Yes / Smart city development is gaining considerable recognition in the systematic literature and international policies throughout the world. The study aims to identify the key barriers of smart cities from a review of existing literature and views of experts in this area. This work further makes an attempt on the prioritisation of barriers to recognise the most important barrier category and ranking of specific barriers within the categories to the development of smart cities in India. Through the existing literature, this work explored 31 barriers of smart cities development and divided them into six categories. This research work employed fuzzy Analytic Hierarchy Process (AHP) technique to prioritise the selected barriers. Findings reveal that ‘Governance’ is documented as the most significant category of barriers for smart city development followed by ‘Economic; ‘Technology’; ‘Social’; ‘Environmental’ and ‘Legal and Ethical’. In this work, authors also performed sensitivity analysis to validate the findings of study. This research is useful to the government and policymakers for eradicating the potential interferences in smart city development initiatives in developing countries like India.

Yes / Our previous case-control study observed isolated lymphocytes from 208 individuals and determined the differences in the sensitivity to genomic damage of lymphocytes derived from cancer patients, pre/suspect cancer patients and healthy volunteers using the Comet assay (Anderson et al, 2014). We adapted the LGS technique using a slightly different method and examined 700 more blood samples from 598 patients with cancer or suspected cancer and 102 healthy individuals. To help increase the sensitivity of the test and detect cancer at the level of each individual, we joined with the IMSTAR team who analysed our cells with their fully automated Pathfinder™ cell reader-analyser system. With this reading and analysis system 4,000 to 10,000 cells were able to be read per slide. The new test which is called TumorScan is a highly sensitive test to detect any cancer at an early stage through the response of the white blood cells to UV treatment. These patient blood samples have also been collected at the stage before confirming diagnosis and treatment. There were four of these individuals with cancer who had received anti-cancer treatment. The results from these patients showed a reverse pattern compared to non-treated cancer patients and followed the pattern seen in healthy individuals. The results are consistent with the early results as reported in the above 2014 paper. Given the results from these samples were in a particularly challenging subgroup, whose cancer status was difficult to distinguish, the data suggest that the technique using the TumorScan system could exceed the area under the ROC curve >93% obtained in the earlier study on a group basis, whereas this present study was to detect cancer at an early stage in each individual. / Department of Research and Knowledge Transfer at the University of Bradford, Bradford, UK

A computationally efficient procedure, NLPANOPT, is developed for the preliminary design of minimum-weight thin-walled stiffened composite panels loaded in uniaxial compression based on a geometrically nonlinear analysis. An approximate, semi-analytical nonlinear analysis code, NLPAN, which requires buckling eigenfunction information from the buckling analysis code, VIPASA, is linked with the optimization code ADS. A blade-stiffened and T-stiffened panel are designed for specified loads using NLPANOPT for postbuckling response and PASCO for buckling-critical response. Comparisons of panel weight and imperfection sensitivity between the NLPANOPT designs and PASCO designs are presented. In general, the designs obtained with NLPANOPT are lighter and less imperfection sensitive than the designs obtained with PASCO. The nonlinear analysis allows for a more accurate prediction of the true strength of the stiffened structure, by accounting for postbuckling strength and modal interaction. The effect of laminate stacking sequence is also investigated. The current design procedure requires the stacking sequence to be prescribed, proving to be a limitation in the design procedure. / Master of Science

Yes / This work aims to present an improved version of the liquid mixture identification sensor, the proposed sensor is tested experimentaly on mixture of water ethanol, the identification of liquid is based on the measurement of frequency displacement, and comparison with reference values of water ethanol. This device is based on metamaterial structure which is a CRLH (composite right left hand) resonator with ZOR (Zero Order Resonator). The CRLH in addition to its property of miniaturization effect, when combined with ZOR, the resonant frequency of various volume fraction are extended, which make the sensitivity higher. The high sensitivity of the sensor is obtained by an optimum choice of the CRLH components. The geometrical size of the sensor is 20 mm by 11 mm. It was printed on a RT/Duroid 5880 substrate with a very short testing surface area of 4 mm by 8 mm, the liquid is placed on the top side of the sensor, exactly on the CRLH structure. Three prototypes of sensors operating from 1 GHz to 3 GHz are proposed, designed and simulated using the commercial software HFSS (high-frequency structural simulator). The main advantages of this work is first miaturization effect, second high sensitivity and finaly a wide range of liquid can be tested with this sensor. To prove the working principle, ethanol with different volume fractions was adopted as a liquid under test, the obtained results present very good agreement with the literature and suggested that it is a miniaturised and high sensitive candidate (better than 1.38%) for liquid mixture identification.

