A two-level structure for advanced space power system automation

The tasks to be carried out during the three-year project period are: (1) performing extensive simulation using existing mathematical models to build a specific knowledge base of the operating characteristics of space power systems; (2) carrying out the necessary basic research on hierarchical control structures, real-time quantitative algorithms, and decision-theoretic procedures; (3) developing a two-level automation scheme for fault detection and diagnosis, maintenance and restoration scheduling, and load management; and (4) testing and demonstration. The outlines of the proposed system structure that served as a master plan for this project, work accomplished, concluding remarks, and ideas for future work are also addressed

Distributed control design for underwater vehicles

The vast majority of control applications are based on non-interacting decentralized control designs. Because of their single-loop structure, these controllers cannot suppress interactions of the system. It would be useful to tackle the undesirable effects of the interactions at the design stage. A novel model predictive control scheme based on Nash optimality is presented to achieve this goal. In this algorithm, the control problem is decomposed into that of several small-coupled mixed integer optimisation problems. The relevant computational convergence, closed-loop performance and the effect of communication failures on the closed-loop behaviour are analysed. Simulation results are presented to illustrate the effectiveness and practicality of the proposed control algorithm

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method

The development of case-based learning for an antenna engineering course using folklore

Several subjects, including antenna engineering in a communication engineering program, is a math-intensive subject where most students say that it is difficult to understand and visualize. Students are unable to relate theoretical knowledge to real world applications. To overcome this issue, we proposed to motivate students’ curiosity using fun and interesting ways of teaching based on real cases in the community. In an antenna engineering course, there are folklores that performance of an antenna can be improved by attaching items such as basins to the antenna or using everyday objects as an antenna. Theoretical explanations have not been developed yet. In this research, we aim to propose the idea of using folklores as a case-based learning (CBL) exercise. Based on the process of CBL, a 15-week course plan starts with establishing the case in the first week, followed by weeks of theoretical study, lectures and group discussions. Group discussions on the case are established on the 5th and the 10th weeks to share the problems and the new findings. The results of the study are presented in the 15th week. Impressively, the pre-evaluating result shows that 97.5% of students who never attend an antenna engineering class were interested in joining the challenge. The proposed idea will be applied in an antenna engineering course for 4th year students in communication engineering, at the University of Phayao, in the first semester of the 2017 academic year in August 2017

พฤติกรรมการใช้ยาปฏิชีวนะของผู้ใช้บริการห้องพยาบาล มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ วิทยาเขตปราจีนบุรี

The objective of this research is to investigate 1) personal characteristics, 2) knowledge about antibiotics and use of antibiotics, 3) supportive factors affecting antibiotic use, 4) antibiotics use behaviors and 5) factors associated with behaviors of antibiotic usage among patients at KMUTNB Prachinburi Campus. The sample was 400 clients in the nursing room at King Mongkut's University of Technology North Bangkok Prachinburi Campus. The main research instrument included a questionnaire. Statistics used for data analysis were percentage, average, standard deviation and chisquare test. The results of the study revealed that 1) Most of the informants were female students with an average age of 21 years from Faculty of Technology and Industrial Management. Their highest education level was undergraduate degree. For the household monthly income, it was more than 25,000 baht, 2) Regarding the level of their knowledge about antibiotics, it was at low level, 3) The scores of the antibiotic use behaviors were at the moderate level, 4) The scores of the factors supporting antibiotic use behaviors were at the moderate level, 5) Factors associated with behaviors of antibiotics were knowledge about antibiotics and supportive factors affecting antibiotic use. According to the findings from this research, it can be recommended that the relevant agencies and departments should arrange a campaign or a project to raise people’s awareness on the use of antibiotics. Also, agencies and departments should provide advice about how to search for the information about antibiotics from reliable sources on the Internet

The study of prevalence and factors affecting Anaplasma maginale infection in domestic goats in Chonburi province, Thailand

