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"The fast pace of global urbanization is drastically changing the population distributions over the world, which leads to significant changes in geographical population densities. Such changes in turn alter the underlying geographical power demand over time, and drive power substations to become over-supplied (demand ≪ capacity) or under-supplied (demand ≈ capacity). In this work, we make the first attempt to investigate the problem of power substation/user assignment by analyzing large scale power grid data. We develop a Scalable Power User Assignment (SPUA) framework, that takes large-scale spatial power user/substation distribution data and temporal user power consumption data as input, and assigns users to substations, in a manner that minimizes the maximum substation utilization among all substations. To evaluate the performance of SPUA framework, we conduct evaluations on real power consumption data and user/substation location data collected from Xinjiang Province in China for 35 days in 2015. The evaluation results demonstrate that our SPUA framework can achieve a 20%–65% reduction on the maximum substation utilization, and 2 to 3.7 times reduction on total transmission loss over other baseline methods."

The assignment of grammatical gender in German is a notoriously problematic phenomenon due to the apparent opacity of the gender assignment system (e.g. Comrie 1999: 461). Various models of German gender assignment have been proposed (e.g. Spitz 1965, Köpcke 1982, Corbett 1991, Wegener 1995), but none of these is able to account for all of the German data. This thesis investigates a relatively under-explored, recent approach to German gender assignment in the form of Optimal Gender Assignment Theory (OGAT), proposed by Rice (2006). Using the framework of Optimality Theory, OGAT claims that the form and meaning of a noun are of equal importance with respect to its gender. This is formally represented by the crucial equal ranking of all gender assignment constraints in a block of gender features, which is in turn ranked above a default markedness hierarchy *NEUTER » *FEMININE » *MASCULINE, which is based on category size. A key weakness of OGAT is that it does not specify what constitutes a valid gender features constraint. This means that, in theory, any constraint can be proposed ad hoc to ensure that an OGAT analysis yields the correct result. In order to prevent any constraints based on 'postfactum rationalisations' (Comrie 1999: 461) from being included in the investigation, the gender features constraints which have been proposed in the literature for German are assessed according to six criteria suggested by Enger (2009), which seek to determine whether there is independent evidence for a gender features constraint. Using an independently-verified constraint set, OGAT is then tested on a sample of 592 nouns systematically selected from the Duden Rechtschreibung. The results indicate that OGAT is relatively successful in its predictions when compared to other approaches but that it cannot account fully for the sample data. Accordingly, a revised version of the theory is proposed (OGAT II), which involves the ranking of certain gender features constraints. It is found that OGAT II is able to account for the genders of around 95% of nouns in the sample. A number of specific aspects of OGAT II are then tested by means of an experiment in which native German speakers are required to assign genders to 26 pseudo-nouns. The results suggest that OGAT II comes the closest of the systems discussed in the literature to modelling how native speakers assign gender in German.

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Along with process technology advancement, we can integrate more and more on-chip memory in an SOC. Memory intensive applications, such as image processing and digital signal processing, usually access certain number of data arrays. Memory system designs for such systems can then critically influence cost, performance, and power of the resulting SOCs. In this thesis research, we focus on the software design of a memory synthesis method of data stored in arrays. Memory synthesis task considers access time, power, and cost requirements of array data and utilize characteristics of indexing patterns of array accesses. It then derive the allocation of memory organizations and effective organizations of multiple data arrays mapped onto the allocated memory modules. Its design principle lies in the matching of data array reorganization and their assigned memory module resource allocation so as to enhance data access locality in the same memory rows and to reduce the number of row accesses (bit line accesses). Hence, we can achieve required power and performance goals with low memory system cost. Static memory synthesis solves memory synthesis problem with fixed loop count and tasks in prior of product design. The memory synthesis task succeeds the high level synthesis task. It is then followed by the address generating circuit design task and the memory access scheduling circuit design task of the functional module side. These circuit designs can herein be combined with high level synthesis results to perform logic synthesis. Finally, we can perform physical synthesis of functional modules, logic circuit modules, and memory modules. It is thus expected to produce an SOC design satisfying overall design requirements. The software design of the static memory synthesis method includes two main topics: memory allocation and module assignment for data arrays and the estimation method of a memory system design. In this research, we designed the experimental software for the memory synthesis method. We also planned experiments based upon real and synthetic design cases to validate the effectiveness of the static memory synthesis method.

Thesis (M.S. in C.S.)--College of Computing, Georgia Institute of Technology, 2004. Directed by Santosh Pande. / Includes bibliographical references (leaves 73-74).

Autonomous vehicles (AVs) may soon be publicly available and are expected to increase both network capacity and travel demand. Reduced safety margins from computer precision may increase network capacity and allow for more efficient intersection controls. AVs also offer the option of repositioning trips to avoid parking fees or share the vehicle between household members, which may increase the total number of vehicle trips and decrease the relative utility of transit. Since AVs may be available within one or two decades, which is within the span of long-term planning models, practitioners may soon wish to predict the effects of AVs on traffic networks. This thesis modifies the four-step planning model commonly used by practitioners to include AV behaviors and capacity improvements. Because dynamic traffic assignment (DTA) offers more realistic flow propagation and intersection control options, the four-step model is modified to incorporate DTA with endogenous departure time choices. To facilitate modeling of AV intersections, the tile-based reservation (TBR) control policy is simplified into a conflict region (CR) model compatible with general simulation-based DTA and with greatly improved computational tractability. Results suggest that although the total number of personal-vehicle trips may almost double (due to repositioning trips to the origin to avoid parking costs), increases in network and intersection capacity can mostly offset or even improve network conditions. Use of dynamic flow propagation instead of static travel time functions in the four-step model results in predictions of increased average travel speed although both static and dynamic planning models predict a high reliance on repositioning trips (i.e., empty-vehicle travel). To study AV behaviors in DTA, this thesis first integrates DTA into the four-step model with the addition of departure time choice. This model alone may be useful for practitioners as departure time modeling is a major concern with DTA planning models. Also, the TBR intersection policy has only been studied in micro-simulation with heuristic routing strategies. The CR model opens this new technique to study under UE behavior, which is the first step for the bridge between technology demonstration simulations to models practitioners can use to evaluate implementation. . Therefore, the models developed here for the purposes of predicting AV trip and mode choices may themselves become useful tools for other applications. / text

Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

In the Department of Pathology and Laboratory Medicine, at the beginning of each month, the clinical managers use expert knowledge to assign pathologists to expected daily specimens based on the criteria of workload restrictions, clinical sub-specialties, and availability. Since the size of the pathologists’ assignment problem is large, finding a feasible assignment manually is a very time-consuming process that takes a number of iterations over a number of days to complete. Moreover, every time there is a need to make a revision, a new assignment needs to be developed taking into account all the above criteria. The goal of this research is to develop an optimization model and a decision support tool that will help with monthly staffing of pathologists based on the criteria outlined above. The developed model is rooted in the classical operations research assignment problem and it is extended to account for the following requirements: each pathologist should be assigned to a similar specimen type throughout a week; for a given pathologist, there should be a rotation of the specimen types between the weeks; and the clinical managers’ preferences in terms of assigning a particular specimen type to a particular pathologist on a specific day need to be considered. A monthly assignment model covering 36 pathologists and 26 specimen types was solved using IBM ILOG CPLEX Optimization Studio. It is embedded in a decision support tool that helps clinical managers to make staffing decisions. The decision support tool has been validated using data from The Ottawa Hospital (TOH).

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