• Journal of Korean Society of Forest Science
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• v.40 no.1
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• pp.75-81
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• 1978

Elder-berries are economical plants and grown commercially in the United States. Most of the crop is sold to processors and made into natural colour, jellies, jam, port wine or elder berry wine, elder berry juice or used to manufacture of pie mixes. Processors are showing increasing interest in cultivation elder berries. In the present study was wish to find the effect of various factors and practical methods on the processing for the true fruit colour made from fresh elder berries juice as the clearing by the treated pectinase, added sugar, vaccum concentration, extraction of anthocyanosid powder and its property with used prospects. In this study obtained results can be summarized as follows. 1. Pectinase is useful and effected to make clear juice from fresh elder berry juice treated on the $34{\sim}45^{\circ}C$. 2. P.V.C. drum is most useful stored without unfading for clearing elderberry juice and its exposed redish dark purple colour. 3. Clearing elderberry juice stored in the stainless steel drum, changed colour from redish dark purple to dark violets during the stored at the room temperature. 4. Added sugar (Brix $48{\sim}53^{\circ}C$) to the fresh elderberry juice is useful and suitable prospects for to make home juice and wine. 5. The elderberry juice of vaccum concentration is change colour from dark purple to black brown colour during the stored at the room temperature. 6. Its possible to make anthocyanosid powder extracted made from fresh elderberry juice 7. Property of anthocyanosid is an follows. 1) The spectrum of elderberries juice is $523{\sim}530m{\mu}$ 2) The colouring stability is less than $pH_4$ 3) The colouring stability by the heating is less than $pH_4$, and then the more than $pH_4$ is changed colour from redish dark purple to dark brown. 4) By the light colouring stability is less than $pH_4$ 5) The colouring most stability in the pH is $pH_3$ 8. In the future, natural colour made from elderberry juice on the useful prospects is suitable used to make natural fruit juice, ice cream, candy, commercial and home wine, gum, and manufacture of jelly jam, pie maxes, ect.

• Journal of Preventive Medicine and Public Health
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• v.1 no.1
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• pp.67-78
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• 1968

For the purpose of ascertaining the status of physical growth and health status of the University students, a intensive survey was conducted by the authors towards a total of 2,638(male; 2,228, female; 410) who passed the written entrance examination at the Seoul National University. The items included the measurements on physical growth, various physical indixes, visual acuity, tuberculosis and dental status. The findings and results can be summarized as follows: 1. Physical Growth No significant difference was found in the physical growth between classes(literature and science) and by ages. In males, the means of body height, body weight, chest-girth and sittingheight were $168.0{\pm}5.07cm,\;55.7{\pm}5.71kg,\;85.8{\pm}4.4cm\;and\;91.5{\pm}2.21cm$, respectively. In females, these were $157.4{\pm}4.57\;cm,\;00.4{\pm}5.75kg,\;80.3{\pm}4.51cm\;and\;86.1{\pm}3.30cm$, respectively. Basing on the above measurements several physical indixes were calculated as follows ; Relative body weight 33.15 in males and 32.02 in females. Relative chest-girth 51.07 and 51.01, relative sitting-height 54.46 and 54.70 $R\ddot{o}hrer$ index 1.00 and 1.02, Kaup index 1.97 and 2.04, Vervaeck index 83.63 and 83.03, and Pelidisi index 89.94 and 92.45. 2. Visual Acuity Among the students of science classes those of 0.8 and below in vision on left and right occupied 46.4% and 45.0%, those of 0.6 and below 39.1% and 41.2%, respectively. Among the students of literature classes those of 0.8 and below occupied 46.3% and 42.9%, and those of 0.6 and below occupied 41.4% and 39.0, respectively. In males those of 0.8 and below occupied 46.8% and 44.5% and 0.6 and below occupied 41.9% and 39.7%, while in females 0.8 and below occupied 43.9%, and 42.4%, and 0.6 and below occupied 38.3% and 37.3%, respectively. In males those of 0.8 and below in corrected vision occupied 12.1% and 10.3%, while in females 12.9% and 12.2%, respectively. More students of abnormal vision were found among science classes and the proportions of corrected vision were 38.9% and 37.4% in males, and 33.9% and 33.2% in females, respectively. 3. Tuberculosis Among the total, 55 students were diagnosed as tuberculosis, of whom 50 were minimal cases, 2 were moderately advanced cases and 3 were far advanced cases. 4. Dental Status Among the total, 81.2% were of decayed teeth, 20.8% filled, 9.5% missed, 5.0% extraction needed, 9.1% sunplatinum bridges, 3.3% golden bridges and 5.5% golden inlay. Regarding tartar on teeth moderate, heavy and light grades occupied 49.5%, 29.7% and 20.3%, respectively and 0.8% had none. 5. Comprehensive evaluation According to criteria 4 grades were applied to comprehensive evaluation as follows : A...excellent in physical status B...with some physical defects but no difficulties in study C...need treatment D...need treatiment and rest Out of the total, A grade occupied 21.6%, B 76.2% and C. and D 2.2.

