• Korean Journal of Poultry Science
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• v.26 no.2
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• pp.85-95
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• 1999

The mechanically deboned chicken meat(MDCM) has several limits in using for in using for in processed meat products as a main material because of poor color and textural properties, chance of microbial contamination and lipid oxidation. There has been a growing interest all over world in the application of MDCM to the surimi process. The surimi made from MDCM contains a high concentration of myofibrillar protein since this processing involves repeated washing processes with an aqueous solution in order to remove heme pigments, fat and other undesirable substances. The quality of the surimi made from MDCM is affected by various processing factors, such as kinds of wash solution, ion strength, washing cycle, temperature, pH changes, composition, part of muscle, particle size, and rigor state etc. A number of researchers havee investigated the effect of the various washing conditions on the properties of surimi gels. A fuller information of all the factors affecting surimi processing and gel formation by heat-induced gelation has not been known yet.

• Journal of Information Display
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• v.13 no.1
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• pp.37-42
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• 2012

An empirical functional form was suggested for the analysis of the emission spectrum of high-power light-emitting diode (LED) consisting of a sharp blue peak from the LED chips and a broad yellow peak from the phosphor layer. The peak positions, half widths, shape parameters, and amplitudes of these two peaks were reliably obtained as a function of the temperature, and the results were discussed qualitatively in relation with the junction temperature. The adoption of an inert liquid was found to have significantly reduced the LED temperature and the color shift of the emitted light. The phenomenological approach used in this study may be helpful in the simulation of the LED spectrum under various thermal conditions, and may thus be helpful in the improvement of the device performance.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.173-181
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• 2011

Recognition of traffic signs helps an unmanned ground vehicle to decide its behavior correctly, and it can reduce traffic accidents. However, low cost traffic sign recognition using a vision sensor is very difficult because the signs are exposed to various illumination conditions. This paper proposes a new approach to solve this problem using an illuminometer which detects the intensity of illumination. Using the intensity of illumination, the recognizer adjusts the parameters for image processing. Therefore, we can reduce the loss of information such as the shape and color of traffic signs. Experimental results show that the proposed method is able to improve the performance of traffic sign recognition in various weather and lighting conditions.

• Journal of the Korean Applied Science and Technology
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• v.22 no.4
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• pp.299-305
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• 2005

In this study, we designed color of tunable and high efficient organic materials using the quantum dynamics and the semi-empirical calculation, and applied this results to the fabrication of organic light-emitting diodes. Also we optimized the molecular structure of phosphorescent materials and the energy transfer from a host to a dye which makes organic light-emitting diodes improve. Using quantum dynamics method, the molecular structures of ligand only and the whole metal chelate were optimized, and these energy levels were calculated. From this test results, we could understand the emission mechanism of phosphors with various ligands as well as design the proper ligands reducing the T-T annihilation and the carrier lifetime. We also could design ligands with various colors using this test method.

• Journal of Information Display
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• v.13 no.4
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• pp.159-166
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• 2012

In this paper, a display's emotional image quality can be primarily determined by designing the proper luminance level. Though displays with high luminance are preferred, too much light emission from a display may cause glare or visual fatigue to viewers. To find out the proper luminance level based on various video contents, this study was conducted with an OLED display with a real-black level and a wide color gamut, and with an LCD display with a high luminance level, to set the glare threshold under various conditions. The optimum luminance levels according to the display's loading ratio were found, and the maximum luminance that did not cause a glare in the test is proposed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.41-46
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• 2023

Human urine is a process of excreting waste products in the blood, and it is easy to collect and contains various substances. Urinalysis is used to check for diseases, health conditions, and urinary tract infections. There are three methods of urinalysis: physical property test, chemical test, and microscopic test, and chemical test results can be easily confirmed using urine test strips. A variety of items can be tested on the urine test strip, through which various diseases can be identified. Recently, with the spread of smart phones, research on reading urine test strips using smart phones is being conducted. There is a method of detecting and reading the color change of a urine test strip using a smartphone. This method uses the RGB values and the color difference formula to discriminate. However, there is a problem in that accuracy is lowered due to various environmental factors. This paper applies a deep learning model to solve this problem. In particular, color discrimination of a urine test strip is improved in a smartphone using a lightweight CNN (Convolutional Neural Networks) model. CNN is a useful model for image recognition and pattern finding, and a lightweight version is also available. Through this, it is possible to operate a deep learning model on a smartphone and extract accurate urine test results. Urine test strips were taken in various environments to prepare deep learning model training images, and a urine test service application was designed using MobileNet V3.

