• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.402-407
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• 2014

In this study, Italy poplar(Populus euramericana) was selected for test specimen to measure cutting power when it harvested. The experiment has been controlled as three levels of feed rate (0.41, 1.25 and 2.5 m/s), sawing speed (800, 1,000 and 1,200 rpm), and the five levels of root collar diameter (50, 70, 90 and 110, 130 mm). The harvested volume after 3 years (root collar diameter 50 mm) was 10.5 tons, which falls short of the target amount of biomass is 20~30 ton/ha. In addition, the biomass amount of diameter 90 and 110 mm which reached the target amount were estimated to be 23.5 and 32.5 ton/ha respectively. As a result of experiment, it was found out that power of 128.2 and 175.8 W are consumed in case of cutting with the feed rate of 0.41m/s and minimum sawing speed (800 rpm) respectively. With the working area of 0.3 ha/h, it is considered to present working capacities of 16.5 and 22.8 ton/h respectively. The power consumed at the feed rate of 1.25 m/s is estimated to be 113.8 and 153.7W respectively and working capacity in a working area of 1 ha/h is estimated to be 23.5 and 32.5 ton/h. The power consumed at the feed rate of 2.5 m/s is estimated to be 119.8 and 166.9 W respectively and working capacity in a working area of 2 ha/h is estimated to be 47.0 and 65.5 ton/ha respectively. Therefore, the power source of harvest machine at the feed rate of 1.25, 2.50 m/s and sawing speed of 800 rpm shall be selected as it can process the target amount of estimated biomass.

• Journal of Biomedical Engineering Research
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• v.19 no.6
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• pp.617-622
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• 1998

A cryotherapy system using cold air was developed. The developed system had superior low-temperature characteristics with various flow rates and nozzle sizes, and used R-404A, as a coolant, which has no destructive effects of Ozone layers. Flow rates and the treatment time can be easily altered during the operation. In addition, and alarm system was designed for the overload, overheat, and over-charge of the machine. For clinical applications, skin temperatures, intra-articular temperatures of the knee joint and intra-muscluar temperatures of the gluteal muscles were measured during and after the cryotherapy. After a 5-minute therapy, skin and intra-articular temperatures decreased by $23.3{\pm}4.7 and 4.1 {\pm}1.0^{circ}C$, respectively. A 5-minute cryotherapy was good enough to maintain low intra-articular temperatures for 2-3 hours. Resting intra-muscular temperatures in 2, 4, and 6cm deep in the gluteal muscle were $36.5{\pm}1.2, 36.9{\pm}0.2, 37.1{\pm}0.2^{circ}C$, respectively (p<0.05). Lowest temperatures in 2, 4, and 6cm depth were $35.1{\pm}0.7, 36.2{\pm}0.4, 36.9{\pm}0.3^{circ}C$, respectively (p<0.05). Temperatures after a 2-hour cold air application on the skin and in the muscle in dept도 of 2, 4, and 6cm were $32.2{\pm}1.1, 36.2{\pm}0.5, 36.6{\pm}0.3, 36.9{\pm}0.3^{circ}C$respectively (p<0.05). Temperatures on the skin and in the muscle significantly decreased after 2 hours, compared with before cold air application (p<0.05). The intra-muscular temperature was changed more slowly than the skin temperature, and the deeper the muscle, the lesser temperature changes. The effect of a 5-minute cold air application lasts up to 2 hours, and it seems that the rebound-rise of the temperature dut to the reactive vasodilatation does not occur in the gluteal muscle.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1319-1326
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• 2019

The KARI(Korea Aerospace Research Institute) operates the government satellite information application consultation to cope with ever-increasing demand for satellite images in the public sector, and carries out various support projects including the generation and provision of mosaic images on the Korean Peninsula every year to enhance user convenience and promote the use of satellite images. In particular, the government has wanted to increase the utilization of mosaic images on the Korean Peninsula and seek to classify and update mosaic images so that users can use them in their businesses easily. However, it is necessary to test and verify whether the classification results of the mosaic images can be utilized in the field since the original spectral information is distorted during pan-sharpening and color balancing, and there is a limitation that only R, G, and B bands are provided. Therefore, in this study, the reliability of the classification result of the mosaic image was compared to the result of KOMPSAT-3 image. The study found that the accuracy of the classification result of KOMPSAT-3 image was between 81~86% (overall accuracy is about 85%), while the accuracy of the classification result of mosaic image was between 69~72% (overall accuracy is about 72%). This phenomenon is interpreted not only because of the distortion of the original spectral information through pan-sharpening and mosaic processes, but also because NDVI and NDWI information were extracted from KOMPSAT-3 image rather than from the mosaic image, as only three color bands(R, G, B) were provided. Although it is deemed inadequate to distribute classification results extracted from mosaic images at present, it is believed that it will be necessary to explore ways to minimize the distortion of spectral information when making mosaic images and to develop classification techniques suitable for mosaic images as well as the provision of NIR band information. In addition, it is expected that the utilization of images with limited spectral information could be increased in the future if related research continues, such as the comparative analysis of classification results by geomorphological characteristics and the development of machine learning methods for image classification by objects of interest.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.2142-2147
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• 2012

