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The possibility of using a commercially available structural analysis program to predict the response of a floor system due to walking excitation as given in AISC Design Guide 11, Floor Vibrations Due to Human Activity (Murray, et al., 1997) was explored. This research included ideal floors that did not have measured values as well as several case study floors that do have measured values for the fundamental frequency. First, multiple model set-ups and loading protocols are applied to the ideal floors and the results compared to results from the Design Guide procedure. A recommendation of the best combination of a model set-up and loading protocol that best matches the Design Guide procedure results is made. Then, case study floors are modeled with the recommended model set-up and loading protocol, and the results compared to the results from the Design Guide procedure and to measured fundamental frequencies. The peak accelerations are also compared to subjective evaluations as to the acceptability of the system. Next, multiple systems were analyzed using five different modeling techniques, including the Design Guide Method, an alteration of the Design Guide Method, the Rayleigh Method, the Analytical Method, and the structural analysis program method, in an attempt to determine the source of discrepancies between the structural analysis program method and the Design Guide method. Finally, conclusions are drawn regarding the structural analysis program procedure as well as possible sources of differences. In general, the structural analysis program procedure reliably predicts the fundamental frequency of a floor system, but does not predict the Design Guide peak acceleration under dynamic loading. The difference in the effective mass of a system between the two methods is a source of discrepancy. / Master of Science

This dissertation proposes a novel computer modeling (DTFLOP modeling) technique to predict the real-time behavior of dynamic systems. The proposed DTFLOP modeling classifies the computation into the sequential computation, which is conducted on the CPU, and the parallel computation, which is performed on the GPU and formulates the data transmission between the CPU and the GPU using the parameters of the memory access speed and the floating point operations to be carried out on the CPU and the GPU by relating the calculation rate respectively. With the help of the proposed DTFLOP modeling it is possible to estimate the time cost for computing the model that represents a dynamic system given a certain computer. The proposed DTFLOP modeling can be utilized as a general method to analyze the computation of a model related to a dynamic system and two real life systems are selected to demonstrate its performance, the cooperative autonomous vehicle system and the full-field measurement system. For the cooperative autonomous vehicle system a novel parallel grid-based RBE technique is firstly proposed. The formulations are derived by identifying the parallel computation in the prediction and correction processes of the RBE. A belief fusion technique, which fuses not only the observation information but also the target motion information, has hen been proposed. The proposed DTFLOP modeling is validated using the proposed parallel grid-based RBE technique with the GPU implementation by comparing the estimated time cost with the actual time cost of the parallel grid-based RBE. The superiority of the proposed parallel grid-based RBE technique is investigated by a number of numerical examples in comparison with the conventional grid-based RBE technique. The belief fusion technique is examined by a simulated target search and rescue test and it is observed to maintain more information of the target compared with the conventional observation fusion technique and eventually leads to the better performance of the target search and rescue. For the full-field measurement system a novel parallel DCT full-field measurement technique for measuring the displacement and strain field on the deformed surface of a structure is proposed. The proposed parallel DCT full-field measurement technique measures the displacement and strain field by tracking the centroids of the marked dots on the deformed surface. It identifies and develops the parallel computation in the image analysis and the field estimation processes and then is implemented into the GPU to accelerate the conventional full-field measurement techniques. The detail strategy of the GPU implementation is also developed and presented. The corresponding software package, which also includes a graphic user interface, and the hardware system consist of two digital cameras, LED lights and adjustable support legs to accommodate indoor or outdoor experimental environments are proposed. The proposed DTFLOP modeling is applied to the proposed parallel DCT full-field measurement technique to estimate its performance and the well match with the actual performance demonstrates the DTFLOP modeling. A number of both simulated and real experiments, including the tensile, compressive and bending experiments in the laboratory and outdoor environments, are performed to validate and demonstrate the proposed parallel DCT full-field measurement technique. / Ph. D.

