Presently, owners are interested in evaluating the feasibility of investing in the construction of new building projects based on cost and time constraints. They need to therefore have an idea about the project construction costs, the time required to finish construction of a project in its conceptual phase, and about the implementation of feasibility study. Because due to associated risks, construction cost estimates and schedules are vital to any project. The research’s objective is to develop a methodology that can be used to create an integrated computer model that helps owners and designers generate construction cost estimates, and derive the baseline schedule for any proposed building project at its feasibility stage. All the relevant data used within the model is collected from the literature and is stored in comprehensive databases designed for this purpose. The data is based on 2011 RSMeans publications and consist of around 4,000 previously constructed projects. The model is developed in a Microsoft environment using Microsoft Excel 2007 and Microsoft Project 2007. This model uses deterministic and stochastic approaches to execute all necessary calculations for the conceptual cost estimate and baseline schedule. A deterministic approach relies on realistic data while a stochastic one relies on incorporating the uncertainty and risk available in calculating the cost and duration of any construction building project. The model is user friendly, flexible and executes all the necessary calculations quickly. The successful development of the model would help owners and investors identify the cost and baseline schedule of proposed projects at the early stages of the project life, so that they have an idea of the budget required for construction and the time needed to recover their investment.

It is understood that children learn the use of grammatical categories in their native language, and previous models have only been partially successful in describing this acquisition. The present study uses an adaptation selection algorithm to continue the work in addressing this question. The input for the computer model is child-directed speech towards three children, ages ranging from 1;1 to 5;1 during the course of sampling. The output of the model consists of the input words labeled with a grammatical category. This output data was evaluated at regular intervals through its ability to correctly identify the grammatical categories of language of the target child. The findings suggest that the use of this type of model is effective in categorizing words into grammatical categories in both accuracy and completion.

Presently, owners are interested in evaluating the feasibility of investing in the construction of new building projects based on cost and time constraints. They need to therefore have an idea about the project construction costs, the time required to finish construction of a project in its conceptual phase, and about the implementation of feasibility study. Because due to associated risks, construction cost estimates and schedules are vital to any project. The research’s objective is to develop a methodology that can be used to create an integrated computer model that helps owners and designers generate construction cost estimates, and derive the baseline schedule for any proposed building project at its feasibility stage. All the relevant data used within the model is collected from the literature and is stored in comprehensive databases designed for this purpose. The data is based on 2011 RSMeans publications and consist of around 4,000 previously constructed projects. The model is developed in a Microsoft environment using Microsoft Excel 2007 and Microsoft Project 2007. This model uses deterministic and stochastic approaches to execute all necessary calculations for the conceptual cost estimate and baseline schedule. A deterministic approach relies on realistic data while a stochastic one relies on incorporating the uncertainty and risk available in calculating the cost and duration of any construction building project. The model is user friendly, flexible and executes all the necessary calculations quickly. The successful development of the model would help owners and investors identify the cost and baseline schedule of proposed projects at the early stages of the project life, so that they have an idea of the budget required for construction and the time needed to recover their investment.

<p>Traumatic injuries are the leading cause of death to children between the ages of one to nineteen years in the United States. The primary source of these traumatic injuries is motor vehicle traffic, with the head being the primary region of the body to suffer injury. While the pediatric neck is also prone to injury, it is particularly notable since it governs head excursion and acceleration, thus influencing head impacts and injuries. Pediatric fatalities can be prevented through safety improvements to vehicle compartments and child restraints by way of advanced biofidelic pediatric anthropomorphic testing devices (ATDs) and a more complete understanding of pediatric biomechanics. Computer models of the pediatric head and neck provide a valuable tool to combine results from pediatric postmortem human specimen (PMHS), radiological, and human volunteer studies to investigate the dynamics of the pediatric head and neck. The current study produced the first validated computer model of the pediatric head and neck which were created using the framework of a validated adult model. Radiology studies were conducted to determine pediatric cervical muscle cross sectional areas, vertebral anthropometry, and vertebral inertial properties. The results of these studies were combined with available pediatric PMHS properties to create the six and ten year old models. The models were validated against pediatric volunteer low speed frontal impacts and were then used to simulate higher rate and injurious inducing loading scenarios. The six and ten year old flexion bending stiffnesses were found to be 36% and 45% of the adult bending stiffness, respectively. The pediatric tensile stiffnesses were found to be 67% and 76% of the adult tensile stiffness. The tensile failure tolerance of the six year old was between 1490 and 2300 N and of the ten year old between 2040 and 3170 N. The adult and pediatric Hybrid III ATDs were found to be on average 2.5 times stiffer in flexion bending than the computer models. Biofidelity corridors were created with the models to be used to guide future ATD designs. Overall, the pediatric models provide a general tool that can be used to assess the safety of children during motor vehicle crashes.</p> / Dissertation

<p>Our interest is the risk assessment of rare natural hazards, such as</p><p>large volcanic pyroclastic flows. Since catastrophic consequences of</p><p>volcanic flows are rare events, our analysis benefits from the use of</p><p>a computer model to provide information about these events under</p><p>natural conditions that may not have been observed in reality.</p><p>A common problem in the analysis of computer experiments, however, is the high computational cost associated with each simulation of a complex physical process. We tackle this problem by using a statistical approximation (emulator) to predict the output of this computer model at untried values of inputs. Gaussian process response surface is a technique commonly used in these applications, because it is fast and easy to use in the analysis.</p><p>We explore several aspects of the implementation of Gaussian process emulators in a Bayesian context. First, we propose an improvement for the implementation of the plug-in approach to Gaussian processes. Next, we also evaluate the performance of a spatial model for large data sets in the context of computer experiments.</p><p>Computer model data can also be combined to field observations in order to calibrate the emulator and obtain statistical approximations to the computer model that are closer to reality. We present an application where we learn the joint distribution of inputs from field data and then bind this auxiliary information to the emulator in a calibration process.</p><p>One of the outputs of our computer model is a surface of maximum volcanic flow height over some geographical area. We show how the topography of the volcano area plays an important role in determining the shape of this surface, and we propose methods</p><p>to incorporate geophysical information in the multivariate analysis of computer model output.</p> / Dissertation