The objective of this study was to determine the prevalence and factors affecting Anaplasma marginale infection of goat farming in Chonburi province, Thailand. A total of 182 samples were collected from clinical services records from the Veterinary Teaching Hospital, Rajamangala University of Technology Tawan-ok. Moreover, the potential risk factors of A. marginale infection, including vectors infestation, barn-types, preventive medicine protocols using vector-control agents and/or deworming programs, and the farming areas were statistically analyzed. The results revealed that 24.7% of goats were positive for A. marginale infection. The Nhong Yai district had the highest infection rate at 34.1% (15/44). The Mueng, Chonburi and Sri Racha district goats were infected at the rate of 27.5% (11/40) and 24.3% (9/37), respectively. The potential significant factors affecting A. marginale infection were vectors infestation (P < 0.01) and preventive medicine protocols using vector-control agents and/or deworming programs (P < 0.05). In conclusion, the vectors infestation increases the chance of A. marginale infection. Conversely, appropriate consistent preventive medical health management by application of vector-control agents and/or deworming programs can reduce the likelihood of infection. Our study could serve as a guideline for prevention planning and for further study of livestock rearing behavior concerning infection of blood parasites in nearby area

Surrogate model-based strategy for cryogenic cavitation model validation and sensitivity evaluation

The study of cavitation dynamics in cryogenic environment has critical implications for the performance and safety of liquid rocket engines, but there is no established method to estimate cavitation-induced loads. To help develop such a computational capability, we employ a multiple-surrogate model-based approach to aid in the model validation and calibration process of a transport-based, homogeneous cryogenic cavitation model. We assess the role of empirical parameters in the cavitation model and uncertainties in material properties via global sensitivity analysis coupled with multiple surrogates including polynomial response surface, radial basis neural network, kriging, and a predicted residual sum of squares-based weighted average surrogate model. The global sensitivity analysis results indicate that the performance of cavitation model is more sensitive to the changes in model parameters than to uncertainties in material properties. Although the impact of uncertainty in temperature-dependent vapor pressure on the predictions seems significant, uncertainty in latent heat influences only temperature field. The influence of wall heat transfer on pressure load is insignificant. We find that slower onset of vapor condensation leads to deviation of the predictions from the experiments. The recalibrated model parameters rectify the importance of evaporation source terms, resulting in significant improvements in pressure predictions. The model parameters need to be adjusted for different fluids, but for a given fluid, they help capture the essential fluid physics with different geometry and operating conditions. Copyright © 2008 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/61228/1/1779_ftp.pd

A multi-objective model for inventory and planned production reassignment to committed orders with homogeneity requirements

[EN] Certain industries are characterized by obtaining non-homogeneous units of the same product. However, customers require homogeneity in some attributes between units of the same and different products requesting in their orders. To commit such orders, an estimation of the homogeneous product to be obtained can be used. Unfortunately, estimations of homogenous product quantities can differ considerably from real distributions. This fact could entail the impossibility of accomplishing the delivery of customer orders in the terms previously committed. To solve this, we propose a multi-objective mathematical programming model to reallocate already available homogeneous products in stock and planned production to committed orders. The main contributions of this model are the consideration of the homogeneity requirement between units of different lines of the same order, the allowance of partial deliveries of order lines, and the specification of some relevant attributes of products to accomplish with the customer homogeneity requirement. Different hypotheses are proved through experiments and statistical analyses applied to a ceramic tile company. The epsilon-constraint method is used to obtain an implementable solution for the company. The weighted sum method is used when proving other hypotheses that offer some managerial insights to companies.This work was supported by the Program of Formation of University Professors (FPU) of the Spanish Ministry of Education, Culture and Sport (FPU15/03595), and by the Spanish Ministry of Economy and Competitiveness Project DPI2011-23597.Esteso, A.; Alemany Díaz, MDM.; Ortiz Bas, Á.; Peidro Payá, D. (2018). A multi-objective model for inventory and planned production reassignment to committed orders with homogeneity requirements. Computers & Industrial Engineering. 124:180-194. https://doi.org/10.1016/j.cie.2018.07.025S18019412