• Journal of the Korean Society for information Management
• /
• v.24 no.4
• /
• pp.267-283
• /
• 2007

In this study, measures of distributional similarity such as KL-divergence are applied to cluster documents instead of traditional cosine measure, which is the most prevalent vector similarity measure for document clustering. Three variations of KL-divergence are investigated; Jansen-Shannon divergence, symmetric skew divergence, and minimum skew divergence. In order to verify the contribution of distributional similarities to document clustering, two experiments are designed and carried out on three test collections. In the first experiment the clustering performances of the three divergence measures are compared to that of cosine measure. The result showed that minimum skew divergence outperformed the other divergence measures as well as cosine measure. In the second experiment second-order distributional similarities are calculated with Pearson correlation coefficient from the first-order similarity matrixes. From the result of the second experiment, secondorder distributional similarities were found to improve the overall performance of document clustering. These results suggest that minimum skew divergence must be selected as document vector similarity measure when considering both time and accuracy, and second-order similarity is a good choice for considering clustering accuracy only.

• Journal of IKEEE
• /
• v.14 no.3
• /
• pp.224-231
• /
• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.27 no.10
• /
• pp.68-77
• /
• 1990

In this paper, a neural patten recognition method for the automatic circuit diagram reading system is proposed. The proposed procedure to recognize a deformed logic symbols is composed of three stages: feature detection, log mapping, and pattern classification. In the feature detection stage, a modified competitive learning algorithm where each pattern has the inhibition weight as well as the activation weight is developed. The global information of hand-written logic symbols is obtained by the feature detection neural network having both the inhibition and activation weights. The obtained global data is then transformed into a log space by the conformal mapping where according to the Schwartz's theory about the human visual signal process-ing, the degree of rotation and the scale change are mapped into the translation change. Logic symbols are finally classified by a three layer perceptron trained by the error back propagation algorithm. The computer simulation demonstrates that the proposed multistage neural network system can recognize well the deformed patterns of hand-written logic circuit diagrams.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.36C no.12
• /
• pp.90-97
• /
• 1999

Recently, there have been many researches to automate processing and analysing image data in medical field, due to the advance of image processing techniques, the fast communication network and high performance hardware. In this paper, we design and implement the system based on the multi-layer neural network model to be able to analyze, differentiate and count blood cells in the peripheral blood image. To do these, we segment red and white-blood cell in blood image acquired from microscope with CCD(Charge-coupled device) camera and then apply the various feature extraction algorithms to classify. In addition to, we reduce multi-variate feature number using PCA(Principle Component Analysis) to construct more efficient classifier. So, in this paper, we are sure that the proposed system can be applied to a pathological guided system.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.11
• /
• pp.6533-6535
• /
• 2013

Background: The purpose of this study was to evaluate a new type of tumor biomarker, eukaryotic elongation factor 2 (eEF2), in serum for the early diagnosis, confirmative diagnosis as well as assessment of treatment of non-small cell lung cancer (NSCLC). Methods: 130 patients with NSCLC and 50 healthy individuals undergoing physical examination in our hospital provided the observation and healthy control groups. An enzyme linked immune sorbent assay (ELISA) method was applied to determine serum eEF2 levels. Serum neuron specific enolase (NSE) and squamous cell carcinoma antigen (SCC) levels in the observation group were assessed with an automatic biochemical analyzer. Results: The median levels of eEF2 in the serum of NSCLC patients was found to be significantly higher than the healthy control group (p < 0.01) and it was markedly higher in stages III, IV than stages I, II (p < 0.05). eEF2 was higher with tumor size ${\geq}2$ cm than <2 cm (P< 0.01). Furthermore, two weeks after surgery patients showed a significant trend for eEF2 decrease (p < 0.05). Conclusions: The eukaryotic elongation factor 2 (eEF2) has certain clinical values for early diagnosis, verification, and prognosis as well as classification of lung cancer patients.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.6
• /
• pp.88-100
• /
• 1998

In this paper, an algorithm for a real-time automatic fingerprint identification system is proposed. The fingerprint feature volume is extracted by considering distinct and local characteristics(such as intensity and image quality difference etc.) in fingerprint images, which makes the algorithm properly adaptive to various image acquisitionj methods. Also the matching technique is designed to be invariant on rotation, scaling and translation (RST) changes while being capable of real-time processing. And the classification of fingerprints is performed based on the ridge flow and the relations among singular points such as cores and deltas. The developed fingerprint identification algorithm has been applied to various sets of fingerprint images such as one from NIST(National Institute of Standards and Technology, USA), a pressed fingerprint database constructed according to Korean population distributions in sex, ages and jobs, and a set of rolled-than-scanned fingerprint images. The overall performance of the algorithm has been analyzed and evaluated to the false rejection ratio of 0.07% while holding the false acceptance ratio of 0%.

