• Journal of the Semiconductor & Display Technology
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• v.14 no.1
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• pp.7-11
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• 2015

In this paper, an automatic focusing method has been proposed for speedy and reliable measurement and inspection in industry. It is very difficult to determine focusing step size and moving direction in one camera autofocusing. The proposed method can improve speed and accuracy of focusing by using the optical axis interval of two cameras, which is automatically set up as focusing step size. Also, it can determine moving direction from focus value comparisons of two cameras, and then solve ambiguity of one camera focusing. Its performance is verified by experiments. It is expected that it can apply to optical system for measurement and inspection in industry fields.

• Communications for Statistical Applications and Methods
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• v.17 no.5
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• pp.689-696
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• 2010

Interval-censored data are commonly found in studies of diseases that progress without symptoms, which require clinical evaluation for detection. Several techniques have been suggested with independent assumption. However, the assumption will not be valid if observations come from clusters. Furthermore, when the cluster size relates to response variables, commonly used methods can bring biased results. For example, in a study on lymphatic filariasis, a parasitic disease where worms make several nests in the infected person's lymphatic vessels and reside until adulthood, the response variable of interest is the nest-extinction times. Since the extinction times of nests are checked by repeated ultrasound examinations, exact extinction times are not observed. Instead, data are composed of two examination points: the last examination time with living worms and the first examination time with dead worms. Furthermore, as Williamson et al. (2008) pointed out, larger nests show a tendency for low clearance rates. This association has been denoted as an informative cluster size. To analyze the relationship between the numbers of nests and interval-censored nest-extinction times, this study proposes a joint model for the relationship between cluster size and clustered interval-censored failure data.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.435-443
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• 2010

When testing systems that incorporate probabilistic behavior, it is necessary to apply test inputs a number of times in order to give a test verdict. Interval estimation can be used to assert the correctness of probabilities where the selection of confidence interval is one of the important issues for quality of testing. The Wald interval has been widely accepted for interval estimation. In this paper, we compare the Wald interval and the Agresti-Coull interval for various sizes of samples. The comparison is carried out based on the test pass probability of correct implementations and the test fail probability of incorrect implementations when these confidence intervals are used for probability testing. We consider two-sided confidence intervals to check if the probability is close to a given value. Also one-sided confidence intervals are considered in the comparison in order to check if the probability is not less than a given value. When testing probabilities using two-sided confidence intervals, we recommend the Agresti-Coull interval. For one-sided confidence intervals, the Agresti-Coull interval is recommended when the size of samples is large while either one of two confidence intervals can be used for small size samples.

• Journal of Gastric Cancer
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• v.12 no.3
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• pp.164-172
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• 2012

Purpose: The purpose of this study is to investigate the prognostic significance of tumor size for 5-year survival rate in patients with gastric cancer. Materials and Methods: A total of 1,697 patients with gastric cancer, who underwent potentially curative gastrectomy, were evaluated. Patients were divided into 4 groups as follows, according to the median size of early and advanced gastric cancer, respectively: small early gastric cancer (tumor size ${\leq}3$ cm), large early gastric cancer (tumor size >3 cm), small advanced gastric cancer (tumor size ${\leq}$ 6 cm), and large advanced gastric cancer (tumor size >6 cm). The prognostic value of tumor size for 5-year survival rate was investigated. Results: In a univariate analysis, tumor size is a significant prognostic factor in advanced gastric cancer, but not in early gastric cancer. Multivariate analysis showed that tumor size is an independent prognostic factor for 5-year survival rate in advanced gastric cancer (P=0.003, hazard ratio=1.372, 95% confidence interval=1.115~1.690). When advanced gastric cancer is subdivided into 2 groups, according to serosa invasion: Group 1; serosa negative (T2 and T3, 7th AJCC), and Group 2; serosa positive (T4a and T4b, 7th AJCC), tumor size is an independent prognostic factor in Group 1 (P=0.011, hazard ratio=1.810, 95% confidence interval=1.149~2.852) and in Group 2 (P=0.033, hazard ratio=1.288, 95% confidence interval=1.020~1.627), respectively. Conclusions: Tumor size is an independent prognostic factor in advanced gastric cancer irrespective of the serosa invasion, but not in early gastric cancer.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.107-108
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• 2016

Our study proposes the methods of distinguishing vehicle types using the interval and size of the car. The car videos converts the basic RGB model to Gray model for use and through Canny Edge Direction, it eliminates the background of the car while obtaining feature points through the detection of contours.

• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.18-30
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• 2000

Recent studies have shown that the $\bar{X}$ chart with variable sampling intervals(VSI) and the $\bar{X}$ chart with variable sample size(VSS) are much quicker than Shewhart $\bar{X}$ chart in detecting shiks in the process. Shewhart $\bar{X}$ chart has been beneficial to detect large shifts but it is hard to apply Shewhart $\bar{X}$ chart in detecting moderate shifts in the process mean. In this article the $\bar{X}$ chart using variable sample size(VSS) and variable sampling Intervals(VSI) has been proposed to supplement the weak point mentioned above. So the purpose of this paper is to consider finding the design parameters which minimize expected loss costs for unit process time and measure the performance of VSSI(variable sample size and sampling interval) $\bar{X}$ chart. It is important that assignable causes be detected to maintain the process controlled. This paper has been studied under the assumption that one cycle is from starting of the process to eliminating the assignable causes in the process. The other purpose of this article is to represent the expected loss costs in one cycle with three process parameters(sample size, sampling interval and control limits) function and find the three parameters.

• Fashion & Textile Research Journal
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• v.10 no.6
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• pp.966-978
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• 2008

The aim of this study was to provide size intervals in hand requisite in design of gloves. In this study, a survey was administered to gather information about glove manufacturers' sizing systems. In addition, KS glove standards' size dimensions were analyzed. As well, the ISO hand sizing system was also studied. Based on all the analyses' results, a new glove size intervals were composed. The size comprised the control dimensions of hand length and hand circumference. The size interval was 8mm in hand length and 13mm in hand circumference. The size range was established by making the coverage above 80%. The coverage of the new size interval system for an adult's hand was 86.4% and 13 sizes were suggested. The coverage of the male size system was 86.0% and 10 sizes were suggested. The coverage of the female size system was 87.6% and 8 sizes were suggested. For the unfitted gloves, size ranges based on hand length and hand circumference were developed. For the adults group, S, M, L, and XL were suggested and the coverage of the new size range was 78.8%. For the male group, S, M, and L were suggested and the coverage was 82.3%. For the female group, S, M, and L were also suggested and the coverage was 81.3%.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.551-562
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• 1995

We consider the iterated bootstrap method in regression model with heterogeneous error variances. The iterated wild bootstrap confidence intervla of the mean response is considered. It is shown that the iterated wild bootstrap confidence interval has coverage error of order $n^{-1}$ wheresa percentile method interval has an error of order $n^{-1/2}$. The simulation results reveal that the iterated bootstrap method calibrates the coverage error of percentile method interval successfully even for the small sample size.

• Journal of the Korean Home Economics Association
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• v.43 no.9 s.211
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• pp.175-191
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• 2005

This paper proposed a sizig system for men's jackets in order to improve the clothing fitness and rain the productivity. The sizing system was classified according to 3 age groups. Figure types were categorized by shoulder angle and body shape. The size interval of the basic dimensions was established at regular intervals centering around their means. Altogether, 15 size charts were developed based on the frequency distribution. Size designating measurements for jackets were height, chest girth and waist girth. Size intervals were 3cm for chest and waist girth, 5m for height, and 2cm for waist and hip girth. Considering the cover factor, charts with a limited number of sizes were suggested with necessary measurements for each figure type of each age group.

• Journal of Internet Computing and Services
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• v.4 no.6
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• pp.13-24
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• 2003

Grid technology requires use of geographically distributed resources from multiple domains. Resource monitoring services or tools consisting sensors or agents will run on many systems to find static resource information (such as architecture vendor, OS name and version, MIPS rate, memory size, CPU capacity, disk size, and NIC information) and dynamic resource information (CPU usage, network usage(bandwidth, latency), memory usage, etc.). Thus monitoring itself may cause system overhead. This paper proposes the optimal monitoring interval to reduce the cost of monitoring services and the dynamic monitoring interval to measure monitoring events accurately. By employing two features, we find out unnecessary system overhead is significantly reduced and accuracy of events is still acquired.