Salmonella and Cronobacter sakazakii are two leading causes of foodborne illness associated with low-moisture foods, including infant formula. Both causative organisms can persist in food manufacturing processing environments and contaminate finished product if programs are not in place to limit their introduction and control their spread. An environmental sampling and monitoring program is an important tool that food manufacturers use to determine the effectiveness of their sanitation practices and pathogen control efforts. Guidance for initiating an environmental sampling plan and evaluating the plan is lacking. The objective of this study was to develop microbiological environmental sampling plans based on the answers to a series of questions related to product hazards, processing risks and controls, and knowledge of appropriate microbiological sampling and testing protocols. Furthermore, these initial sampling plans were related to the volume of product and size of the processing facility.  An interactive spreadsheet tool for designing sampling monitoring plans for an infant formula process was developed using Microsoft Excel. Additionally, the tool can be used to record qualitative and quantitative sample test results, and to alert the user how the upcoming sampling plan will be changed, if necessary, based on monthly test summaries. The sampling tool provides a simple method for selecting an appropriate environmental sampling plan (samples per zone per month) and provides a rationale and guidance for creating and modifying these plans.  Effective sampling plans and trend analysis of sample test results support the food processors decisions for implementing controls to enhance food safety. / Master of Science in Life Sciences

Abstract National Health Insurance (NHI) has been implemented in Taiwan for nearly eight years; since then, over 96% of 23 million residents of Taiwan have benefited from this program, and 70% of them are satisfied. Recently, the growth rate of healthcare expenditure, however, has been phenomenally rapid, owing to the ageing population, the economic development, the expansion of health insurance, the increased supply of healthcare resources, and the innovation of medical technology. Under the circumstance that the bill of raising the insurance premium rate could not be passed by the legislative congress, the Bureau of NHI (BNHI) was forced to economize on expense to achieve the financial balance. Currently, the BNHI implements ¡§total amount control¡¨ to control the total medical claimed payments of each medical healthcare provider. Facing the increasing volume of documentary auditing, the BNHI has to make its efforts on how to improve its auditing efficiency. This is also one of the purposes of this thesis. This study aimed to establish a reasonable and fair auditing procedure of medical claim payment, termed ¡§medical claim payments auditing (MCPA) procedure¡¨. At the stage of professional auditing, adopted the ¡§MIL-STD-105E sampling plan¡¨ to select data for professional audit and used the auditing results as a payment criterion. To verify the adaptability of the MCPA procedure, the researcher used the data provided by the institutes of Kaohsiung and Pintong as simulation objects. Further, the estimated cost model was adopted to increase the possibility of using this procedure. The MCPA procedure consists of the following characteristics: 1) The number of sampling is much lower than that of the current system used by the NHI, thus the audit labor-force and time can be reduced significantly. 2) The incentive mechanism design encourages the healthcare providers to honestly apply their medical claim payments and avoids inappropriate healthcare services. 3) Adopting international standards of sampling technology makes the MCPA procedure trustworthy and simultaneously can reduce the implementing obstructs. Keywords: National Health Insurance; Sampling plan; Incentive mechanism design

The application of stochastic modeling for learning the behavior of multibody dynamics models is investigated. The stochastic modeling technique is also known as Kriging or random function approach. Post-processing data from a simulation run is used to train the stochastic model that estimates the relationship between model inputs, such as the suspension relative displacement and velocity, and the output, for example, sum of suspension forces. Computational efficiency of Multibody Dynamics (MBD) models can be improved by replacing their computationally-intensive subsystems with stochastic predictions. The stochastic modeling technique is able to learn the behavior of a physical system and integrate its behavior in MBS models, resulting in improved real-time simulations and reduced computational effort in models with repeated substructures (for example, modeling a train with a large number of rail vehicles). Since the sampling plan greatly influences the overall accuracy and efficiency of the stochastic predictions, various sampling plans are investigated, and a space-filling Latin Hypercube sampling plan based on the traveling salesman problem (TPS) is suggested for efficiently representing the entire parameter space. The simulation results confirm the expected increased modeling efficiency, although further research is needed for improving the accuracy of the predictions. The prediction accuracy is expected to improve through employing a sampling strategy that considers the discrete nature of the training data and uses infill criteria that considers the shape of the output function and detects sample spaces with high prediction errors. It is recommended that future efforts consider quantifying the computation efficiency of the proposed learning behavior by overcoming the inefficiencies associated with transferring data between multiple software packages, which proved to be a limiting factor in this study. These limitations can be overcome by using the user subroutine functionality of SIMPACK and adding the stochastic modeling technique to its force library. / Ph. D.

