• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.593-596
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• 1999

In this paper, we propose an image retrieval system using the MBCM(Modified Borda Count method) in CME(Combining Multiple Experts). It combines color-, shape- and texture-based retrieval sub-systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment, our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.316-318
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• 1993

In order to estimation the optimum PID parameter of the turbine speed controller, the response cure of the object plant was compared with the reference pattern and then the magnitude peak value error and peak time error was calculated. With the calculated errors as input into the Fuzzy inference Method was introduced to propose the tuning method for each parameter. And the computer simulation was performed with the above Fuzzy inference method in which the Chunju hydro power plant turbine governor system was used as a model. This Study also aims to develop the exclusive tuner for govenor using industrial computer.

• School Mathematics
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• v.15 no.2
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• pp.459-479
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• 2013

The Purpose of this study was to explore the methods of generalization and errors pattern generated by mathematically gifted students and non-gifted students in elementary school. In this research, 6 problems corresponding to the x+a, ax, ax+c, $ax^2$, $ax^2+c$, $a^x$ patterns were given to 156 students. Conclusions obtained through this study are as follows. First, both group were the best in symbolically generalizing ax pattern, whereas the number of students who generalized $a^x$ pattern symbolically was the least. Second, mathematically gifted students in elementary school were able to algebraically generalize more than 79% of in x+a, ax, ax+c, $ax^2$, $ax^2+c$, $a^x$ patterns. However, non-gifted students succeeded in algebraically generalizing more than 79% only in x+a, ax patterns. Third, students in both groups failed in finding commonness in phased numbers, so they solved problems arithmetically depending on to what extent it was increased when they failed in reaching generalization of formula. Fourth, as for the type of error that students make mistake, technical error was the highest with 10.9% among mathematically gifted students in elementary school, also technical error was the highest as 17.1% among non-gifted students. Fifth, as for the frequency of error against the types of all patterns, mathematically gifted students in elementary school marked 17.3% and non-gifted students were 31.2%, which means that a majority of mathematically gifted students in elementary school are able to do symbolic generalization to a certain degree, but many non-gifted students did not comprehend questions on patterns and failed in symbolic generalization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.425-430
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• 2017

RFID is a technology that uses radio frequency to read information in tags attached to objects or people. Because it reads the information without contact when tracking the location using tags in a RFID system, there can be errors between the actual position and measured position. In this paper, three methods (the method of radiation pattern, the method of the median value, and the method using both the radiation pattern and median value) are proposed to identify the location of objects or people using the RFID technique. The location identification system based on RFID was constructed and tags were arranged in a square pattern. The real location and experimentally predicted location of an object containing a reader were compared to confirm the error. Instead of the existing papers that obtained the approximately location of a reader by calculating the center of gravity of all tags read by that reader, in this study, the predicted location was obtained by the median value and the radiation pattern. This study validated which method was the most efficient among the three methods proposed in this paper through the data of the read tags. As a result, the method of the median value had the smallest error among those assessed.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.317-331
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• 2004

Recently software agent has been studied as a new abstraction unit of software engineering. The agent with autonomous, adaptability and cooperation attribute is accepted as a new abstraction unit especially in distributed systems, open systems, and complex systems. However, the progress of agent research has been slow and the realization of agent programming language seems to be far distant. Because the properties of agent are diverse, the opinions of researchers can not converge to one. In this situation, software agent framework is accepted more realistic alternative solution. However the knowledge for its development doesn't have been shared among developers. So they often have to make same errors. We will help sharing of knowledge and experience by using pattern language which has been used in object technology for long times. This paper proposes a reactive agent framework pattern language and validates it based on ATAM［l］ The increase of such indirect experience can reduce the waste of resource by preventing the same try and error. So agent framework developers are able to concentrate on more essential issues. Finally quality of software agent framework will be increased.