• Restorative Dentistry and Endodontics
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• v.35 no.6
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• pp.453-460
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• 2010

Objectives: To evaluate the accuracy and consistency of two different apex locators at both the Apex and 0.5 marks. Materials and Methods: Twenty-six root canals was scheduled for extraction for periodontal or prosthodontic reasons. Thirteen canals were measured using Root ZX and the rest by i-ROOT. The root canal length was measured both the at 0.5 mark and the Apex mark. The file was then fixed to the toot, and the distance from the file tip to the major foramen of each canal was measured after removing the root dentin under the microscope so that the major foramen and the file tip were seen. Results: 1. When the Apex mark was used, 100% of both the Root ZX and i-ROOT groups were within 0.5 mm of the major foramen. 2. When 0.5 mark was used, 100% of the Root ZX group and 77% of the i-ROOT group were within 0.5 mm of the major foramen. 3. In terms of standard deviation and quartile value, the Apex mark was more consistent than 0.5 mark in the Root ZX group, and 0.5 mark was more consistent in the i-ROOT group, but there was no statistically significant difference when compared with t-test. 4. The root canal length difference between the Apex mark and 0.5 mark was 0.22 mm and 0.46 mm in the Root ZX and i-ROOT groups, respectively. Conclusions: In this study, the Apex mark was the more consistent mark. Therefore, it is recommended to subtract 0.5 mm, which is the average length between the apex and apical constriction, from the root canal length at the Apex mark to obtain the working length clinically.

• Applied Biological Chemistry
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• v.20 no.1
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• pp.66-80
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• 1977

This research was carried as a part of the basic study, in which the aptitude of theKorean oak varieties as barrels for aging apple fine spirits was investigated, and thefollowing results were obtained. 1. Following was the result of the chemical analysis of the fruits which are now mass-produced and can be used as a substitute for raw materials for wine production. Apple (Malus pumila Miller var. domestica Schneider) : Total sugar. total acid, volatile acid and pectin of Jonathan (Hong-og) were 13.95%, 0.46%, 0.012%, 0.20% respectively. Total sugar, total acid, volatile acid and pectin of Ralls (Koog-kwang) were 13.35%, 0.43%, 0.011%, 0.45% respectively. 2. Because of low yield of apple juice due to cellulose, pectin, hemicellulose which are present besides sugars, acids in apples, the apple juice were treated with xylanase of Aspergillus niger SUAFM-430, cellulase and pectinase of Aspergillus niger SUAFM-6. This treatment increased the yield of apple juice. And the apple juice was sterilized by adding potassium metabisulfite $(K_2S_20_5)$ and Saccharomyces cerevisae var. ellipsoideus Rasse Johannisberg II (SUAFM-1018) as a cultivation yeast, which has a strong fermentation power was used to ferment. The yield of apple wine based on raw material was 86-87%. The amount of ethanol, extract and methanol obtained from Jonathan and Ralls were 13.5%, 5.4%, 0.04-0.05% respectively. 3. Wines were distilled for two times by the pot still method to make fine spirits. The yield of fine spirits from apple wine mash was 86.6%, and the pH of fine spirits from Jonathan and Ralls were 4.1, 4.2 respectively. 4. The oak chips made of inner part or outer part of 24 Korean oak varieties were used to select the barrel for aging fine spirits. Two oak chips (one oak chip: $1{\times}1{\times}5cm$) of the inner part or of the outer part of each oak variety were dipped into 300 ml of fine spirits, which was bottled in 640ml beer bottle, and followed aging. The colors, flavors and tastes of the fine spirits were checked during 6 months. A. As a criterion for the first screening of oak barrels for aging fine spirits, the rate five of color extraction was determined. The oak chips showed good results in their order as follows and the best 5 varieties were selected. Gal-cham: Quercus aliena Blume (Inner part), Gul-cham: Quercus variabilis Blume (Outer part), Gal-chain: Quercus aliena Blume (Outer part), Jol-cham: Quercus serrata Thumb (Inner and Outer part). Sin-gal-cham: Quercus mongolica Fisher (Outer and Inner part) Sang-su-ri: Quercus acutissima Carruthers (Outer and Inner part) B. To find out the influence of aging temperature on aging, apple fine spirits were aged by dipping each oak chip at room temperature $(24-25^{\circ}C)$) and $45^{\circ}C$. Aging at $45^{\circ}C$ gave the best result followed aging at $30^{\circ}C$ and then at room temperature. C. Apple fine spirits was aged for six months by dipping oak chips in Erlenmeyer flasks and was irradiated with U.V light. The U.V irradiation enhanced the aging effect by nearly two times, compared with the aging without U.V irradiation. D. In aging apple fine spirits by dipping two oak chips, it was observed that the extent of the extraction of most components of oak chips were strongly dependent upon the pH of fine spirits. E. Oak chips of five selected oak varieties and a Limousin white oak from France as a control were used. Each apple fine spitits was dipped by two oak chips, and was aged at room temperature $(24-25^{\circ}C)$, $30^{\circ}C$, $45^{\circ}C$, and with the U.V irradiation at room temperature shaking every week. After six months of aging, the panel test of these aged fine spirits (Young Brandy) showed the following result. Young brandy of apples aged at $45^{\circ}C$ by dipping oak chips of Gal-chain was almost as the fine spirits which were aged at room temperature by dipping Limousin white oak chips from France. Young brandy of with U.V. irradiation at room temperature which were aged by dipping oak chips of Gal-chain was a little worse than that from the fine spirits aged at room temperature by dipping Limousin white oak chips from France. And so, Korean oak varieties are thought to be able to be used for aging every apple fine spirit which was here investigated.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.