• Journal of Mushroom
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• v.21 no.3
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• pp.154-159
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• 2023

A new spore-less cultivar Lentinula edodes 'Daedam' was bred from monokaryotic strains of 'LE15401-24' and 'LE192118-10'. The optimum temperature for mycelial growth of 'Daedam' on potato dextrose agar was 22~25℃. Total cultivation period of the new cultivar, from inoculation to its first harvest, was 134 days, similar to that of the control cultivar 'Hwadam'. Total yield of 'Daedam' was 222g per 3kg substrate, and was lower than that of control cultivar(266.0g). The fruiting body of 'Daedam' had a thick and small pileus and a longer stem compare to control cultivar. As a result of a analyzing the productivity of 'Daedam' on the different substrate types, the biological efficiency was 26.7% in the 1.2kg cylindrical substrate(CS), which was higher than that of the 3kg rod-type substrate(RS). 'Daedam' had a similar yield compared to 'Hanacham' in first fruiting body production, but the cultivation period was 40 days shorter. Therefore, 'Daedam' can only harvest fruiting bodies once, it is thought that it can be used as spore-less oak mushroom cultivar for short-term cultivation instead of 'Hanacham' in mushroom farms.

• 한국정책학회보
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• v.21 no.4
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• pp.199-228
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• 2012

Policy problems are complex due to diverse participants and their relations in the policy processes. Defining the right problem in the first place is important because Type III error is likely to happen without removing rival hypothesis in defining the problem. This study applies Boundary Analysis suggested by Dunn to structure IT policy problems in Korea. The time frame of the study focuses on 5 years of Lee Administration and data are collected from four newspapers. Using content analysis, the study, first, elaborates total 2,614 policy problems from 1,908 stakeholders. After removing duplicating problems, 369 problems from 323 stakeholders are identified as a boundary of IT policy problem. Among others, failures in government policies are weighted as the most serious problems in IT policy field. However, many significant problems raised by stakeholders dated back to more than a decade, and those are intrinsic problems, which initially caused by market distortions in the IT industry. Therefore, we should be cautious not to overemphasize the most conspicuous problem as the only problem in the policy field when we interpret results of problem structuring.

• The Korean Journal of Mycology
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• v.50 no.2
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• pp.93-102
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• 2022

A new cultivar of oak mushroom Lentinula edodes 'Jadam' was bred from monokaryotic strains of 'Hwadam-18' and 'GMLE36295-22'. The optimum temperature for mycelial growth of 'Jadam' on potato dextrose agar was 22-25℃. Total cultivation period of the new cultivar, from inoculation to its first harvest, was 122-124 days, shorter to that of the control cultivar 'Hwadam'. Total yield of 'Jadam' was 623.8 g per 3 kg substrate, and is higher than that of 'Hwadam' (455.2 g). In the fruiting body of the new cultivar, the stipe was shorter and thinner than those of 'Hwadam'. A farmhouse field test showed that the period of mycelial growth and browning was shorter than that of control cultivar 'L808'. The total yield for 2 flush was 543.3 g for 'Jadam'. It was similar to the 585.3 g of the control cultivar. Therefore, the new cultivar 'Jadam' could be a substitute for 'L808' in the field of farms.

• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.1
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• pp.1-9
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• 2022

This study was carried out to compare the DMY (dry matter yield) of IRG (Italian ryegrass) in the southern coastal regions of Korea due to seasonal climate scenarios such as the Kaul-Changma (late monsoon) in autumn, extreme winter cold, and drought in the next spring. The IRG data (n = 203) were collected from various Reports for Collaborative Research Program to Develop New Cultivars of Summer Crops in Jeju, 203 Namwon, and Yeungam from the Rural Development Administration - (en DASH). In order to define the seasonal climate scenarios, climate variables including temperature, humidity, wind, sunshine were used by collected from the Korean Meteorological Administration. The discriminant analysis based on 5% significance level was performed to distinguish normal and abnormal climate scenarios. Furthermore, the DMY comparison was simulated based on the information of sample distribution of IRG. As a result, in the southern coastal regions, only the impact of next spring drought on DMY of IRG was critical. Although the severe winter cold was clearly classified from the normal, there was no difference in DMY. Thus, the DMY comparison was simulated only for the next spring drought. Under the yield comparison simulation, DMY (kg/ha) in the normal and drought was 14,743.83 and 12,707.97 respectively. It implies that the expected damage caused by the spring drought was about 2,000 kg/ha. Furthermore, the predicted DMY of spring drought was wider and slower than that of normal, indicating on high variability. This study is meaningful in confirming the predictive DMY damage and its possibility by spring drought for IRG via statistical simulation considering seasonal climate scenarios.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.70-81
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• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.85-100
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• 2023

Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.471-485
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• 2023

Recently, due to the nature of blockchain that guarantees users' anonymity, more and more cases are being exploited for crimes such as illegal transactions. However, cryptocurrency is protected in cryptocurrency wallets, making it difficult to recover criminal funds. Therefore, this study acquires artifacts from the data and memory area of a local PC based on user behavior from four browser extension wallets (Metamask, Binance, Phantom, and Kaikas) to track and retrieve cryptocurrencies used in crime, and analyzes how to use them from a digital forensics perspective. As a result of the analysis, the type of wallet and cryptocurrency used by the suspect was confirmed through the API name obtained from the browser's cache data, and the URL and wallet address used for the remittance transaction were obtained. We also identified Client IDs that could identify devices used in cookie data, and confirmed that mnemonic code could be obtained from memory. Additionally, we propose an algorithm to measure the persistence of obtainable mnemonic code and automate acquisition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.160-174
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• 2023

LiDAR plays a key role in autonomous vehicles, and to improve its visibility, it is necessary to improve its performance and the detection objects. Accordingly, this study proposes a shape for traffic safety signs that is advantageous for self-driving vehicles to recognize. Improvement plans are also proposed using a shape-recognition algorithm based on point cloud data collected through LiDAR sensors. For the experiment, a DBSCAN-based road-sign recognition and classification algorithm, which is commonly used in point cloud research, was developed, and a 32ch LiDAR was used in an actual road environment to conduct recognition performance tests for 5 types of road signs. As a result of the study, it was possible to detect a smaller number of point clouds with a regular triangle or rectangular shape that has vertical asymmetry than a square or circle. The results showed a high classification accuracy of 83% or more. In addition, when the size of the square mark was enlarged by 1.5 times, it was possible to classify it as a square despite an increase in the measurement distance. These results are expected to be used to improve dedicated roads and traffic safety facilities for sensors in the future autonomous driving era and to develop new facilities.

• 한국체육학회지인문사회과학편
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• v.55 no.3
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• pp.43-57
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• 2016

This narrative study aims to describe the experience of P.E. assessment that was conducted by P.E. teachers of Korea Science Academy of KAIST, and interpret the educational significance that was found in the process. The study participants were two P.E. teachers who were selected by decisive case sampling method. Data were collected mainly through official interviews with study participants, and through researcher's field notes, informal interviews, various minutes, students' evaluation of teaching, and emails between the researcher and study participants. Data were analyzed through inductive categorization, and to gain veracity of the study, there were integration of diverse materials, advice and suggestions of fellow researchers, continuous confirmation of study texts by study participants. Study participants, while conducting P.E. assessment in Korea Science Academy of KAIST, experienced effectiveness of evaluation such as qualitative development of P,E. classes in accordance with the simplified assessment, freedom from the chores of handling assessment results, students' improved perceptions of P.E. class, realization of safe classes without excessive competition, and the possibility of giving alternative evaluations to pass/fail system but at the same time experienced limitations such as concerns over gaining validity and reliability of P.E. evaluation, the students' attitude who take lightly of P.E. class, and the reality that teachers cannot fail students. The evaluation experiences of the two P.E teachers were educationally interpreted as encounter with good P.E. classes, invitation to P.E. class criticism, and the start of school P.E. culture that is led by students.

• Analytical Science and Technology
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• v.20 no.1
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• pp.84-90
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• 2007

To determine levels of 11 sulfonamides for animals in food, simultaneously, a selective method of high performance liquid chromatography with UV detector has been applied. The targets were sulfachlorpyridazine (SCP), sulfadiazine (SDZ), sulfadimethoxine (SDM), sulfisoxazole (SSX), sulfamerazine (SMZ), sulfamethazine (SMT), sulfamethoxazole (SMX), sulfamethoxypyridazine (SMP), sulfamonomethoxine (SMM), sulfaquinoxaline (SQX) and sulfathiazole (STZ). Food samples were beef, pork, chicken, milk and whole egg that were collected at the main 6 cities in Korea as Seoul, Busan, Daejon, Incheon, Mokpo and Gangneung. After homogenizing food samples with sodium phosphate solution and acetonitrile, it was extracted with n-hexane. The mobile phase gradient was a mixture of 5 mM potassium phosphate (pH 3.25) and methanol with a gradient ratio from 100:0 to 30:70. The UV wavelength was 270 nm. The overall recoveries were ranged from 75% to 95% and the limit of detection was minimum 0.004 mg/kg for SMT, and 0.007 mg/kg for STZ at signal/noise > 3, respectively. As results, sulfonamide drugs were not detected in most of the selected food samples, however, sulfamonomethoxine was detected in meat. The determined level of sulfamonomethoxine were 0.03 and 0.06 mg/kg for beef that were below the MRLs.