Understanding the dynamics of agricultural basins has been difficult for decision-makers when developing cost-effective plans. An uncertainty analysis evaluates the impact of information gaps on hydrologic model’s output and performance. The Agricultural Policy/Environmental Extender (APEX v1501) was used to predict runoff, crop yield, sediment load, total phosphorus, and total nitrogen from agricultural fields in the Mississippi Delta to investigate the impact of using different input variables (climate, soils, and management practices) on mechanistic models. Results indicated that the use of surrogate information such as weather data from close weather stations, a predominant soil series, and simulated irrigation schedules, could be considered when available in situ information is restricted. Overall results provided information on model setup and output interpretation that may be useful to Mississippi Delta decision-makers.

No description available.

This thesis applies the theory of uncertainty quantification and sensitivity analysis on the SIR-model and SEIR-model for the spread of diseases. We attempt to determine if we can apply this theory to estimate the model parameters to an acceptable degree of accuracy.  Using sensitivity analysis we determine which parameters of the models are the most significant for some quantity of interest. We apply forward uncertainty quantification to determine how the uncertainty of the model parameters propagates to the quantities of interests. And lastly, we apply uncertainty quantification based on the maximum likelihood method to estimate the model parameters. To easily verify the results, we use synthetic data when estimating the parameters. After applying these methods we see that the importance of the model parameters heavily depend on the choice of quantity of interest. We also note that the uncertainty method reduces the uncertainty in the quantities of interests, although there are a lot of sources of errors that still needs to be considered.

Sensitivity analysis quantifies the effect that of perturbations of the model inputs have on the model's outputs. Some of the key insights gained using sensitivity analysis are to understand the robustness of the model with respect to perturbations, and to select the most important parameters for the model. MATLODE is a tool for sensitivity analysis of models described by ordinary differential equations (ODEs). MATLODE implements two distinct approaches for sensitivity analysis: direct (via the tangent linear model) and adjoint. Within each approach, four families of numerical methods are implemented, namely explicit Runge-Kutta, implicit Runge-Kutta, Rosenbrock, and single diagonally implicit Runge-Kutta. Each approach and family has its own strengths and weaknesses when applied to real world problems. MATLODE has a multitude of options that allows users to find the best approach for a wide range of initial value problems. In spite of the great importance of sensitivity analysis for models governed by differential equations, until this work there was no MATLAB ordinary differential equation sensitivity analysis toolbox publicly available. The two most popular sensitivity analysis packages, CVODES [8] and FATODE [10], are geared toward the high performance modeling space; however, no native MATLAB toolbox was available. MATLODE fills this need and offers sensitivity analysis capabilities in MATLAB, one of the most popular programming languages within scientific communities such as chemistry, biology, ecology, and oceanogra- phy. We expect that MATLODE will prove to be a useful tool for these communities to help facilitate their research and fill the gap between theory and practice. / Master of Science / Sensitivity analysis is the study of how small changes in a model?s input effect the model’s output. Sensitivity analysis provides tools to quantify the impact that small, discrete changes in input values have on the output. The objective of this research is to develop a MATLAB sensitivity analysis toolbox called MATLODE. This research is critical to a wide range of communities who need to optimize system behavior or predict outcomes based on a variety of initial conditions. For example, an analyst could build a model that reflects the performance of an automobile engine, where each part in the engine has a set of initial characteristics. The analyst can use sensitivity analysis to determine which part effects the engine’s overall performance the most (or the least), without physically building the engine and running a series of empirical tests. By employing sensitivity analysis, the analyst saves time and money, and since multiple tests can usually be run through the model in the time needed to run just one empirical test, the analyst is likely to gain deeper insight and design a better product. Prior to MATLODE, employing sensitivity analysis without significant knowledge of computational science was too cumbersome and essentially impractical for many of the communities who could benefit from its use. MATLODE bridges the gap between computational science and a variety of communities faced with understanding how small changes in a system’s input values effect the systems output; and by bridging that gap, MATLODE enables more large scale research initiatives than ever before.

