This thesis considers three physician scheduling problems in health care systems. Specifically, we focus on improvements to current physician scheduling practices through the use of mathematical modeling. In the first part of the thesis, we present a physician shift scheduling problem focusing on maximizing continuity of care (i.e., ensuring that patients are familiar with their treating physicians, and vice versa). We develop an objective scoring method for measuring the continuity of a physician schedule and combine it with a mixed integer programming model. We apply our methods to the problem faced in the pediatric intensive care unit at Children's Healthcare of Atlanta at Egleston, and show that our schedule generation approach outperforms manual methods for schedule construction, both with regards to solution time and continuity. The next topic presented in this thesis focuses on two scheduling problems: (i) the assignment of residents to rotations over a one-year period, and given that assignment, (ii) the scheduling of residents' night and weekend shifts. We present an integer programming model for the assignment of residents to rotations such that residents of the same type receive similar educational experiences. We allow for flexible input of parameters and varying groups of residents and rotations without needing to alter the model constraints. We present a simple model for scheduling 1st-year residents to night and weekend shifts. We apply these approaches to problems faced in the Department of Surgery Residency Program at Emory University School of Medicine. Rotation assignment is made more efficient through automated schedule generation, and the shift scheduling model allows us to highlight infeasibilities that occur when shift lengths exceed a certain value, and we discuss the impact of duty hour restrictions under limitations of current scheduling practices. The final topic of this thesis focuses on the assignment of physicians to various tasks while promoting equity of assignments and maximizing space utilization. We present an integer programming model to solve this problem, and we apply this model to the physician scheduling problem faced in the Department of Gynecology and Obstetrics at Emory University Hospital and generate high quality solutions very quickly.

International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / NASA's Space Network (SN) provides both single access (SA) and multiple access (MA) services through a pre-scheduling system. Currently, a user's spacecraft is incapable of receiving service unless prior scheduling occurred with the control center. NASA is interested in efficiently utilizing the time between scheduled services. Thus, a demand assignment multiple access (DAMA) service study was conducted to provide a solution. The DAMA service would allow the user's spacecraft to initiate a service request. The control center could then schedule the next available time slot upon owner approval. In this paper, the basic DAMA service request design and integration is presented.

This study reports on investigation of ways of improving the breeding programme for growth-related traits in common carp in Vietnam. The base population was synthesized following a single pair mating scheme from six carp stocks: (1) 2nd generation of family selection; (2) Hungarian 6th generation of mass selection; (3) Hungarian scaled carp; (4) Indonesian yellow 6th generation of mass selection; (5) Indonesian yellow carp; and (6) Vietnamese 6th generation of mass selection. The next two selected generations were produced using a partial factorial mating scheme, with each family being split and reared using communal early rearing (CER) or separate early rearing (SER) methods. The second generation (G2) was produced from selected fish from the CER G1 group. The total number of selection, control and reference families was 135 in the G1 and 101 in the G2 respectively. The control and reference (Hungarian P33 line) families were produced by single pair mating (reference families with the G2 only). Seven microsatellite loci were used for parentage assignment in the CER groups: 96.8% of the offspring (1284 individuals) and 96.2% offspring (1341 individuals) were unambiguously assigned to 113 families (selection, control) in the G1 and 99 families (selection, control and reference) in the G2 generations, respectively. Restricted maximum likelihood in the individual model was used to estimate phenotypic and genetic parameters. In CER, the estimated heritability values of common carp were from 0.20 ± 0.04 to 0.29 ± 0.05 for both weight and length at final harvest, indicating substantial additive genetic variation for selection on growth-related traits. The overall obtained maternal and common environmental effects were consistently close to zero. The average of direct response to selection for body weight was 15.0% per generation. In SER, the number of families in the G1 and G2 were 135 (selection and control) and 101 (selection, control and reference), respectively. The heritability estimates were from 0.20 ± 0.07 to 0.31 ± 0.08 at final measurement. Common environmental (full-sib family) effect were all lower at tagging and slightly higher at last measurement, ranging from 0.05 to 0.22. The response in each generation of selection as the difference between the selection and control lines was 8.1% on average for weight at final harvest, lower than under CER. The high genetic correlations of growth-related traits between the third (one year old, mature) and second (7 months old) measurements could allow selection to be based on the earlier assessment, reducing handling stress close to spawning. The benefits of using microsatellite markers to ascertain parentage, achieve greater growth rate (close to farming systems), shorten time to maturity and selection, and the overall relative merits of using CER v’s SER in this genetic improvement programme are discussed.

