Heterogeneous computing (HC) systems are essential parts of modern-day computing architectures such as cloud, cluster, grid, and edge computing. Many algorithms exist within the classical environment for mapping computational tasks to the HC system’s nodes, but this problem is not well explored in the quantum area. In this work, the practicality, accuracy, and computation time of quantum mapping algorithms are compared against eleven classical mapping algorithms. The classical algorithms used for comparison include A-star (A*), Genetic Algorithm (GA), Simulated Annealing (SA), Genetic Simulated Annealing (GSA), Opportunistic Load Balancing (OLB), Minimum Completion Time (MCT), Minimum Execution Time (MET), Tabu, Min-min, Max-min, and Duplex. These algorithms are benchmarked using several different test cases to account for varying system parameters and task characteristics. This study reveals that a quantum mapping algorithm is feasible and can produce results similar to classical algorithms.

The premise of this research is the concept, development, and application of an approximate relation for the material balance of abnormally-pressured gas reservoirs. The approximation is formulated directly from the rigorous material balance for the case of an abnormally-pressured gas reservoir. The primary assumption in this derivation is that WGp <1 or Ce(p)(pi-p)<1. Further, we can proceed by assuming that W is either constant or some arbitrary function. If we assume W=constant, then the following form results: At first glance there may be concern that this approximation is not sufficiently valid for field applications — however, we have shown this relation to be an extraordinarily accurate approximation of the rigorous material balance. This result is suited not only for use as a characteristic model, but also for use as a data analysis mechanism (i.e., this result is used to develop a suite of analysis plots, plotting functions, a type curve, etc.). In this work we provide the following new results: 1) A suite of 6 (six) plotting functions based on the p/z-Gp2 material balance model. 2) A suite of 4 (four) p/z-Gp performance plots which are used to calibrate analysis. 3) A new type curve in terms of a dimensionless pressure function (pD=(pi/zi-p/z)/pi/zi) versus a dimensionless cumulative production function (GpD=Gp/G), where the type curve solution is based on the new p/z-Gp^2 (a quadratic material balance) model.

Multilevel modeling represents a potentially viable method for meta-analyzing single-subject research, but questions remain concerning its methodological properties with regard to characteristics of single-subject data. For this dissertation, Monte Carlo methods were used to investigate the properties of a 3 level model (i.e., with a quadratic equation at level 1), and three different level 1 error specifications (i.e., different variance components and covariances of 0, lag-1 autoregressive covariance structures, and separate error terms for each phase, with different variance components and covariances of 0). Data for simulated subjects were generated to have characteristics typical of published single-subject data (e.g., typical variances and magnitudes of effect). Samples were simulated for conditions which varied in number of data points per phase, number of subjects per study, number of studies meta-analyzed, level of autocorrelation in residuals, and continuity of variance across phases. Outcome variables examined included rates of convergence of analyses, power for statistical tests of fixed effects, and relative parameter bias of estimates of fixed effects, random effects’ variance components, and autocorrelation estimates. Convergence rates were found to be 100% for all level 1 error specifications and data conditions. Power for statistical tests of fixed effects was observed to be adequate when 10 or more data points were generated per phase and 60 or more total subjects were included in meta-analyses. The relative biases of estimates of fixed effects were found to have limited associations with numbers of data points per phase, levels of autocorrelation, and the continuity/discontinuity of variance across phases. Random effects’ variance components were observed to be frequently biased. Associations between relative bias and data conditions were found to vary by random effect. Finally, autocorrelation estimates were found to be biased in all conditions for which autocorrelation was generated. Results are discussed with regard to study strengths and limitations, and their implications for the meta-analysis of single subject data and primary single subject research. / text

