bandwidth granularity dynamic adaptation based on the optical path fragmentation status offers improved performance over fixed minimum bandwidth allocation granularity with respect to the bandwidth blocking probability, the throughput, the network bandwidth utilization and the number of path splitting.

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

This thesis is concerned with the channel assignment (CA) problem in multi-channel multi-interface wireless mesh networks (M2WNs). First, for M2WNs with general topologies, we rigorously demonstrate using the combinatorial principle of inclusion/exclusion that the CA solution space can be quantified, indicating that its cardinality is greatly influenced by the number of radio interfaces installed on each router. Based on this analysis, a novel scheme is developed to construct a new reduced search space, represented by a lattice structure, that is searched more efficiently for a CA solution. The elements in the reduced lattice-based space, labeled Solution Structures (SS), represent groupings of feasible CA solutions satisfying the radio constraints at each node. Two algorithms are presented for searching the lattice structure. The first is a greedy algorithm that finds a good SS in polynomial time, while the second provides a user-controlled depthfirst search for the optimal SS. The obtained SS is used to construct an unconstrained weighted graph coloring problem which is then solved to satisfy the soft interference constraints. For the special class of full M2WNs (fM2WNs), we show that an optimal CA solution can only be achieved with a certain number of channels; we denote this number as the characteristic channel number and derive upper and lower bounds for that number as a function of the number of radios per router. Furthermore, exact values for the required channels for minimum interference are obtained when certain relations between the number of routers and the radio interfaces in a given fM2WN are satisfied. These bounds are then employed to develop closed-form expressions for the minimum channel interference that achieves the maximum throughput for uniform traffic on all communication links. Accordingly, a polynomial-time algorithm to find a near-optimal solution for the channel assignment problem in fM2WN is developed. Experimental results confirm the obtained theoretical results and demonstrate the performance of the proposed schemes.

Factoring is a financial tool, which allows companies to gain money before the maturity of the invoices issued by them. Factoring can be provided as a regression or non-recourse. The accounting of factoring is based on the form of factoring. Recognition should be fundamentally based on economic substance of transactions rather than the legal status declared for example by contracts. Non-recourse factoring is based on assignment of receivables and regressive factoring is rather receivables management. The issue of accounting for factoring is not yet finally resolved officially.