Energy consumption is increasingly affecting battery life and cooling for real- time systems. Dynamic Voltage and frequency Scaling (DVS) has been shown to substantially reduce the energy consumption of uniprocessor real-time systems. It is worthwhile to extend the efficient DVS scheduling algorithms to distributed system with dependent tasks. The dissertation describes how to extend several effective uniprocessor DVS schedul- ing algorithms to distributed system with dependent task set. Task assignment and deadline assignment heuristics are proposed and compared with existing heuristics concerning energy-conserving performance. An admission test and a deadline com- putation algorithm are presented in the dissertation for dynamic task set to accept the arriving task in a DVS scheduled real-time system. Simulations show that an effective distributed DVS scheduling is capable of saving as much as 89% of energy that would be consumed without using DVS scheduling. It is also shown that task assignment and deadline assignment affect the energy- conserving performance of DVS scheduling algorithms. For some aggressive DVS scheduling algorithms, however, the effect of task assignment is negligible. The ad- mission test accept over 80% of tasks that can be accepted by a non-DVS scheduler to a DVS scheduled real-time system.

The enzyme nitroreductase (NR) catalyzes two-electron reduction of high explosives such as trinitrotoluene (TNT), a wide variety of other toxic nitroaromatic compounds, as well as riboflavin derivatives, using a tightly-bound flavin mononucleotide (FMN) cofactor. It has important environmental and clinical implications. Previous studies have focused on elucidating NRs catalytic mechanism and solving its crystal structure. In this dissertation work, we first develop and implement new strategies for labeling NR with stable isotopes, and report a completely re-designed protocol for NRs purification. Then we report the successful assignment of over half of NRs backbone resonances using 3d-NMR methods. The most significant observation is that we find a well-resolved 2d 1H-15N HSQC NMR spectrum is obtained at 37°C for NR, while the HSQC at 4°C is poorly-dispersed and comprised of sharp overlapped peaks. Thus, it would appear that NR denatures at 4°C. However, as we demonstrate, the non-covalently-bound FMN cofactor is not released at the lower temperature, based on retention of the native flavin visible-CD spectrum. Similarly, far-UV CD spectroscopy shows that the protein retains full secondary structural content at 4C. In addition, near-UV CD and Fluorine-19 NMR experiments demonstrate that under completely native conditions (neutral pH, no additives) NR maintains a high degree of tertiary structure and well-defined hydrophobic side-chain packing, ruling out the possibility of a molten-globule state. Thus, our studies report strong evidence that the dramatic low-temperature (low-T) transition near 20°C observed by NMR is not the result of protein structural changes, but rather, we propose that NR exists as an ensemble of rapidly inter-converting structures, at lower temperature, only adopting a well-defined unique structure above 20°C. Both saturation-transfer from water and solvent proton-exchange measurements support our proposed model in which the unique high-T structure is favored entropically, by release of water molecules; on the other hand, the fluxional low-T state incorporates greater water solvation at 4°C. In the latter part of this study, we present preliminary data suggesting that the flexibility implied by easy water-access to the loosely-structured state plays a role in accommodating binding of diverse substrates. Therefore, the fluxional low-T state may be functionally important. A possible direct link between the enzyme dynamics and its catalytic activity will be an area of future investigation.

