• Bulletin of the Korean Mathematical Society
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• v.50 no.2
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• pp.441-444
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• 2013

It is shown that any two-dimensional globally hyperbolic spacetime with noncompact Cauchy surfaces has no null cut points.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.2
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• pp.85-94
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• 1990

In automatic metal cuttings, the chip control is one of the serious problems. So the automatic detection of chip forms is essential to the chip control in automatic metal cuttings. Cutting experiments were carried out under the variety of cutting conditions (cutting speed, feed, depth of cut and tool geometry) and with workpiece made of steel (S45C), and cutting forces were measured in-processing by using a piezoelectric type Tool Dynamometer. In this report, the frequency analysis of dynamic components, the upper frequency distributions, the ratio of RMS values, the numbers of null point and the probability density were calculated from the dynamic componeents of cutting forces filtered through various band pass filters. Experimental results showed that computer chip form monitoring system based on the cutting forces was designed and simulated and that 6 type of chip forms could be detected while in-process machining.

• Nutrition Research and Practice
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• v.14 no.1
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• pp.20-24
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• 2020

BACKGROUND/OBJECTIVES: Malnutrition has multiple impacts on surgical success, postoperative complications, duration of hospital stay, and costs, particularly for cancer patients. There are various nutrition risk screening tools available for clinical use. Herein, we aim to determine the most appropriate nutritional risk screening system for esophageal cancer (EC) patients in China. SUBJECTS/METHODS: In total, 138 EC patients were enrolled in this study and evaluated by experienced nurses using three different nutritional screening tools, the Nutrition Risk Screening 2002 tool (NRS2002), the Patient-generated Subjective Globe Assessment (PG-SGA), and the Nutrition Risk Index (NRI).We compared sensitivity, specificity, positive and negative likelihood ratios, and Youden index generated by each of the three screening tools. Finally, cut-off points for all three tools were re-defined to optimize and validate the best nutritional risk screening tool for assessing EC patients. RESULTS: Our data suggested that all three screening tools were 100% sensitive for EC patients, while the specificities were 44.4%, 2.96%, and 59.26% for NRS 2002, PG-SGA, and NRI, respectively. NRI had a higher positive likelihood ratio as well as a higher area under the receiver operating characteristic curve compared to those of NRS 2002 and PG-SGA; although, all three tools had null negative likelihood ratios. After adjusting the cut-off points, the specificity and accuracy for all tools were significantly improved, however, the NRI remained the most appropriate nutritional risk screening system for EC patients. CONCLUSIONS: The NRI is the most suitable (highest sensitivity and accuracy) nutritional risk screening tool for EC patients. The performance of the NRI can be significantly improved if the cut-off point is modified according to the results obtained using MedCalc software.