Orientador: Mario Antonio Bernal Rodriguez / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-08-30T22:42:12Z (GMT). No. of bitstreams: 1 TelloCajiao_JohnJames_M.pdf: 2614936 bytes, checksum: e5bdfc91b42434b003cad0b5fa850afb (MD5) Previous issue date: 2016 / Resumo: O objetivo deste trabalho é estudar a influência da conformação do DNA na probabilidade de dano direto produzido por partículas ionizantes. Além disso, os fundamentos mecanicísticos do modelo Linear-Quadrático são investigadas através de um modelo biofísico desenvolvido neste trabalho, baseado na TADR (Teoria da Ação Dual da Radiação). Para este fim, três modelos geométricos do material genético foram construídos. Os modelos têm resolução atomística e levam em conta ? 10^9 pares de base (bps) nas configurações A,B e Z do DNA. A partir de um único bp, os diferentes níveis organizacionais no interior do núcleo da célula foram criados por meio de transformações lineares. Em seguida, o código Monte Carlo (MC) GEANT4-DNA foi usado para simular o transporte de prótons de 0.5, 1, 5, 7 e 10 MeV assim como de partículas alfa de 2, 5, 7 e 10M eV . O número de partículas em cada caso é de tal modo que as doses absorvidas estão entre 0.5 ? 16Gy. Os três modelos foram consistentes com as dimensões das estruturas reais. Em particular, os modelos foram compatíveis com a exigência de que o diâmetro da cromatina seja de 30 nm, bem como com os volumes bp reportados em outros trabalhos. Os rendimentos tanto das quebras totais quanto das quebras duplas (TSBY e DSBY) foram obtidos para cada qualidade de radiação. Além disso, a probabilidade de impacto (SHP) definida como a razão entre o volume do DNA e o volume núcleo, foi calculada teoricamente e a partir das simulações. O modelo biofísico em conjunto com as simulações MC forneceu o número de lesões letais (N_LL) em função da dose, para prótons de 0,5 e 10 MeV, e para partículas alfa de 2 e 10 MeV . Os N_LL puderam ser divididos em aqueles criados por uma única trajetória e aqueles originados pela interacção de duas trajetórias. Concluiu-se que o TSBY é praticamente determinada pela SHP e depende fracamente da qualidade de radiação incidente. No entanto, o DSBY mostrou forte dependência tanto da conformação do DNA quanto da qualidade de radiação. Isto é devido à relação entre a capacidade de agrupamento das deposições de energia para uma radiação dada e o empacotamento do DNA. Por outro lado, a análise dos mecanismos de produção de dano, baseada na TADR e testada com o modelo biofísico desenvolvido, mostraram que os efeitos de uma única trajetória (de primeira ordem) dependem linearmente com a dose. Além disso, os efeitos inter-trajetórias seguem um comportamento quadrático com a dose, com um termo linear que influencia o mecanismo de primeira ordem. Isto significa que o comportamento linear-quadrático do N_LL com a dose, tem fundamentos mecanicistas, pelo menos, na primeira fase do dano / Abstract: The aim of this work is to study the influence of the DNA conformation on the probability of direct damage induction by ionizing particles. Also, the mechanistic grounds of the Linear-Quadratic radiobiological model are investigated through the eyes of a home-made biophysical model based on the DRAT (Dual Radiation Action Theory). To this end, three geometrical models of the genetic material were constructed. The models have atomistic resolution and account for ? 10^9 base pairs (bps) in the A-, B- and Z-DNA configurations. Starting from a single bp, the different organizational levels inside the cell nucleus were created by means of linear transformations. Next, the Monte Carlo (MC) code GEANT4-DNA was used to simulate the transport of protons of 0.5, 1, 5, 7 and 10 MeV , and alpha particles of 2, 5, 7 and 10 MeV. The number of particles in each case is such that the absorbed doses range between 0.5 Gy and 16 Gy. The three models proved to be consistent with the dimensions of the real structures. In particular, the models were compatible with the 30 nm chromatin fiber diameter requirement as well as with the bp volumes reported in other works. The Total and Double Strand Break Yields (TSBY and DSBY) were obtained for every radiation quality. Also, the Site-Hit Probability (SHP) defined as the total target to the nucleus volume ratio, was computed theoretically and from the simulations. The biophysical model in conjunction with the MC simulations furnished the number of lethal lesions (N_LL) as a function of dose, for protons of 0.5 and 10 MeV , and for alpha particles of 2 and 10 MeV . The N_LL could be split into those created by a single track and those originated by interaction of two tracks. It is concluded that the TSBY is practically determined by the SHP and depends weakly on the incident radiation quality. Nevertheless, the DSBY showed strong dependence on both the DNA conformation and the radiation quality. This is due to the interplay between the energy deposition clustering capacity of a given radiation and the DNA spatial packing. On the other hand, the analysis of the mechanisms of damage production based on the DRAT and tested with the biophysical model developed, showed that single-track (first order) effects depend linearly on the dose. Moreover, inter-track effects follows a quadratic behavior with the dose, having a linear term that influences the first order mechanism. This means that the Linear-Quadratic behavior of the N_LL with the dose, has mechanistic groundings at least at the first stage of the damage / Mestrado / Física / Mestre em Física / 1370449/2014 / CAPES