Transportation planning and urban development in the United States have synchronously emerged over the past few decades to encompass goals associated with sustainability, improved connectivity, complete streets and mitigation of environmental impacts. These goals have evolved in tandem with some of the relatively more traditional objectives of supply-side improvements such as infrastructure and capacity expansion. Apart from the numerous federal regulations in the US transportation sector that reassert sustainability motivations, metropolitan planning organizations and civic societies face similar concerns in their decision-making and policy implementation. However, overall transportation planning to incorporate these wide-ranging objectives requires characterization of large-scale transportation systems and traffic flow through them, which is dynamic in nature, computationally intense and a non-trivial problem. Thus, these contemporary questions lie at the interface of transportation planning, urban development and sustainability planning. They have the potential of being effectively addressed through state-of-the-art transportation modeling tools, which is the main motivation and philosophy of this thesis. From the research standpoint, some of these issues have been addressed in the past typically from the urban design, built-environment, public health and vehicle technology and mostly qualitative perspectives, but not as much from the traffic engineering and transportation systems perspective---a gap in literature which the thesis aims to fill. Specifically, it makes use of simulation-based dynamic traffic assignment (DTA) to develop modeling paradigms and integrated frameworks to seamlessly incorporate these in the transportation planning process. In addition to just incorporating them in the planning process, DTA-based paradigms are able to accommodate numerous spatial and temporal dynamics associated with system traffic, which more traditional static models are not able to. Besides, these features are critical in the context of the planning questions of this study. Specifically, systemic impacts of suburban and urban street pattern developments typically found in US cities in past decades of the 20th century have been investigated. While street connectivity and design evolution is mostly regulated through local codes and subdivision ordinances, its impacts on traffic and system congestion requires modeling and quantitative evidence which are explored in this thesis. On the environmental impact mitigation side, regional emission inventories from the traffic sector have also been quantified. Novel modeling approaches for the street connectivity-accessibility problem are proposed. An integrated framework using the Environmental Protection Agency's regulatory MOVES model has been developed, combining it with mesoscopic-level DTA simulation. Model demonstrations and applications on real and large-sized study areas reveal that different levels of connectivity and accessibility have substantial impacts on system-wide traffic---as connectivity levels reduce, traffic and congestion metrics show a gradually increasing trend. As regards emissions, incorporation of dynamic features leads to more realistic emissions inventory generation compared to default databases and modules, owing to consideration of the added dynamic features of system traffic and region-specific conditions. Inter-dependencies among these sustainability planning questions through the common linkage of traffic dynamics are also highlighted. In summary, the modeling frameworks, analyses and findings in the thesis contribute to some ongoing debates in planning studies and practice regarding ideal urban designs, provisions of sustainability and complete streets. Furthermore, the integrated emissions modeling framework, in addition to sustainability-related contributions, provides important tools to aid MPOs and state agencies in preparation of state implementation plans for demonstrating conformity to national ambient air-quality standards in their regions and counties. This is a critical condition for them to receive federal transportation funding. / text