• Special Issue of the Society of Naval Architects of Korea
• /
• 2006.09a
• /
• pp.112-121
• /
• 2006

The vertical displacement of a ship on the basis of the sea level is an important parameter for its stability and control. To indicate the displacement on operating conditions, "draft marks" are carved on the hull of the ship in various ways. One of the methods is welding. The position, shape and size of the marks are specified on the shipbuilding rules by classification societies to be checked by shipbuilders. In most cases, high-skilled workers do the welding along the drawing for the marks and welding bead becomes the marks. But the inaccuracies due to human errors and high labor cost increase the needs for automating the work process of the draft marks. In the preceding work, an indoor robot was developed for automatic marking system on flat surfaces and the work proved that the robot welding was more effective and accurate than manual welding. However, many parts of the hull structure constructed at the outdoor are cowed shapes, which is beyond the capability of the robot developed for the indoor works on the flat surface. The marking on the curved steel surface requiring the 25m elevations is one of the main challenges to the conventional robots. In the present paper, the robot capable of climbing vertical curved steel surfaces and performing the welding at the marked position by effectively solving the problems mentioned earlier is presented.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.10
• /
• pp.25-33
• /
• 2012

In this paper, we propose a rule-based model to correct errors in a speech recognition result in the mobile device environment. The proposed model considers the mobile device environment with limited resources such as processing time and memory, as follows. In order to minimize the error correction processing time, the proposed model removes some processing steps such as morphological analysis and the composition and decomposition of syllable. Also, the proposed model utilizes the longest match rule selection method to generate one error correction candidate per point, assumed that an error occurs. For the purpose of deploying memory resource, the proposed model uses neither the Eojeol dictionary nor the morphological analyzer, and stores a combined rule list without any classification. Considering the modification and maintenance of the proposed model, the error correction rules are automatically extracted from a training corpus. Experimental results show that the proposed model improves 5.27% on the precision and 5.60% on the recall based on Eojoel unit for the speech recognition result.

• Journal of Environmental Science International
• /
• v.19 no.3
• /
• pp.281-293
• /
• 2010

The present study explores time and spatial thermal environment for Daegu, which is a city built on a basin area, according to varying land cover conditions of the earth's surface by analyzing data derived from meteorological observation and satellite images. The study has classified land use by utilizing MODIS satellite images and analyzed land surface temperature. Also, by using data acquired from automatic weather system, the study has evaluated the effects of atmospheric heating caused by city pavements by analyzing the sensible heat flux between the city's land surface and the atmosphere. The results are as follows. 1) Classification of land use in the Daegu area shows 46.64% of urban and built-up area, 1.39% of watersides, 35.19% of forest, 11.43% of crops, and 5.37% grasslands. 2) During the weekdays throughout the year, the land surface temperature was high for Dalseogu, Bukgu, and Seogu regions where industrial complexes could be found. Comparatively, lower temperature could be observed in the woodlands. 3) While the land surface temperature displayed the effects of pushing air upwards during the weekdays in urban areas, the reverse was true for forest regions. During the night, the temperature did not exert any significant influence on air movement.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.6
• /
• pp.842-848
• /
• 2018

The Smart plug is a device that connects between the outlet and the product at home, and it is an IoT type device that can drive energy saving and transmit information to the outside by power on / off control function and power measurement function. In this case, a smart plug that incorporates deep learning of intelligence technology that allows people to learn how to think about a computer, automatically classifies a product as it operates, and automatically tests the operating status of the washing machine by using input AC current pattern. Through this study, even if the product does not function as IoT, it can classify product type and operation state by smart plug connection alone, so we can draw a new paradigm of life pattern and energy saving in one family.