• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.209-213
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• 2019

Recently, demand for high energy density and long cycling stability of energy storage system has increased for application using with frequency regulation (F/R) in power grid. Supercapacitor have long lifetime and high charge and discharge rate, it is very adaptable to apply a frequency regulation in power grid. Supercapacitor can complement batteries to reduce the size and installation of batteries. Because their utilization in a system can potentially eliminate the need for short-term frequent replacement as required by batteries, hence, saving the resources invested in the upkeep of the whole system or extension of lifecycle of batteries in the long run of power grid. However, low energy density in supercapacitor is critical weakness to utilization for huge energy storage system of power grid. So, it is still far from being able to replace batteries and struggle in meeting the demand for a high energy density. But, today, LIC (Lithium Ion Capacitor) considered as an attractive structure to improve energy density much more than EDLC (Electric double layer capacitor) because LIC has high voltage range up to 3.8 V. But, many aspects of the electrochemical performance of LIC still need to be examined closely in order to apply for commercial use. In this study, in order to improve the capacitance of LIC related with energy density, we designed new method of pre-doping in anode electrode. The electrode in cathode were fabricated in dry room which has a relative humidity under 0.1% and constant electrode thickness over $100{\mu}m$ was manufactured for stable mechanical strength and anode doping. To minimize of contact resistance, fabricated electrode was conducted hot compression process from room temperature to $65^{\circ}C$. We designed various pre-doping method for LIC structure and analyzing the doping mechanism issues. Finally, we suggest new pre-doping method to improve the capacitance and electrochemical stability for LIC.

• Journal of the Korea Society of Computer and Information
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• v.6 no.4
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• pp.188-205
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• 2001

Insurer's duty of declaration is based on reciprocity of principle of the highest good, and recently it is widely recognized in the British and American insurance circles. The conception of fiduciary relationship is no longer equity or the legal theory which is only confined to the nations with Anglo-American laws. Therefore, recognizing the fiduciary relationship as the essence of insurance contract, which is more closely related to public interest than any other fields. will serve an efficient measure to seek fair and reasonable relationship with contractor, and provide legal foundation which permits contractor to bring an action for damage against violation of insurer's duty of declaration. In the future, only when the fiduciary relationship is approved as the essence of insurance contract, the business performance and quality of insurance industry is expected to increase. Therefore, to keep well this fiduciary relationship, or increase the fiduciary relationship persistency rates seems to be the bottom line in the insurance industry. In this paper, we developed a fiduciary relationship maintenance ratio based on comparison by case, which is represented with usually maintained contract months to paid months, based on each contract of the basis point. In this paper we have developed a new business model seeking the maximum profit with low cost and high efficiency, management policy of putting its priority on its substantiality, as an improvement measure to break away from the vicious circle of high cost and low efficiency, and management policy of putting its priority on its external growth(expansion of market share).

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1611-1623
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• 2021

Thisstudy demonstratessoil moisture and evapotranspiration performance using Korea Land Data Assimilation System (KLDAS) under Korea Land Information System (KLIS). Spin-up was repeated 8 times in 2018. In addition, low-resolution and high-resolution meteorological data were generated using meteorological data observed by Korea Meteorological Administration (KMA), Rural Development Administration (RDA), Korea Rural Community Corporation (KRC), Korea Hydro & Nuclear Power Co.,Ltd. (KHNP), Korea Water Resources Corporation (K-water), and Ministry of Environment (ME), and applied to KLDAS. And, to confirm the degree of accuracy improvement of Korea Low spatial resolution (hereafter, K-Low; 0.125°) and Korea High spatial resolution (hereafter, K-High; 0.01°), soil moisture and evapotranspiration to which Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and ASOS-Spatial (ASOS-S) used in the previous study were applied were evaluated together. As a result, optimization of the initial boundary condition requires 2 time (58 point), 3 time (6 point), and 6 time (3 point) spin-up for soil moisture. In the case of evapotranspiration, 1 time (58 point) and 2 time (58 point) spin-ups are required. In the case of soil moisture to which MERRA-2, ASOS-S, K-Low, and K-High were applied, the mean of R² were 0.615, 0.601, 0.594, and 0.664, respectively, and in the case of evapotranspiration, the mean of R² were 0.531, 0.495, 0.656, and 0.677, respectively, indicating the accuracy of K-High was rated as the highest. The accuracy of KLDAS can be improved by securing a large number of ground observation data through the results of this study and generating high-resolution grid-type meteorological data. However, if the meteorological condition at each point is not sufficiently taken into account when converting the point data into a grid, the accuracy is rather lowered. For a further study, it is expected that higher quality data can be produced by generating and applying grid-type meteorological data using the parameter setting of IDW or other interpolation techniques.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Korean Journal of Labor Studies
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• v.24 no.1
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• pp.107-156
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• 2018