This study is aimed at decreasing wrong diagnosis with corrected EF(Ejection Fraction) of 2D echo cardiography by analysing the physical time-resolution difference between Cine MRI and 2D echo cardiography and applying the corrected EF in 2D echocardiography. From February 2010 to December 2011, among the 110 patients who had undergone both 2D echo cardiography and cine MRI only 37 patient were selected suffering aortic valve regurgitation. ED, ES and SV were measured and EF was calculated in each system while normal ranges of Cine MRI and 2D echocardiography were compared to evauate misdiagnosis rate. The correlation of physical time resolution between 2D echocardiography and MRI was evaluated and the differences were corrected with linear regression coefficient which is derived from linear regression analysis. Blandt-Altman plot was used to evaluate the reliability of corrected 2D echo cardiography EF and compare the error among measured values. The values were compared with MRI normal range and misdiagnosis rate was measured again. As a result, misdiagnosis rates of physical time resolution were measured to be 32.4%(12people) before the correction of EF and 18.9%(7people) after the correction. Also, EF confirmed in Blandt-Altman plot were almost the same with MRI EF. In conclusion, when diagnosing aortic regurgitation disease, simply using 2D echocardiography can easily raise the misdiagnosis rates, therefore considering the MRI machine's physical merits, correcting the time resolution difference is important by calculating time resolution wrong diagnosis would decrease and it is considered to be useful in clinical circumstances.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.198-221
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• 2021

After large-scale reforestation in the 1960s and 1970s, forests in Korea have gradually been aging. Net ecosystem CO₂ exchange of old-growth forests is theoretically near zero; however, it can be a CO₂ sink or source depending on the intervention of disturbance or management. In this study, we report the CO₂ budget dynamics of the Gwangneung deciduous old-growth forest (GDK) in Korea and examined the following two questions: (1) is the preserved GDK indeed CO₂ neutral as theoretically known? and (2) can we explain the dynamics of CO₂ budget by the common mechanisms reported in the literature? To answer, we analyzed the 15-year long CO₂ flux data measured by eddy covariance technique along with other biometeorological data at the KoFlux GDK site from 2006 to 2020. The results showed that (1) GDK switched back-and-forth between sink and source of CO₂ but averaged to be a week CO₂ source (and turning to a moderate CO₂ source for the recent five years) and (2) the interannual variability of solar radiation, growing season length, and leaf area index showed a positive correlation with that of gross primary production (GPP) (R²=0.32~0.45); whereas the interannual variability of both air and surface temperature was not significantly correlated with that of ecosystem respiration (RE). Furthermore, the machine learning-based model trained using the dataset of early monitoring period (first 10 years) failed to reproduce the observed interannual variations of GPP and RE for the recent five years. Biomass data analysis suggests that carbon emissions from coarse woody debris may have contributed partly to the conversion to a moderate CO₂ source. To properly understand and interpret the long-term CO₂ budget dynamics of GDK, new framework of analysis and modeling based on complex systems science is needed. Also, it is important to maintain the flux monitoring and data quality along with the monitoring of coarse woody debris and disturbances.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• The Journal of Korean Society for Radiation Therapy
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• v.12 no.1
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• pp.91-104
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• 2000

