• International Journal of Precision Engineering and Manufacturing
• /
• v.1 no.1
• /
• pp.111-117
• /
• 2000

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. This paper models the thermal errors for error analysis and develops an on-the-machine measurement system by which the volumetric errors are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses and a designed spherical ball artifact (SBA). Experiments show that the developed system provides a high measuring accuracy, with repeatability of $\pm$2$\mu\textrm{m}$ in X, Y and Z directions. It is believed that the developed measurement system can be also applied to the machine tools with CNC controller. In addition, machining accuracy and product quality can be also improved by using the developed measurement system when the spherical ball artifact is mounted on a modular fixture.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.32 no.1
• /
• pp.61-75
• /
• 2007

The purpose of this paper is to develop a new group classification method based on genetic algorithm and to com-pare its prediction performance with those of existing methods in the area of bond rating. To serve this purpose, we conduct various experiments with pilot and general models. Specifically, we first conduct experiments employing two pilot models : the one searching for the cluster center of each group and the other one searching for both the cluster center and the attribute weights in order to maximize classification accuracy. The results from the pilot experiments show that the performance of the latter in terms of classification accuracy ratio is higher than that of the former which provides the rationale of searching for both the cluster center of each group and the attribute weights to improve classification accuracy. With this lesson in mind, we design two generalized models employing genetic algorithm : the one is to maximize the classification accuracy and the other one is to minimize the total misclassification cost. We compare the performance of these two models with those of existing statistical and artificial intelligent models such as MDA, ANN, and Decision Tree, and conclude that the genetic algorithm-based group classification method that we propose in this paper significantly outperforms the other methods in respect of classification accuracy ratio as well as misclassification cost.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.6
• /
• pp.1955-1960
• /
• 2010

A performance of CNC 3-axis pipe profile-cutting machine we developed was evaluated by measuring and verifying a positioning accuracy of its feeding unit and a cutting shape accuracy of pipe workpiece. The positioning accuracy was verified by comparing moving distance actuated by PLC motion controller with actual one measured by a laser interferometer. The cutting shape accuracy was also verified by comparing a cutting shape obtained through scanning and 3D modeling the pipe workpiece with that through CL data.

• Journal of Institute of Convergence Technology
• /
• v.9 no.1
• /
• pp.31-36
• /
• 2019

After 30 years of KKP model analysis and extended 30 years of accuracy analysis, the unique correlation and various problems between measured horizontal surface insolation and measured weather data are found in this paper. The KKP model's 10yrs daily total horizontal surface insolation forecasting was averaged about 97.7% on average, and the forecasting accuracy at peak times per day was about 92.1%, which is highly applicable regardless of location and weather conditions nationwide. The daily total solar radiation forecasting accuracy of the modified KKP cloud model was 98.9%, similar to the KKP model, and 93.0% of the forecasting accuracy at the peak time per day. And the results of evaluating the accuracy of calculation for 30 years of KKP model were cloud model 107.6% and cloud model 95.1%. During the accuracy analysis evaluation, this study found that inaccuracies in measurement data of cloud cover should be clearly assessed by the Meteorological Administration.

• Journal of Computing Science and Engineering
• /
• v.5 no.4
• /
• pp.294-304
• /
• 2011

Enhancing continuous queries over data streams with temporal functions and predicates enriches the expressive power of those queries. While traditional continuous queries retrieve only the values of attributes, temporal continuous queries retrieve the valid time intervals of those values as well. Correctly evaluating such queries requires the coalescing of adjacent timestamps for value-equivalent tuples prior to evaluating temporal functions and predicates. For many stream applications, the available computing resources may be too limited to produce exact query results. These limitations are commonly addressed through load shedding and produce approximated query results. There have been many load shedding mechanisms proposed so far, but for temporal continuous queries, the presence of coalescing makes theses existing methods unsuitable. In this paper, we propose a new accuracy metric and load shedding algorithm that are suitable for temporal query processing when memory is insufficient. The accuracy metric uses a combination of the Jaccard coefficient to measure the accuracy of attribute values and $\mathcal{PQI}$ interval orders to measure the accuracy of the valid time intervals in the approximate query result. The algorithm employs a greedy strategy combining two objectives reflecting the two accuracy metrics (i.e., value and interval). In the performance study, the proposed greedy algorithm outperforms a conventional random load shedding algorithm by up to an order of magnitude in its achieved accuracy.

