• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• Journal of the korean academy of Pediatric Dentistry
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• v.39 no.2
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• pp.129-138
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• 2012

The aim of this in vitro study was to evaluate the effectiveness of experimental 2.26% fluoride-polyvinyl alcohol (F-PVA) tape in inhibition of enamel demineralization using enamel surface microhardness (SMH) analysis and scanning electron microscopy (SEM) examination. Enamel specimens (n=60) randomly assigned to four groups: control group, F-PVA tape group, fluoride varinish (F-varnish) group, casein phosphopeptide-amorphous calcium phosphate (CPP-ACFP) group. After topical application, pH-cycling was processed. Then, SMH was measured and the percentage loss of surface microhardness (%SML) was calculated. For the SEM examination, five sample specimens in each group were treated and the morphologic character was evaluated. After pH-cycling, the SMH values of the enamel specimens of F-PVA tape and F-varnish group were significantly higher than that of CPP-ACFP group, there was no significant difference between F-PVA tape and Fvarnish group. With SEM examination, enamel surfaces in the F-PVA tape group and F-varnish group showed numerous spherical and ovoid crystals formed on the enamel surface were also observed. The density of crystals was higher than that of both control group and CPP-ACFP group. F-PVA tape is effective in inhibition of enamel demineralization. Also, F-PVA tape's inhibition of enamel demineralization is comparable to that of F-vanish and greater than that of CPP-ACFP.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.754-761
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• 2008

As the automobile industry and technologies are developed, driver's tend to more concern about service matters than mechanical matters. For this reason, interests about recognition of human knowledge and emotion to make safe and convenient driving environment for driver are increasing more and more. recognition of human knowledge and emotion are emotion engineering technology which has been studied since the late 1980s to provide people with human-friendly services. Emotion engineering technology analyzes people's emotion through their faces, voices and gestures, so if we use this technology for automobile, we can supply drivels with various kinds of service for each driver's situation and help them drive safely. Furthermore, we can prevent accidents which are caused by careless driving or dozing off while driving by recognizing driver's gestures. the purpose of this paper is to develop a system which can recognize states of driver's emotion and attention for safe driving. First of all, we detect a signals of driver's emotion by using bio-motion signals, sleepiness and attention, and then we build several types of databases. by analyzing this databases, we find some special features about drivers' emotion, sleepiness and attention, and fuse the results through Multi-Modal method so that it is possible to develop the system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.675-686
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• 2005

In this paper, we propose an efficient face region detection technique for the content-based video summarization. To segment video, shot changes are detected from a video sequence and key frames are selected from the shots. We select one frame that has the least difference between neighboring frames in each shot. The proposed face detection algorithm detects face region from selected key frames. And then, we provide user with summarized frames included face region that has an important meaning in dramas or movies. Using Bayes classification rule and statistical characteristic of the skin pixels, face regions are detected in the frames. After skin detection, we adopt the projection method to segment an image(frame) into face region and non-face region. The segmented regions are candidates of the face object and they include many false detected regions. So, we design a classifier to minimize false lesion using CART. From SGLD matrices, we extract the textual feature values such as Inertial, Inverse Difference, and Correlation. As a result of our experiment, proposed face detection algorithm shows a good performance for the key frames with a complex and variant background. And our system provides key frames included the face region for user as video summarized information.

• Food Science and Preservation
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• v.16 no.1
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• pp.1-7
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• 2009

Watermelons (Citrulus vulgaris Schrad) are usually sorted manually by weight, appearance, and acoustic impulse, so grading of maturity and internal quality is subject to inaccuracies. It was necessary to develop a nondestructive evaluation technique of internal watermelon quality to reduce human error. Thus, acoustic characteristics related to internal quality factors were analyzed. Among these factors, three (ripeness, presence of an internal cavity, and blood-colored flesh) were selected for evaluation. The number of peaks and the sum of peak amplitudes for watermelons with blood-colored flesh were lower than for normal fruits. The portable evaluation system has an impact mechanism, a microphone sensor, a signal processing board, an LCD panel, and a battery. A performance test was conducted in the field. The internal quality evaluation model showed 87% prediction accuracy. Validation was conducted on 72 samples. The accuracy of quality evaluation was 83%. The quality of samples was evaluated by an inspector using conventional methods (hitting the watermelon and listening to the sounds), and then compared with prototype results. The quality evaluation accuracy of the prototype was better than that of the inspector. This nondestructive quality evaluation system could be useful in the field, warehouse, and supermarket

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.70-77
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• 2008

This paper proposes a new text candidate region detection method that uses genetic algorithm based on information of the segmented regions. In image segmentation, a classification of the pixels at each color channel and a reclassification of the region-unit for reducing inhomogeneous clusters are performed. EWFCM(Entropy-based Weighted C-Means) algorithm to classify the pixels at each color channel is an improved FCM algorithm added with spatial information, and therefore it removes the meaningless regions like noise. A region-based reclassification based on a similarity between each segmented region of the most inhomogeneous cluster and the other clusters reduces the inhomogeneous clusters more efficiently than pixel- and cluster-based reclassifications. And detecting text candidate regions is performed by genetic algorithm based on energy and variance of the directional edge components, the number, and a size of the segmented regions. The region information-based detection method can singles out semantic text candidate regions more accurately than pixel-based detection method and the detection results will be more useful in recognizing the text regions hereafter. Experiments showed the results of the segmentation and the detection. And it confirmed that the proposed method was superior to the existing methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.563-568
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• 2007

This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.456-462
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• 2008