The underlying mathematical model of many simulation models is graph dynamical systems (GDS). This dynamical system, its implementation, and analyses on each will be the focus of this paper. When using a simulation model to answer a research question, it is important to describe this underlying mathematical model in which we are operating for verification and validation. In this paper we discuss analyses commonly used in simulation models. These include sensitivity analyses and uncertainty quantification, which provide motivation for stability and structure-to-function research in GDS. We review various results in these areas, which contribute toward validation and computationally tractable analyses of our simulation model. We then present two new areas of research - stability of transient structure with respect to update order permutations, and an application of GDS in which a time-varying generalized cellular automata is implemented as a simulation model. / Master of Science / There are many systems in our society which are vital, and require quantitative analysis. These include population dynamics, transportation, and energy. To answer research questions about these systems, one may construct a mathematical model of the system and conduct simulations. It is important to define both the mathematical model and the simulation model in order to better understand the source of errors, or to be confident in the validity of the models. One source of error may be in parameters of our simulation model. It can be difficult to gather reliable and precise data, especially in massively interacting systems. Thus we would like to know that there is a range of values which will result in similar outcomes. Stability results can give us this assurance. This paper mainly focuses on stability results in graph dynamical systems (GDS), which is the underlying mathematical model of many simulation models, especially ones with a networked structure.

Barrier islands serve as valuable resources for coastal communities by reducing backbarrier flooding, providing wildlife habitat, and creating local economic activity through opportunities for recreation and tourism. Because the benefits of these islands are linked to their morphology, coastal resource planners must consider what management alternatives will maximize these benefits, considering both short- and long-term goals. Recent advances in long-term computational modeling of barrier island, marsh, and lagoon systems have created opportunities for gaining additional insights into the morphodynamics of these systems, which may help planners make better-informed coastal management decisions. In this series of studies, a recently developed long-term barrier-marsh-lagoon model is evaluated to better understand system morphodynamics and applied to a real barrier island system in the mid-Atlantic to understand its vulnerabilities and the potential impacts of management alternatives. In the first study, a comprehensive review of advances in barrier island morphodynamic modeling was presented. In the second study, a global sensitivity analysis method, the Sobol method, was used to explore the parameter space of the barrier-marsh-lagoon model. The significant influence of initial barrier geometry, the combination of parameters required for short-term drowning to occur, and the significant role of tidal dispersion on backbarrier sediment dynamics were morphodynamic insights drawn from this study. In the third study, five global sensitivity analysis methods were evaluated based on their ability to rank parameters, converge to stable results, and their reliability. Groups of the most significant parameters were generally identified by all methods; however, the Morris method exceeded all others in terms of performance, especially its ability to converge and its reliability. VARS performed second best, on average, with better convergence and reliability results than the Sobol method, and with lower simulation counts. In the fourth study, the long-term model was applied to a mid-Atlantic barrier island and used to assess the island's vulnerabilities to sea level rise, overwash, and the impact of coastal management alternatives. Thin-layer placement and beach nourishment were found to be effective at sustaining the marsh and minimizing island retreat, respectively. / Doctor of Philosophy / Barrier islands help coastal communities by reducing flooding, providing wildlife habitat, and creating local economic activity through opportunities for recreation and tourism. Because the benefits of these islands are linked to their form, decision-makers must think about how to manage these islands to help the community both now and in the future. Recent advances in computer modeling of barrier islands, and the adjacent marshes and lagoons, over decades to hundreds of years, have created opportunities for us to learn more about how these systems behave over time, which may help planners make better-informed coastal management decisions. In this series of studies, a recently developed computer model of the barrier island, marsh, and lagoon is evaluated to learn how the system changes over time and applied to a real barrier island system in the mid-Atlantic to understand its vulnerabilities and the potential impacts of management alternatives. In the first study, a comprehensive review of advances in computer modeling of barrier island changes over time was presented. In the second study, the impact of the model parameters and their combinations with one another was explored using the Sobol global sensitivity analysis method, which is widely considered to be the standard method in practice. The significant influence of initial barrier geometry, the combination of parameters required for the barrier to be overcome by sea level in the short-term, and the significant role of sediment delivered behind the island through tidal inlets were significant insights into the system behavior that were drawn from this study. In the third study, five global sensitivity analysis methods were evaluated based on their ability to rank parameters, the number of computer simulations that were required, the ability of a method to arrive at a conclusive answer, and the consistency of a method in providing an answer. Groups of the most significant parameters were generally identified by all methods; however, the Morris method exceeded all others in terms of its ability to find conclusive and consistent answers due to its ability to identify unimportant parameters. VARS performed second best, on average, with better ability to find conclusive and consistent answers with fewer computer simulations than Sobol. In the fourth study, the long-term computer model was applied to a mid-Atlantic barrier island and used to assess the island's vulnerabilities to sea level rise, overwash (when water flows over the dunes), and the impact of coastal management alternatives. Placing thin layers of additional sediment on top of the marsh platforms and extending the shoreline toward the ocean by placing additional sediment on the beach were found to be effective at sustaining the marsh and minimizing movement of the barrier island landward, respectively.