Les travaux présentés dans le cadre de cette thèse sont divisés en trois grandes parties qui concernent l’utilisation des nanoparticules métalliques pour augmenter les effets de la radiothérapie. Cette utilisation très particulière des nanoparticules n’a fait l’objet, jusqu’à présent, que d’études précliniques sauf un nano-objet qui fait actuellement l’objet de phases cliniques I et II à l’Institut Gustave Roussy de Villejuif, France. La première partie est une recherche bibliographique qui s’est concrétisée par la parution d’un état de l’art dans une revue internationale. Ce dernier identifie les paramètres jouant un rôle clef dans l’augmentation de la radiothérapie par les nanoparticules. Suite à cette étude de la littérature, le constat a été fait que la recherche préclinique en nanomédecine est plus longue et plus onéreuse que celle qui s’intéresse aux objets (macro-molécules) de taille standard. C’est pour améliorer cette prise en charge préclinique qu’une plateforme informatique de simulation Monte-Carlo des interactions nanoparticules – rayons X a été développée. Cette dernière ayant pour objectif de réaliser un classement in silico rapide et fiable des nanoparticules radiosensibilisantes permettant d’identifier de façon efficiente les nanostructures présentant les propriétés les plus prometteuses. La seconde partie de cette thèse consiste en une analyse de robustesse de ce simulateur, visant à identifier les paramètres de variabilité intrinsèques au simulateur et à quantifier leur influence sur la variation des résultats. Trois paramètres ont été identifiés comme paramètres critiques de simulation et doivent être maintenus constants entre les différentes études. Enfin, une troisième partie traite de l’application de cet outil de simulation au screening virtuel de nanoparticules radiosensilisantes. Dans cette partie sont réalisées une analyse de prédiction in silico / in vitro et une analyse de prédiction in silico / in cellulo. Les résultats très encourageants (correspondance acceptable entre les prédictions du simulateur et les résultats in cellulo) obtenus durant cette dernière phase ont également fait l’objet d’une soumission à publication dans une revue internationale. / The work that has been carried out during this PhD thesis is divided into three main parts that are related to the use of metallic nanoparticles to enhance the effects of radiation therapy. Until now, this particular use of nanoparticles has only been limited to preclinical trials apart from a single nano-object which is currently tested in phases I and II clinical trials in the Institut Gustave Roussy of Villejuif, France. The first part of this study is a bibliographic research that has been published as a review article in an international journal. The latter identifies the key parameters responsible for the enhancement of radiation therapy by nanoparticles. Following this part, the observation was made that the preclinical research in nanomedicine is longer and more expensive than for classical macromolecules. That is why, in order to improve this preclinical step, a Monte Carlo simulation platform of nanoparticles – X rays interactions has been developed. The aim of this platform is to perform a quick and reliable in silico ranking of radiosensitizing nanoparticles in order to efficiently identify the nanostructures with the most promising properties. The second part of this thesis consists of a robustness analysis of the latter simulator, aiming to identify its intrinsic variability parameters and to quantify their influence on the variability of the results. Three parameters have been identified as critical simulation parameters and should be kept constant between studies. Finally, a third part deals with the application of the simulation platform to the virtual screening of radiosensitizing nanoparticles. A predictive in silico / in vitro and in silico / in cellulo analysis are carried out in this section. Promising results (acceptable matching between simulator’s predictions and in cellulo results) obtained during this last phase were also submitted for publication in an international journal.

The unfolded protein response (UPR) is activated by protein misfolding stress in the endoplasmic reticulum (ER). The UPR is a transcriptional program that aims to maintain ER folding capacity, where imbalances between protein load and processing ability is termed ER stress. Signal transduction of the UPR begins with 3 ER-resident transmembrane sensors: PERK, IRE1 and ATF6. All sensors initiate downstream signaling cascades which culminate in improved protein folding, transcriptional upregulation of genes encoding ER chaperones, and mechanisms to reduce translational and transcriptional ER load, therefore re-establishing ER homeostasis. The signaling cascades of each sensor are distinct but cooperative, and involve a significant amount of crosstalk, feedback and overlap. Indeed, there are many pathological and physiological conditions have an effect on ER protein burden, and therefore on activation of the UPR. Increases in protein load in professional secretory cells, hypoxic conditions in a tumor mass, obesity all induce cause changes in the ER folding environment. Although we understand how the UPR contributes to relieve ER stress under acute conditions (e.g. pharmacological treatment) much less is understood about the contributions to physiological processes and chronic stress conditions. Our overall goal was to understand how the UPR is activated during physiological settings, the mechanisms it uses to maintain folding capacity under these setting and the specific components responsible for adapting the response to various stresses. We first decided to understand a chronic stress from a transgenic approach. By creating a knockout mouse, the genetic deletion functions as a stress and we can understand its physiological role. By compounding two genetic deletions in UPR components (ATF6α and p58IPK) we provide evidence for the developmental role these components play. Homozygous deletion ATF6α bears no gross histological phenotype yet causes synthetic lethality when combined with p58IPK deletion. This also reveals that the UPR is able to adapt to genetic impairment of protein folding in vivo. Next, to better understand these chronic states, we established an experimentally tractable chronic stress treatment in vivo. Our treatment suppressed ATF6α dependent chaperone expression through an mRNA degradative mechanism, which led to long term changes in UPR expression. We determined that chronic conditions can change the sensitivity of the UPR to ER stress, potentially as an adaptive consequence. We also showed that sensitivity to ER stress can be changed during chronic stress. Finally we simulated the UPR in a computational ordinary differential equation (ODE) model in order to determine how various stresses and component interactions determine the output of the UPR. We built a series of equations to describe the UPR signaling network, entrained it on experimental data and refined it through the use of transgenic knockout cells. Our model was robust enough to recreate experimental measurements of UPR components when tested in parallel with knockout cells. We found that stress sensitivity is dependent on the crosstalk and negative feedback connections of the UPR. This study has enhanced our understanding of activation of the UPR under non-acute settings. It demonstrates that the UPR is a signaling hub with a broad output range that is capable of handling a variable degree of insults because of the intrinsic properties of the signaling network. This provides a better understanding for the contributions of the UPR to physiological stresses and certain chronic diseases.