This article examines the history of the in - house subcontracting and the stabilization of labor - management relations in the steel industry in Japan. The ratio of in-house subcontract workers among steel workers has increased steadily until the mid-2000s, and about 70% in case of the largest company. In-house subcontracting was used as a strategy of the company to increase the quantity flexibility of employment and to save labor costs. The in-house subcontracting company needed company-specialized skills, and the internal labor market was formed because the rate of full-time workers was high and the turnover rate was low. The in-house subcontractor introduced long-term business relationship with the steel factory by introducing the equipment and materials necessary for the performance of the work, and the factory implemented the productivity improvement policy of the in-house subcontractor, and the win-win relationship between the factory and in-house subcontractor was developed. The trade union did not oppose the idea that the expansion of in-house subcontracting contributed to corporate profits, the stability of employment of the members and maintenance of their working conditions. Since 2000, the steel factory has pursued the transformation of in - house subcontractors into subsidiaries, which has been supported by capital relations. By the way, since the mid-2000s, there has been an increase in the number of regular workers' employment. The major factors are as follows: more strengthened compliance with laws and regulations, the higher quality request of customers, stricter keeping of deadlines, and problem in recruiting of workers at in-house subcontract companies. The wage gap between the factory and in - house subcontracting was less at company B than at company S, and the wage level of in - house subcontracting was about 90% of the factory at company B. The relatively small gap at company B seems to be due to the union's movement of narrowing the gap, low market dominance and unfavorable labor market. The internal labor market has been formed in the in-house subcontracting, and the wage gap is not large, and the possibility of labor disputes is low. Industrial relations are stable in the in-house subcontract company as well as the factory. The stabilization of labor-management relations in the steel industry in Korea is required to reduce the wage gap between the factory and in-house subcontract enterprises by raising productivity and expanding the internal labor market at in-house subcontract enterprises.

• Food Engineering Progress
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• v.21 no.1
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• pp.57-63
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• 2017

This study investigated the effects of 27.12 MHz radio frequency (RF) heating on heat transfer phenomena during the thawing process of frozen food. To determine the velocity of the RF thawing machine, samples were frozen at $-80^{\circ}C$ and subjected to different power treatments. The phase change times (-5 to $0^{\circ}C$) of frozen radish were 30, 26, 13, and 8 min; those of pork sirloin were 38, 25, 11, and 5 min; those of rump were 23, 17, 11, and 6 min; those of chicken breast were 42, 29, 13, and 9 min; and those of tuna were 25, 23, 10, and 5 min at 50, 100, 200, and 400 W, respectively. The heating limit temperatures of the radish, pork sirloin, rump, chicken breast, and tuna samples were 19.5, 9.2, 21.8, 8.8, and $16.8^{\circ}C$ at 50 W; 23.5, 15.5, 27.3, 12.3, and $19^{\circ}C$ at 100 W; 42, 26.9, 45.7, 22.1, and $39.4^{\circ}C$ at 200 W; and 48.5, 54.7, 63.6, 57.3, and $44.9^{\circ}C$ at 400 W. These results suggest that high-power RF improves thawing velocity and heating limit temperatures, and that an improvement on the operation of the RF thawing machine, according to food temperatures, is needed.

• Korean Journal of Poultry Science
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• v.46 no.1
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• pp.25-30
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• 2019

This study was conducted to investigate basic data of development for appropriate management system in broiler. Data such as ages at marketing, livability, body weight, etc. were collected from a total of 53 broiler farms located in Chungnam, Chungbuk, Jeollanam, Jeollabuk, Gyeongbuk. 1. Average of ages at marketing were 32 days. Those of windowless house and open-type house were 31.96 and 32.03 days, respectively. The significant difference among four seasons was highly found (P<0.001). The longest ages at marketing were 32.86 days in winter. Average of livability was 96.25%. According to type of chick house, those of windowless house and open-type house were 95.93% and 96.59%, respectively. The livability according to season showed significant difference (P<0.05). The highest livability was 97.39% in autumn. However, the lowest livability was 95.36% in summer. 2. Average body weight at marketing was 1.62 kg. The significant difference was found in marketing weight by season (P<0.05). The heaviest body weight was 1.65 kg in winter, but the lowest weight was 1.60 kg in summer. Average of FCR was 1.62. the significant differences according to the season were highly found (P<0.01). Especially, the best FCR was 1.59 in autumn. Average cycles of marketing was 5.70. The significant differences according to farms size were found (P<0.05), cycles of small farms and big farms were 5.8 and 5.3, respectively. The ages at marketing were highly correlated with marketing weight (r=0.684) and feed conversion (r=0.439). The correlation between feed conversion and livability was highly negative (r=-0.614). According to the above result, livability and body weight at marketing were badly detected in summer. In conclusion, broiler farms should be controlled through properly environmental management system for improvement of performances.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.292-299
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• 2018

In a survey in which farmers were asked about their levels of satisfaction with agricultural machines, Japanese products scored higher than local products by 1.2, 1.3, and 1.4 times for tractors, combine harvesters, and rice transplanter, respectively. Japanese products corresponded to generally high satisfaction levels in terms of operating performance, operability, frequency of breakdowns, and durability, excluding sales price and after-sales services. Effective countermeasures through quality improvement are therefore necessary for Korean products. Furthermore, a survey of dealers showed that the components and consumables for core agricultural machines had high frequencies of breakdowns and repairs. Four major components of tractors represented 85.3% of all breakdowns and repairs, five components of combine harvesters represented 89.6%, and three components of rice transplanters represented 80.5%. Moreover, a comparison of the technological levels between local and imported machines showed that the local machines' levels were at 60-100% for tractors, 70-100% for combine harvesters, and 70-95% for rice transplanters. Small and mid-sized tractors, 4 interrow combine harvesters, and 6 interrow rice transplanters showed similar levels of technology. The results of the analysis suggest that action is urgently needed at a policy level to establish an agricultural machinery component research center for the development, production, and supply of commonly-used components, with the participation of manufacturers of agricultural machines and components, in order to enhance the competitiveness of local manufacturers and to revitalize the agricultural machine market.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.