The classification is that a new data is classified into one of given classes and is one of the most generally used data mining techniques. Memory-Based Reasoning (MBR) is a reasoning method for classification problem. MBR simply keeps many patterns which are represented by original vector form of features in memory without rules for reasoning, and uses a distance function to classify a test pattern. If training patterns grows in MBR, as well as size of memory great the calculation amount for reasoning much have. NGE, FPA, and RPA methods are well-known MBR algorithms, which are proven to show satisfactory performance, but those have serious problems for memory usage and lengthy computation. In this paper, we propose DPA (Dynamic Partition Averaging) algorithm. it chooses partition points by calculating GINI-Index in the entire pattern space, and partitions the entire pattern space dynamically. If classes that are included to a partition are unique, it generates a representative pattern from partition, unless partitions relevant partitions repeatedly by same method. The proposed method has been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory and FPA, and RPA.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.11a
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• pp.32-37
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• 1999

본 연구는 컨조인트 분석기법을 이용하여 의자의 물리적 적합도를 분석, 평가하여 사용자가 선호하는 최적의 의자를 제시하고자 하는데 목적이 있다. 컨조인트 분석기법은 Marketing 분야에서 주로 많이 쓰여온 분석 방법으로서 제품의 중요한 속성들을 찾아내어 다양한 종류의 제품들에 대한 고객의 선호도를 분석하는 방법이다. 이러한 컨조인트 분석기법은 제품개발과 평가의 측면에서 매우 큰 가능성이 있음에도 불구하고 마켓팅 이외의 분야에서는 거의 적용되자 않고 있는 실정이다. 따라서 본 연구에서는 의자의 물리적 적합성 연구에 이 컨조인트 분석을 이용하여 그 적용의 가능성을 알아보고자 하였다. 또한 이러한 적합성 연구에 컨조인트 분석기법이 타당한 분석기법인지 비교하기 위해 분산분석의 기법도 병행하여 실시하였다. 문헌 조사와 전문가 의견 수렴을 통하여 선행연구에서 추출된 의자의 물리적 적합도 요소인 안정성, 여유성, 적합성, 안락성등 4개의 적합도 요소를 채택하여 종속변수로 사용하였다. 또한 의자 자체의 설계 요소에 해당하는 휴먼인터페이스 요소(HIE)는 높이 조절 여부, 팔걸이 유무, Tilting 유무의 3가지 속성을 선택하여 독립변수로 사용하였다. 분석에 사용된 의자는 각 속성을 특징적으로 대표하는 8개의 의자들로서 구성하였고 63명의 피험자를 사용하여 실험하였다. 분석의 결과는 안정성에 가장 큰 영향을 주는 속성은 높이조절(HC)로서 남자와 여자 모두 높이조절 기능이 없을 때 안정성을 느낀다는 결과가 나왔다. 여유성에 영향을 주는 가장 큰 요인은 남자는 높이조절 기능이 있을 때, 여자는 팔걸이가 있을 때 여유성이 있다고 판단하였으며, 인체적합성에 영향을 주는 요인은 남자와 여자 모두 Tilting 기능이, 안락성에 영향을 주는 주요인은 남자는 Tilting 기능이 있을 매, 여자는 높이조절 기능이 있을 때인 것으로 나타났다.감, 강연성, 회복성, 수분특성, 밀도감이었으며, 요인들로 설명되는 누적분산값은 67.18%였다.주관적 평가의 결과와 객관적 평가 결과를 이용해 마직물의 태를 평가하는 산출식을 제시하였다. 태 평가치의 경우 16가지 특성치를 모두 넣는 방법과 stepwise 방법, 또 Kawabatark 사용한 순차적 군 회귀법의 세가지 방법의 회귀식 중 16가지 특성치를 모두 넣는 방법의 결정계수가 가장 높았다.tosterone농도는 107.7$\pm$12.0 pmol／l이었고, 남성의 타액내 농도는 274.2$\pm$22.1 pmol／l이었다. 이상의 결과로 보아 본 연구에서 정립된 EIA 방법은 RIA를 대신하여 소규모의 실험실에서도 활용할 수 있을 것으로 사려된다.또한 상실기 이후 배아에서 합성되며, 발생시기에 따라 그 영향이 다르고 팽창과 부화에 관여하는 것으로 사료된다. 더욱이, 조선의 ${\ulcorner}$구성교육${\lrcorner}$이 조선총독부의 관리하에서 실행되었다는 것을, 당시의 사범학교를 중심으로 한 교육조직을 기술한 문헌에 의해 규명시켰다.nd of letter design which represents -natural objects and was popular at the time of Yukjo Dynasty, and there are some documents of that period left both in Japan and Korea. "Hyojedo" in Korea is supposed to have been influenced by the letter design. Asite- is also considered to have been "Japanese Letter Jobcheso." Therefore, the purpose of

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.171-183
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• 2018

Despite the rapid expansion of satellite images supply, the application of imagery is often restricted due to unautomated image processing. This paper presents the automated process for the selection of training areas which are essential to conducting supervised image classification. The training areas were selected based on the prior and cover information. After the selection, the training data were used to classify land cover in an urban area with the latest image and the classification accuracy was valuated. The automatic selection of training area was processed with following steps, 1) to redraw inner areas of prior land cover polygon with negative buffer (-15m) 2) to select the polygons with proper size of area ($2,000{\sim}200,000m^2$) 3) to calculate the mean and standard deviation of reflectance and NDVI of the polygons 4) to select the polygons having characteristic mean value of each land cover type with minimum standard deviation. The supervised image classification was conducted using the automatically selected training data with Sentinel-2 images in 2017. The accuracy of land cover classification was 86.9% ($\hat{K}=0.81$). The result shows that the process of automatic selection is effective in image processing and able to contribute to solving the bottleneck in the application of imagery.