• Journal of Korean Library and Information Science Society
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• v.10
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• pp.229-265
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• 1983

Many changes have been made on the cataloging rules on filmstrips and slides all the way from the Cox's rules of 1963 to AACR 2 of 1978. The purpose of this study is to analyze eight major British and American cataloging rules on filmstrips and slides, from the results of which to identify what major changes have been made chronologically, and to clarify major differences among them in describing the form ol Physical Description Area. The findings of the study can be summarized as follows: 1. In order to make a clear distinction from one element to the other in Physical Description Area, the use of punctuation has been made more concrete. In AACR 2, various punctuations in accordance with the each element's character are used. 2. The rules on the describing the number of physical units of filmstrips have got more and more specified. 3. The descriptive form of specific material designation is closely related to the existence or nonexistence of rules on the general material designation in the body of entry. Therefore, the rules of AECT and CLA having rules on the general material designation do not use the specific material designation in Physical Description Area. On the other hand, ISBD(NBM), LA rules and AACR 2 which makes it optional to use the general material designation prescribe to use the specific material designation. 4. As for the descriptions of the physical status other than the unit and size of the filmstrips and slides, the first LC card and Cox's rules, had the color designation, and the CLA rules had sound designation. In the LA rules, AACR1(Chapter 12 Revised) and AACR 2, the detailed description of the physical status including the indication of color, sound, kind of frame, time etc. has become more and more important for Physical Description Area. 5. All the rules adopt millimetre as the measuring unit of the size of filmstrips. For the slides, most rules employ inch instead. But LA rules and ISBD(NBM) use centimeters, and AACR 2 takes either inch or centimeters. 6. Most rules, including Cox's rules, give the information on the accompanying materials. The information has been added as the last element of the Physical Description Area in the AACR 2, and recognized very important.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.33-45
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• 2011

In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

• Journal of Information Technology Application
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• v.3 no.2
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• pp.133-147
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• 2001

This paper proposed a new algorithm for binarization and removal of noises in color images with characters and pictures. Binarization was performed by threshold which had computed with color-relationship relative to the number of pixel in background and character candidates and pre-threshold for dividing of background and character candidates in input images. The pre-threshold has been computed by the histogram of R, G, B In respect of the images, while background and character candidates of input images are divided by the above pre-threshold. As it is possible that threshold can be dynamically decided by the quantity of the noises, and the character images are maintained and the noises are removed to the maximum. And, in this study, we made the noise pattern table as a result of analysis in noise pattern included in the various color images aiming at removal of the noises from the Images. Noises included in the images can figure out Distribution by way of the noise pattern table and pattern matching itself. And then this Distribution classified difficulty of noises included in the images into the three categories. As removal of noises in the images is processed through different procedure according to the its classified difficulties, time required for process was reduced and efficiency of noise removal was improved. As a result of recognition experiments in respect of extracted characters in color images by way of the proposed algorithm, we conformed that the proposed algorithm is useful in a sense that it obtained the recognition rate in general documents without colors and pictures to the same level.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.95-102
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• 2005

In this paper, we propose a user friendly object-based image retrieval system using the interaction between cortex and hippocampus. Most existing ways of queries in content-based image retrieval rely on query by example or query by sketch. But these methods of queries are not adequate to needs of people's various queries because they are not easy for people to use and restrict. We propose a method of automatic color object extraction using CSB tree map(Color and Spatial based Binary をn map). Extracted objects were transformed to bit stream representing information such as color, size and location by region labelling algorithm and they are learned by the hippocampal neural network using the interplay between cortex and hippocampus. The cells of exciting at peculiar features in brain generate the special sign when people recognize some patterns. The existing neural networks treat each attribute of features evenly. Proposed hippocampal neural network makes an adaptive fast content-based image retrieval system using excitatory learning method that forwards important features to long-term memories and inhibitory teaming method that forwards unimportant features to short-term memories controlled by impression.