• Journal of IKEEE
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• v.23 no.4
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• pp.1373-1380
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• 2019

In order to increase energy efficiency, developments of the advanced metering infrastructure (AMI) in the smart grid technology have recently been actively conducted. An essential part of AMI is analyzing power consumption and forecasting consumption patterns. In this paper, we analyze the power consumption and summarized the data errors. Monthly power consumption patterns are also analyzed using the k-means clustering algorithm. Forecasting the consumption pattern by each household is difficult. Therefore, we first classify the data into 100 clusters and then predict the average of the next day as the daily average of the clusters based on the deep neural network. Using practically collected AMI data, we analyzed the data errors and could successfully conducted power forecasting based on a clustering technique.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.333-344
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• 2021

Technique for the long-gap filling that occur frequently in ocean monitoring data is developed. The method estimates the unknown values of the long-gap by the summation of the estimated trend and selected residual components of the given missing intervals. The method was used to impute the data of the long-term missing interval of about 1 month, such as temperature and water temperature of the Ulleungdo ocean buoy data. The imputed data showed differences depending on the monitoring parameters, but it was found that the variation pattern was appropriately reproduced. Although this method causes bias and variance errors due to trend and residual components estimation, it was found that the bias error of statistical measure estimation due to long-term missing is greatly reduced. The mean, and the 90% confidence intervals of the gap-filling model's RMS errors are 0.93 and 0.35~1.95, respectively.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.407-419
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• 2022

The semiconductor fabrication process is complex and time-consuming. There are sometimes errors in the process, which results in defective die on the wafer bin map (WBM). We can detect the faulty WBM by finding some patterns caused by dies. When one manually seeks the failure on WBM, it takes a long time due to the enormous number of WBMs. We suggest a two-step approach to discover the probable pattern on the WBMs in this paper. The first step is to separate the normal WBMs from the defective WBMs. We adapt a hierarchical clustering for de-noising, which nicely performs this work by wisely tuning the number of minimum points and the cutting height. Once declared as a faulty WBM, then it moves to the next step. In the second step, we classify the patterns among the defective WBMs. For this purpose, we extract features from the WBM. Then machine learning algorithm classifies the pattern. We use a real WBM data set (WM-811K) released by Taiwan semiconductor manufacturing company.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.903-909
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• 2018

In this paper, performance analysis of machine vision techniques is presented to improve the convenience and speed of automatic inspection in the industrial field when machine vision is applied to the image not taken in the stationary state, but in the moving state on a conveyer. When the length of cylindrical rods used for automobiles was measured using the edge detection method, the conveying speed increased, and the uncertainty of the boundary between the background and the part image increased, which resulted in a shorter image of the object taken. This paper proposes a linear compensation method to predict the biased errors of the length measurements after examining the pattern of biased and random errors, respectively, with 6 different types of specimens and 7 velocity stages. The length measurement corrected by the linear compensation method had the same accuracy as the stationary state within the speed range of 30 cm/s and could enhance the application capability in automatic inspections.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.21-32
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• 2007

The households to be surveyed are usually huge number at the level of a city or metropolitan survey, not to mention a nationwide travel survey. Therefore, household travel surveys to figure out true origin-destination (O/D) trip patterns (population O/D) are conducted through a sampling method rather than by surveying all of the population in the system. Therefore, the population O/D pattern can only be estimated by expanding the sampled O/D patterns to the population. It is very difficult to avoid the errors involved in the process of sampling, surveying and expanding O/D data. In order to minimize such errors while estimating the true O/D patterns of the population, the validation and adjustment process should employed by doing a comparison between the expanded sample O/D data and observed link traffic volumes. This study suggests a method of validation and adjustment of the expanded sample O/D data by comparing observed link volumes at several screenlines. The study also suggests a practical technique to modify O/D pairs which are excluded in the screenline validation process by comparing observed traffic volume with the results of traffic assignment analysis. An empirical study was also conducted as an example applying the suggested methods of validation and adjustment with Korea's nationwide O/D data and highway network.