Less-than-truckload industry has a valuable potential for applications of operations research in two areas, network design and efficiency improvement within existing networks. This thesis focuses on the latter, specifically the less-than-truckload terminals where cross docking operations occur. The assignment of incoming trailers to inbound docks is one of the critical decisions that affect the performance of less-than-truckload terminals. This research reviews existing models in literature and introduces an optimal mixed integer quadratic model with the objective of generating assignments that are robust against variability in system parameters such as truck arrival and service times, terminal characteristics and trailer load content. The computational limitations of the optimal model are discussed. A dock assignment heuristic is developed to overcome the computational difficulties reported with the optimal model to solve realistic size problems. It is concluded that the heuristic is generally applicable and is robust against system variably. A dynamic dock assignment heuristic is later introduced to implement the decision process at real time. It is concluded that the dynamic dock assignment heuristic is also robust against system variability. The last part presents a case study that benchmarks the dynamic dock assignment heuristic and existing static assignments at a real terminal. The results show that the dynamic dock assignment heuristic outperforms the static assignment under system variability. Conclusions and future research areas are finally addressed in the last chapter.

Un modèle de croissance et de réponse à la radiothérapie pour le glioblastome multiforme (GBM) basé le formalisme du modèle de prolifération-invasion (PI) et du modèle linéaire-quadratique a été développé et implémenté. La géométrie spécifique au patient est considérée en modélisant, d'une part, les voies d'invasion possibles des GBM avec l'imagerie du tenseur de diffusion (DTI) et, d'autre part, les barrières à la propagation à partir des images anatomiques disponibles. La distribution de dose réelle reçue par un patient donné est appliquée telle quelle dans les simulations, en respectant l'horaire de traitement. Les paramètres libres du modèle (taux de prolifération, coefficient de diffusion, paramètres radiobiologiques) sont choisis aléatoirement à partir de distributions de valeurs plausibles. Un total de 400 ensembles de valeurs pour les paramètres libres sont ainsi choisis pour tous les patients, et une simulation de la croissance et de la réponse au traitement est effectuée pour chaque patient et chaque ensemble de paramètres. Un critère de récidive est appliqué sur les résultats de chaque simulation pour identifier un lieu probable de récidive (SPR). La superposition de tous les SPR obtenus pour un patient donné permet de définir la probabilité d'occurrence (OP). Il est démontré qu'il existe des valeurs de OP élevées pour tous les patients, impliquant que les résultats du modèle PI ne sont pas très sensibles aux valeurs des paramètres utilisés. Il est également démontré comment le formalisme développé dans cet ouvrage pourrait permettre de définir un volume cible personnalisé pour les traitements de radiothérapie du GBM. / We have developed and implemented a model of growth and response to radiotherapy for glioblastoma multiforme (GBM) based on the proliferation-invasion (PI) formalism and linear-quadratic model. We take into account patient-specific geometry to model the possible invasion pathways of GBM with diffusion tensor imaging (DTI) and the barriers to dispersal from anatomical images available. The actual dose distribution received by a given patient is applied as such in the simulation, respecting the treatment schedule. The free parameters in the model (proliferation rate, diffusion coefficient, radiobiological parameters) are randomly chosen from a distribution of plausible values. A total of 400 sets of values for the free parameters are thus chosen for all patients, and a simulation of the growth and the response to treatment is performed for each patient and each set of parameters. A failure criterion is applied to the results of each simulation to identify a site of potential recurrence (SPR). The superposition of all SPR obtained for a given patient defines the occurrence probability (OP). We show that high OP values exist for all patients and conclude that the PI model results are not very sensitive to the values of the parameters used. Finally, we show how the formalism developed in this work could help to define a custom target volume for radiation treatment of GBM.