Recently linear accelerator in radiation therapy in asymmetric field has been easily used since the improvement and capability of asymmetrical field adjustment attached to the machine. It has been thought there have been some significant errors in dose calculation when asymmetrical radiation fields have been utilized in practice of radiation treatments if the fundamental data for dose calculation have been measured in symmetrical standard fields. This study investigated how much the measured data of dose distributions and their isodose curves are different between in asymmetrical and symmetrical standard fields, and how much there difference affect the error in dose calculation in conventional method measured in symmetrical standard field. The distributions of radiation dose were measured by photon diode detector in the water phantom (RFA-300P, Scanditronix, Sweden) as tissue equivalent material on utilization of 6 MV linear accelerator with source surface distance (SSD) 1000 mm. The photon diode detector has the velocity of 1 mm per second from water surface to 250 mm depth in the field size of $40mm{\times}40mm\;to\;250mm{\times}250mm\;symmetric\;field\;and\;40mm{\times}20mm\;to\;250mm{\times}125mm$ asymmetrical fields. The measurements of percent depth dose (PDD) and subsequent plotting of their isodose curves were performed from water surface to 250mm dmm from Y-center axis in $100mm{\times}50mm$ field in order to absence the variability of depth dose according to increasing field sizes and their affects to plotted isodose curves. The difference of PDD between symmetric and asymmetric field was maximum $4.1\%\;decrease\;in\;40mm{\times}20mm\;field,\;maximum\;6.6\%\;decrease\;in\;100mm{\times}50mm\;and\;maximum\;10.2\%\;decrease\;200mm{\times}100mm$, the larger decrease difference of PDD as the greater field size and as greater the depth, The difference of PDD between asymmetrical field and equivalent square field showed maximum $2.4\%\;decrease\;in\;60mm{\times}30mm\;field,\;maximum\;4.8\%\;decrease\;in\;150mm{\times}75mm\;and\;maximum\;6.1\%\;decrease\;in\;250mm{\times}125mm$, and the larger decreased differenced PDD as the greater field size and as greater the depth, these differences of PDD were out of $5\%$ of dose calculation as defined by international Commission on radiation unit and Measurements(ICRU). In the dose distribution of asymmetrical field (half beam) the plotted isodose curves were observed to have deviations by decreased PDD as greater as the blocking of the beam moved closer to the central axis, and as the asymmetrical field increased by moving the block 10 mm keeping away from the central axis, the PDD increased and plotted isodose curves were gradually more flattened, due to reduced amount of the primary beam and the fraction of low energy soft radiations by passing thougepth in asymmetrical field by moving independent jaw each 10 h beam flattening filter. As asymmetrical radiation field as half beam radiation technique is used, the radiation dosimetry calculated in utilizing the fundamental data which measured in standard symmetrical field should be converted on bases of nearly measured data in asymmetrical field, measured beam data flies of various asymmetrical field in various energy and be necessary in each institution.

• Korean Journal of Agricultural Science
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• v.8 no.2
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• pp.203-211
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• 1981

Mechanization of rice transplanting operation is very important project not only to solve the labor shortage problem at the so-called labor demand peak seasons of the rice transplanting, but also to reduce the production cost of rice by reducing the labor requirements. For these reasons this study was carried out to find the basic data for encourage the project of mechanization of rice transplanting. 381 sample farms were surveyed with questionaries and interviewed with a considerable number of relative personels about the operation, selecting and ownership trend of the rice transplanter. Collected data was analized by computer of Chungnam National University computer center applied to frequencies, cross- tabulation, $x^2$-test. The analized results of this survey are summarized as follows; 1. About 76.09% of the farmers interviewed was individual ownership of rice transplanter but about 52.27% of the farmers who wanted to purchase it in 2 or 3 years supported the cooperative ownership and utilization. This fact suggested that cooperative system of village level should be thoroghly studied. 2. The 93.33% of respondents gave the answer that the yield of rice was not affected by the planting methods between machine and manual. 3. The farmers who had a rice transplanter owned 4- row type rice transplanter with mat type seedling but the 25% of the farmers wanted to purchase it in 2 or 3 years wanted to own a 4 row type rice transplanter with band type seedling. Therefore the introduction of the 4-row type rice transplanter with band type seedling to rural area should be considered again. 4. The percent of farmers who wanted the cooperative system of village level was 49.57-57.83% of the farmers who had it already and wanted to own it in near future. It was strengthened by this fact that seedling nursely work was technically supported by the governmental level.

• Journal of Korean Society of Disaster and Security
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• v.9 no.2
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• pp.53-62
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• 2016

This paper is shown the new method using LED Light, which the light environment is upgraded the natural LED light in the area of Disaster Prevention and Safety Management (PDSD), which the events of deaths is reduced on the Suicide, the Infectious diseases, the safety accidents, the Traffic Accident, the crime, the fire, the Nature Disaster, and which the health and the environment and the safety is implemented using the value of the color LED Light. Research findings include,during 3 weeks in the November 2016, in the ten residents (average living 28.7 years, age 67.5 years) with depressive symptoms in the northern part of Seoul, according to the request of the user, the PDSD natural light LED lighting was installed in the home bedroom or the living room, expectations for the ability to restore physical and mental stability were high (88%), in the same way, after 1 week and 3 weeks, the physical and mental changes were compared and the results,84% in the first week and 90% in the third week and thereafter, the effect of relieving depression was high. We conclude that patients with depression have a good sleep, an uneasy feeling, a sense of security, a good night's sleep, and a good feeling. The PDSD LED Light is expected to contribute in the various areas, which reduced the suicides, which give increased immunity from infectious diseases, which give a crash to reduce accidents caused by negligence, which improve the safe operation of heavy vehicles in which a traffics accident incidence installed on the highest point, which improve the safety function on the 'safety way home' for the safety of the community, which due to fire gives alleviate the emotional anxiety of firefighters, which improve the environment for long-term control room working during decision making caused by natural disasters.