The equine paranasal sinuses are a frequent site of disease. They are anatomically complex structures encased in bone that are difficult to visualize. Because of their complexity and location, accurate diagnosis and treatment of the affected sinus(es) is difficult without a good understanding of their anatomy. Use of 3-D computer models in anatomy education has increased in recent years and shows promise in teaching anatomy of complex structures. The goal of this thesis was to develop a computer program illustrating a 3-D model of the equine paranasal sinuses to aid teaching the anatomy of the paranasal sinuses. A CT scan of a horse’s head was performed and a 3-D reconstruction was generated. The paranasal sinuses were illustrated in the reconstructed images using Adobe Photoshop 6.0. Adobe Flash Professional CS5 was used to create an interactive computer program from the images. The resulting computer program depicts the sinuses and features of the skull at five key points plus or minus nine degrees of rotation.

Hot-rolled steel products occupy a key position, between upstream and downstream, in the steel industry chain. In this country, revenue of hot-rolled strip steel products maintains the greatest proportion among all steel products. Continuous pursuit of knowledge progress and growth plays a significant support to sustainable enterprises and gives them a vigorous operational strength in the face of international competition. During the hot strip steel manufacturing process, as the second-level standard of the computer integrated manufacturing system in a steel plant describes, in addition to those needed information related with real-time electronic control equipment dealt by process control computers, how does hot strip mill statistical process computer, abbreviated HSMSPC, utilize statistical analysis and information processing also challenges the future competitiveness. This research engages in a genuine hot strip mill statistical process computer system developed by a well-known steel corporation located in Taiwan, adopting structure behavior coalescence, abbreviated as SBC, six golden rules to build up the architecture-oriented hot strip mill statistical process computer model, abbreviated as AOHSMSPCM. AOHSMSPCM shall construct a hot strip mill statistical process computer system in an architecture-oriented way so that it is able to fully express the operational act and information extraction which cover system structures and system behaviors as well; subsequently, the hot strip mill statistical process computer system will produce higher added value in the face of the production line variability, replicate update, knowledge management, and so on. AOHSMSPCM begins with the analysis layer of system architecture. In this research, system structures and system behaviors are well described in the HSMSPC analysis layer. Besides this, easy to duplicate and extension of scalability are thoroughly elaborated in this research. Finally, this research comes up with "Strengthening the variability control of a hot strip mill", "Preserving assets of corporate knowledge" and "Upgrading process technologies of production lines" as three benefits that AOHSMSPCM contributes to the enterprise.

<p>Cutting edge research problems require the use of complicated and computationally expensive computer models. I will present a practical overview of the design and analysis of computer experiments in high energy nuclear and astro phsyics. The aim of these experiments is to infer credible ranges for certain fundamental parameters of the underlying physical processes through the analysis of model output and experimental data.</p><p>To be truly useful computer models must be calibrated against experimental data. Gaining an understanding of the response of expensive models across the full range of inputs can be a slow and painful process. Gaussian Process emulators can be an efficient and informative surrogate for expensive computer models and prove to be an ideal mechanism for exploring the response of these models to variations in their inputs.</p><p>A sensitivity analysis can be performed on these model emulators to characterize and quantify the relationship between model input parameters and predicted observable properties. The result of this analysis provides the user with information about which parameters are most important and most likely to affect the prediction of a given observable. Sensitivity analysis allow us to identify what model parameters can be most efficiently constrained by the given observational data set.</p><p>In this thesis I describe a range of techniques for the calibration and exploration of the complex and expensive computer models so common in modern physics research. These statistical methods are illustrated with examples drawn from the fields of high energy nuclear physics and galaxy formation.</p> / Dissertation

Presently, owners are interested in evaluating the feasibility of investing in the construction of new building projects based on cost and time constraints. They need to therefore have an idea about the project construction costs, the time required to finish construction of a project in its conceptual phase, and about the implementation of feasibility study. Because due to associated risks, construction cost estimates and schedules are vital to any project. The research’s objective is to develop a methodology that can be used to create an integrated computer model that helps owners and designers generate construction cost estimates, and derive the baseline schedule for any proposed building project at its feasibility stage. All the relevant data used within the model is collected from the literature and is stored in comprehensive databases designed for this purpose. The data is based on 2011 RSMeans publications and consist of around 4,000 previously constructed projects. The model is developed in a Microsoft environment using Microsoft Excel 2007 and Microsoft Project 2007. This model uses deterministic and stochastic approaches to execute all necessary calculations for the conceptual cost estimate and baseline schedule. A deterministic approach relies on realistic data while a stochastic one relies on incorporating the uncertainty and risk available in calculating the cost and duration of any construction building project. The model is user friendly, flexible and executes all the necessary calculations quickly. The successful development of the model would help owners and investors identify the cost and baseline schedule of proposed projects at the early stages of the project life, so that they have an idea of the budget required for construction and the time needed to recover their investment.

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