In this thesis, the channel assignment and routing problems have been investigated for both cooperative and competitive Wireless Mesh networks (WMNs). A dynamic and distributed channel assignment scheme has been proposed which generates the network topologies ensuring less interference and better connectivity. The proposed channel assignment scheme is capable of detecting the node failures and mobility in an efficient manner. The channel monitoring module precisely records the quality of bi-directional links in terms of link delays. In addition, a Quality of Service based Multi-Radio Ad-hoc On Demand Distance Vector (QMR-AODV) routing protocol has been devised. QMR-AODV is multi-radio compatible and provides delay guarantees on end-to-end paths. The inherited problem of AODV’s network wide flooding has been solved by selectively forwarding the routing queries on specified interfaces. The QoS based delay routing metric, combined with the selective route request forwarding, reduces the routing overhead from 24% up to 36% and produces 40.4% to 55.89% less network delays for traffic profiles of 10 to 60 flows, respectively. A distributed channel assignment scheme has been proposed for competitive WMNs, where the problem has been investigated by applying the concepts from non-cooperative bargaining Game Theory in two stages. In the first stage of the game, individual nodes of the non-cooperative setup is considered as the unit of analysis, where sufficient and necessary conditions for the existence of Nash Equilibrium (NE) and Negotiation-Proof Nash Equilibrium (N-PNE) have been derived. A distributed algorithm has been presented with perfect information available to the nodes of the network. In the presence of perfect information, each node has the knowledge of interference experience by the channels in its collision domain. The game converges to N-PNE in finite time and the average fairness achieved by all the nodes is greater than 0.79 (79%) as measured through Jain Fairness Index. Since N-PNE and NE are not always a system optimal solutions when considered from the end-nodes prospective, the model is further extended to incorporate non-cooperative end-users bargaining between two end user’s Mesh Access Points (MAPs), where an increase of 10% to 27% in end-to-end throughput is achieved. Furthermore, a non-cooperative game theoretical model is proposed for end-users flow routing in a multi-radio multi-channel WMNs. The end user nodes are selfish and compete for the channel resources across the WMNs backbone, aiming to maximize their own benefit without taking care for the overall system optimization. The end-to-end throughputs achieved by the flows of an end node and interference experienced across the WMNs backbone are considered as the performance parameters in the utility function. Theoretical foundation has been drawn based on the concepts from the Game Theory and necessary conditions for the existence of NE have been extensively derived. A distributed algorithm running on each end node with imperfect information has been implemented to assess the usefulness of the proposed mechanism. The analytical results have proven that a pure strategy Nash Equilibrium exists with the proposed necessary conditions in a game of imperfect information. Based on a distributed algorithm, the game converges to a stable state in finite time. The proposed game theoretical model provides a more reasonable solution with a standard deviation of 2.19Mbps as compared to 3.74Mbps of the random flow routing. Finally, the Price of Anarchy (PoA) of the system is close to one which shows the efficiency of the proposed scheme.

The brown trout, Salmo trutta L., displays one of the most variable and polymorphic life-history strategies of all the salmonids. In some populations, individuals spend their whole life-cycle in the river (freshwater-resident) whereas in others, a varying proportion migrates to sea for variable amounts of time to better feeding conditions before returning to spawn (anadromous). The ‘decision’ if an individual will migrate or not will be determined by the balance of the costs and benefits of following a particular life-history strategy. The balance of these, which do not affect males and females equally, will determine the future success (measured by fitness) of each strategy. This research addresses the influences of parental contribution, mainly maternal effect, of anadromous and freshwater-resident brown trout on offspring performance and subsequent life-history. A partial migratory population of brown trout was studied in the Tadnoll Brook, one of the seven major tributaries on the River Frome. The tributary is classified as a circum-neutral chalk stream, 9.9 km long with a catchment approximately 50 km2. Carbon and nitrogen stable isotope analysis (SIA) was used to quantify maternal reproductive contribution of anadromous and freshwater-resident brown trout to offspring and determine the future success (measured by fitness) in terms of size and time of emergence. A panel of 12 microsatellite loci was used to assign parentage to 0+ parr. Using field data collected over 1.5 years on individual fish, this study tested parental influence on offspring performance in terms of size and growth rate and calculate the reproductive contribution of maternal/paternal anadromous and freshwater-residents. Adult life-history strategy was identified using a combination of results from SIA, PIT tag data and ecological data (body size, temperature). Parr life-history strategy (1+) was inferred using PIT tag detection data. The results of the SIA indicated fry of anadromous females emerged earlier and at a larger size than fry of freshwater-resident females. Parentage assignment of parr was low (28 %), with 8 parr assigned to both parents and 43 assigned to only a single parent. There was no detectable effect of parental life-history on parr size and growth rate, however the raw data may suggest offspring of anadromous parents have an early size advantage but a slower growth compared to offspring of freshwater-resident parents during the first year of the parr stage. Twenty-four percent of the offspring were identified as putative smolts at 2+ and both forms interbred and could produce offspring of each life-history. Estimates of reproductive contribution (SIA and growth) show a higher proportion of anadromous females and males (growth only) contributed to offspring production. The results of this research indicate that the maternal anadromous contribution is higher in the Tadnoll Brook population, affording fitness benefits to their offspring during early ontogeny such as size advantages and emerging at a more profitable time to establish feeding territories. Adult life-history does not appear to influence juvenile (0+ parr) life-history but may have an effect on offspring performance. The presence of both forms in the population suggests the anadromous fitness benefits to offspring may only have an affect during ontogeny and early stages of growth. Then after juveniles reach a size threshold environmental factors influence offspring life-history, resulting in the largest parr with the fastest growth adopting an anadromous life-history.