c / Among the principal limitations of grain yield in soybean are the insect pests, especially the defoliating caterpillars and Sucking stink bugs grains. It is necessary to reveal and quantify these insects for proper decision-making according to pre-established control levels. So, for the implementation of appropriate management of these soybean insect pests, there is necessity of establishing a sampling plan that will permit the estimation of the population density of pests, effective, trusty and less time-consuming. This work aims to establish a sequential sampling plan for caterpillars and stink bugs soybean according to the sequential test of probability rates. Data were collected in two growing seasons (2010/2011 and 2012/2013). Were counted the number of small caterpillars (<1.5 cm) and large (> 1.5 cm) species Anticarsia gemmatalis (Hübner, 1818), Chrysodeixis includens (Walker, 1857) and Spodoptera eridania (Cramer, 1872) as well as stink bugs nymphs and adults of the species Piezodorus guildinii (Westwood, 1873), Nezara viridula (Linnaeus, 1758), Euschistus heros (Fabricius, 1794) Dichelops furcatus (Fabricius, 1775), Edessa meditabunda (Fabricius, 1794) and Chinavia sp. (Say, 1831) using the vertical cloth-to-beat in a grid of 154 sample points was marked with a 20 × 20 m spacement in area of 6.16 ha in soybean. The distribution of caterpillars, small and large in soybean is aggregated. According to the sequential sampling plans a sufficient number of sample units for soybean caterpillars assessment is 14. According to the sequential sampling plan sufficient number of samples for the evaluation of adult bugs in soybeans is 17. / Entre as principais limitações da produtividade de grãos na cultura de soja encontram-se os insetos-praga, destacando-se as lagartas desfolhadoras e os percevejos sugadores de grãos. É necessário amostrar e quantificar esses insetos para adequada tomada de decisão conforme níveis de controle pré-estabelecidos. Assim, para a implementação de manejo apropriado de insetos-praga em soja, há necessidade de estabelecer um plano de amostragem que permita a estimação da densidade populacional das pragas, eficaz e confiável e com menor dispêndio de tempo. Este trabalho tem por objetivo estabelecer um plano de amostragem sequencial para lagartas e percevejos na cultura de soja de acordo com o teste sequencial da razão de probabilidade. Os dados foram coletados em dois anos agrícolas (2010/2011 e 2012/2013). Foram contabilizados o número de lagartas pequenas (<1,5 cm) e grandes (>1,5 cm) das espécies Anticarsia gemmatalis (Hübner, 1818), Chrysodeixis includens (Walker, 1857) e Spodoptera eridania (Cramer, 1872), bem como percevejos ninfas e adultos das espécies Piezodorus guildinii (Westwood, 1873), Nezara viridula (Linnaeus, 1758), Euschistus heros (Fabricius, 1794) Dichelops furcatus (Fabricius, 1775), Edessa meditabunda (Fabricius, 1794) e Chinavia sp. (Say, 1831) por meio do método de amostragem pano-de-batida vertical em 154 pontos amostrais, espaçados de 20 m × 20 m, em área de 6,16 ha de soja. A distribuição de lagartas, pequenas e grandes na cultura da soja é agregada. De acordo com os planos de amostragem sequencial o número suficiente de unidades amostrais para avaliação de lagartas em soja é 14. De acordo com o plano de amostragem sequencial o número máximo de amostragens para a avaliação de percevejos adultos em soja é 17.