• Journal of Sasang Constitutional Medicine
• /
• v.19 no.1
• /
• pp.60-77
• /
• 2007

1. Objectives This is the comparative study with hand-operated measurement method and Automatic measurement method, in order to convert the automatic measurement method. 2. Methods We measured the body of patients(hand-operated Width 5 Places and hand-operated circumference 8 place,Automatic Width 5 and automatic circumference 8 place by 3D body measuring instrument) and analyzed the anthropometric data divding into sex&age. 362 patient's data are used in the analysis. 3. Results and Conclusions 1) 1th circumference variable which standing was not a sasang constitutional difference. 2) Diagnostic accuracy rate of the body measurement was 50-80%. 3) Diagnostic accuracy rate of man is higher than Diagnostic accuracy rate of women 4) Diagnostic accuracy rate of Automatic & hand-operated measuring was not a big difference.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1211-1215
• /
• 2005

In the GPS attitude determination system, the baseline length constraints can be used efficiently to reduce the search space. It is possible by adopting the assumptions that the baseline length doesn't change and the true baseline length is precisely known. But in real situation, the baseline length might be changed by many reasons and it is impossible to measure the true baseline length because there exists measurement error and antenna phase centre movement. In order to analyze the effect of the baseline length accuracy, one needs to know the relation between the accuracy of the baseline length and success rates of the integer ambiguity resolution. In this paper, the effect of the baseline length accuracy to the integer ambiguity resolution in the attitude determination system is analyzed by empirical method. The results show that the margins in the baseline length accuracy is less than a few cm which implies that one should take great cares when applying the attitude determination system to the flexible structures.

• Phonetics and Speech Sciences
• /
• v.5 no.3
• /
• pp.63-69
• /
• 2013

The purpose of this study was to evaluate the maximum and optimal listening speed of Korean TTS for the blind. Five blind participants took part in this study. The instruments used in this study were 17 sentence sets (2 sets for an excercise, 10 sets for a repeated test, and 5 sets for a random test), with short meaningful sentences (the same sentences for the repeated test, different sentences for the random test) with 15 differentiated speeds (Range=0.8-3.6, SD=0.2). Each participant's maximum and quickest listening speeds were calculated by objective recall accuracy (determined by the number of correctly recalled syllables/the total number of syllables in a sentence X 100) and subjective recall accuracy (recall accuracy judged by each participant's subjective evaluation). The results showed that the participants' recall accuracy had a tendency to increase as the TTS speed decreased. Participants' subjective recall accuracy was higher than objective recall accuracy in the repeated tests and vice versa in the random tests. The results also revealed that the participants' sentence familiarity had an influence on their Korean TTS listening speed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.5143-5158
• /
• 2018

Improving the intrusion detection system (IDS) is a pressing need for cyber security world. With the growth of computer networks, there are constantly daily new attacks. Machine Learning (ML) is one of the most important fields which have great contribution to address the intrusion detection issues. One of these issues relates to the imbalance of the diverse classes of network traffic. Accuracy paradox is a result of training ML algorithm with imbalanced classes. Most of the previous efforts concern improving the overall accuracy of these models which is truly important. However, even they improved the total accuracy of the system; it fell in the accuracy paradox. The seriousness of the threat caused by the minor classes and the pitfalls of the previous efforts to address this issue is the motive for this work. In this paper, we consolidated stratified sampling, cost function and weighted Support Vector Machine (WSVM) method to address the accuracy paradox of ID problem. This model achieved good results of total accuracy and superior results in the small classes like the User-To-Remote and Remote-To-Local attacks using the improved version of the benchmark dataset KDDCup99 which is called NSL-KDD.

• Journal of Korean Academy of Nursing Administration
• /
• v.17 no.2
• /
• pp.189-197
• /
• 2011

Purpose: This study was an analysis of the relationship between perception for appraisal of staff nurses in operating rooms and performance and organizational commitment. Method: The survey was conducted with 176 staff nurses in operating rooms in 2 hospitals in Seoul. Data were analyzed using frequency, one-way ANOVA, Pearson correlation analysis, and stepwise multiple regression. Result: 1. Perception for appraisal including accuracy and justice was significantly related to organizational commitment (r=.496, P=.000). Perception for appraisal including accuracy and justice was slightly related to performance (r=.220, P=.003). 2. In order to determine the percentage of the variance of performance and organizational commitment that could be predicted by perception for appraisal, perception for appraisal was entered in the regression equation. Accuracy accounted for 25% of the variance in the organizational commitment. To determine the percentage of the variance of performance that could be predicted by perception for appraisal and organizational commitment, the perception for appraisal and organizational commitment were entered in the regression equation. Organizational commitment accounted for 21% of the variance in the performance. Consequently accuracy predicted organizational commitment. Organizational commitment predicted performance. Conclusions: Findings indicate the need to increase accuracy of performance appraisal to promote organizational commitment and performance in perioperative nurses.