Approved for public release, distribution is unlimited / The enlisted personnel assignment process is a major part in the United States Navy's Personnel Distribution system. It ensures warfighters and supporting activities receive the right sailor with the right training to the right billet at the right time (R4) and is a critical element in meeting the challenges of Seapower 21 and Global CONOPS. In order to attain these optimal goals the ways-to-do-it need to be customer-centered and should optimize both, the Navy's needs and the sailor's interests. Recent studies and a detailing pilot in 2002 used a web-based marketplace with two-sided matching mechanisms to accomplish this vision. This research examines the introduction of an Assignment Incentive Pay (AIP) as part of the U.S. Navy's enlisted personnel assignment process in a simulation environment. It uses a previously developed simulation tool, including the Deferred Acceptance (DA) and the Linear Programming (LP) matching algorithm to simulate the assignment process. The results of the sensitivity analysis suggested that the Navy should mainly emphasize sailor quality rather than saving AIP funds in order to maximize utility and the possible matches. When adopting such an introduction policy also the percentage of unstable matches under the LP as the matching algorithm was reduced. / Commander, German Navy

Travel time reliability is deemed as one of the most important factors affecting travelers’ route choice decisions. However, existing practices mostly consider average travel time only. This dissertation establishes a methodology framework to overcome such limitation. Semi-standard deviation is first proposed as the measure of reliability to quantify the risk under uncertain conditions on the network. This measure only accounts for travel times that exceed certain pre-specified benchmark, which offers a better behavioral interpretation and theoretical foundation than some currently used measures such as standard deviation and the probability of on-time arrival. Two path finding models are then developed by integrating both average travel time and semi-standard deviation. The single objective model tries to minimize the weighted sum of average travel time and semi-standard deviation, while the multi-objective model treats them as separate objectives and seeks to minimize them simultaneously. The multi-objective formulation is preferred to the single objective model, because it eliminates the need for prior knowledge of reliability ratios. It offers an additional benefit of providing multiple attractive paths for traveler’s further decision making. The sampling based approach using archived travel time data is applied to derive the path semi-standard deviation. The approach provides a nice workaround to the problem that there is no exact solution to analytically derive the measure. Through this process, the correlation structure can be implicitly accounted for while simultaneously avoiding the complicated link travel time distribution fitting and convolution process. Furthermore, the metaheuristic algorithm and stochastic dominance based approach are adapted to solve the proposed models. Both approaches address the issue where classical shortest path algorithms are not applicable due to non-additive semi-standard deviation. However, the stochastic dominance based approach is preferred because it is more computationally efficient and can always find the true optimal paths. In addition to semi-standard deviation, on-time arrival probability and scheduling delay measures are also investigated. Although these three measures share similar mathematical structures, they exhibit different behaviors in response to large deviations from the pre-specified travel time benchmark. Theoretical connections between these measures and the first three stochastic dominance rules are also established. This enables us to incorporate on-time arrival probability and scheduling delay measures into the methodology framework as well.