Software systems increasingly interact with each other, forming ecosystems. Cloud is one such ecosystem that has evolved and enabled other technologies like IoT and containers. Such systems are very complex and heterogeneous because their components can have diverse origins, functions, security policies, and communication protocols, which makes it difficult to comprehend, utilize and consequently secure them. Abstract architectural models can be used to handle this complexity and heterogeneity but there is lack of work on precise, implementation/vendor neutral and holistic models which represent ecosystem components and their mutual interactions. We attempted to find similarities in systems and generalize to create abstract models for adding security. We represented the ecosystem as a Reference architecture (RA) and the ecosystem units as patterns. We started with a pattern diagram which showed all the components involved along with their mutual interactions and dependencies. We added components to the already existent Cloud security RA (SRA). Containers, being relatively new virtualization technology, did not have a precise and holistic reference architecture. We have built a partial RA for containers by identifying and modeling components of the ecosystem. Container security issues were identified from the literature as well as analysis of our patterns. We added corresponding security countermeasures to container RA as security patterns to build a container SRA. Finally, using container SRA as an example, we demonstrated an approach for RA validation. We have also built a composite pattern for fog computing that is an intermediate platform between Cloud and IoT devices. We represented an attack, Distributed Denial of Service (DDoS) using IoT devices, in the form of a misuse pattern which explains it from the attacker’s perspective. We found this modelbased approach useful to build RAs in a flexible and incremental way as components can be identified and added as the ecosystems expand. This provided us better insight to analyze security issues across boundaries of individual ecosystems. A unified, precise and holistic view of the system is not just useful for adding or evaluating security, this approach can also be used to ensure compliance, privacy, safety, reliability and/or governance for cloud and related ecosystems. This is the first work we know of where patterns and RAs are used to represent ecosystems and analyze their security. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

TumbleTime is a children's customizable play area that is both fun and educational. Planned to be produced in foam and vinyl fabric, TumbleTime resembles a gymnastic mat. The design is involved geometry that allows children to discover geometric relationships while playing with their furniture. TumbleTime has thousands of configurations demonstrated by 3D computer renderings and animations produced using Autodesk 3ds Max.

The requirements to protect public water systems from intentional contamination have expanded in the years following September 11, 2001. The areal extent and non-linear nature of water demand and movement in the distribution system makes efficient location of sampling points difficult. This difficulty is compounded by the fact that contamination conceptually can occur at any point and at any time within the distribution system. Small to mid-sized water systems are especially at a disadvantage in addressing this issue due to limited resources available to them. This paper proposes a heuristic methodology to identify strategic locations within the system that can be established as critical detection points for such occurrences. The process uses off-the-shelf software and is structured to be accessible to small and mid-sized water system managers. This methodology is different from others proposed in the literature in that it uses computer simulations to create a database of water system response to contamination at every node in the system. A process is developed to mine this database systematically after considering concentration thresholds and "time since injection" parameters. Finally, using pivot tables and graphs, a network of monitoring locations is identified to provide efficient coverage of the system under the conditions imposed.