• Journal of the Korean Society of Food Culture
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• v.6 no.2
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• pp.185-197
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• 1991

An eating behavior research was done with 50 females at a buffet styled restaurant during their lunch time. Of the respondents, 52.0% were professional and 54.0% were graduate school graduates. Of the respondents, 58.0% of the company were friends and 24.0% were relatives. The average time period of eating was $93.0{\pm}23.4$ minutes. The average frequency of taking food was $4.0{\pm}1.1$ and the average frequency of taking food after satiety was $1.4{\pm}0.8$. It is significant that lower frequency of food consumption was directly proportional to the age groups of respondents. The average selected food items were $30.4{\pm}7.1$ out of 175 and the average weight of the consumed food was $995.0{\pm}240.9$ g. The older age group chose a similar number of food items, but the amount of each food item was considerably less than younger. So the younger the age group was, the more they ate. The average food items at one time was $7.1{\pm}2.2$ and the average food weight time was $233.7{\pm}69.7$ g. The percentage of respondents who evaluated themselves as 'ate too much' was 70.0% and those who evaluate themselves 'ate properly' was 14.0%. Most of them were satisfied with the buffet service. The average of number of food items consumed by respondents before cooking was $50.5{\pm}8.9$. The consumption of calories and nutrients was compared with the Korean Daily Recommended Dietary Allowances. The consumed calories were 60.9% of RDAs, protein 104.4%, calcium 77.1%, iron 129.8%, vitamin A 66.5%, thiamin 96.0%, riboflavin 95.7%, niacin126.6% and ascorbic acid 112.3%. This data exceeded 1/3 of the Korean Daily RDAs tremendously and tells us extreme overeating. The energy ratio of carbohydrate: fat: protein was 51.6: 29.9: 18.5. Caloric consumption of animal food was 27.9% and the consumption rate of the other nutrients from animal food was considerably high. But the consumption rate of vitamin A was 90.9% from vegetable groups. Accoding to this study, buffet service gives some advantages. It gives customers an good opportunity to vary their food intake, which enhances eating experiences and can cause an improvemont of food habits. But overeating is a problem. Therefore, we think it is necessary for those women who have influence over their family's food selection, to have nutrition education about a desirable order of eating a meal, food selection, and health problems due to overeating at buffet styled restaurant. There should be some improvement in the management of buffet service. For example, proper temperature, texture, and freshness of the food should be maintained. Prevention of mixed food smells should be considered as well. To lower the price it is desirable to reduce the number of similar items and to use seasonal food as much as possible. A buffet styled restaurant with less food items with cheaper prices is recommended. Various traditional food should be developed for the menu items. We expect buffet services to be sutable to maintain good health and to be popular to any eater.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.199-205
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• 1998

Cullet Quality Control in auto glass bottle factory is the most important in recent days because of the increasing cost of materials in glass bottle. Since the composition of plate glass cullet is similar, the cullet quality using plate cullet in glass bottle factory is easily controlled. In addition to this, the price of plate glass cullet is so low that the cost reduction can be achieved. If the ratio of plate glass cullet and gush is over 25%, the liquidity of glass water become worse, which is caused by different compositions and viscosity of the components. As a results, Furnace bottom temperature becomes low and glass water becomes inhomogeneous. Thus production efficiency of glass bottle becomes low because of increasing devitrification in Dead Corner part in glass melting furnace. Three experimental methods – (1) increasing melting temperature, (2) using Booster, (3) using bubbler – were performed to increase the furnace bottom temperature and glass water homogeneity. The amounts of plate glass cullet was able to increase up to 90%, 70% and 60% without any devitrification using booster, bubbler and the method of glass melting temperature increase from $1480^{\circ}C$ to $1560^{\circ}C$ respectively. It is not possible to increase the glass melting temperature without the reduction of furnace operation time and the increase of fuel cost. The booster process has disadvantage of much electric energy consumption. Since the bubbler process uses physical convection of melting glass based on compression air, the homogeneity of molten glass is not so good as that of booster process but it can reduce the cost of glass bottle.

• Journal of the Korean Electrochemical Society
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• v.24 no.4
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• pp.120-132
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• 2021

Although the development of high-Nickel is being actively carried out to solve the capacity limitation and the high price of raw cobalt due to the limitation of high voltage use of the existing LiCoO₂, the deterioration of the battery characteristics due to the decrease in structural stability and increase of the Ni content. It is an important cause of delaying commercialization. Therefore, in order to increase the high stability of the Ni-rich ternary cathod material LiNi_0.6Co_0.2Mn_0.2O₂, precursor Ni_0.6Co_0.2Mn_0.2-x(OH)₂/xTiO₂ was prepared using a nanosized TiO₂ suspension type source for uniform Ti substitution in the precursor. It was mixed with Li₂CO₃, and after heating, the cathode active material LiNi_0.6Co_0.2Mn_0.2-xTi_xO₂ was synthesized, and the physical properties according to the Ti content were compared. Through FE-SEM and EDS mapping analysis, it was confirmed that a positive electrode active material having a uniform particle size was prepared through Ti-substituted spherical precursor and Particle Size Analyzer and internal density and strength were increased, XRD structure analysis and ICP-MS quantitative analysis confirmed that the capacity was effectively maintained even when the Ti-substituted positive electrode active material was manufactured and charging and discharging were continued at high temperature and high voltage.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.73-82
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• 2009

Due to the many advantages including low price, low power consumption, and miniaturization, the CMOS camera has been utilized in many applications, including mobile phones, the automotive industry, medical sciences and sensoring, robotic controls, and research in the security field. In particular, the 360 degree omni-directional camera when utilized in multi-camera applications has displayed issues of software nature, interface communication management, delays, and a complicated image display control. Other issues include energy management problems, and miniaturization of a multi-camera in the hardware field. Traditional CMOS camera systems are comprised of an embedded system that consists of a high-performance MCU enabling a camera to send and receive images and a multi-layer system similar to an individual control system that consists of the camera's high performance Micro Controller Unit. We proposed the SL-AVS (Small Size/Low power Around-View System) to be able to control a camera while collecting image data using a high speed synchronization technique on the foundation of a single layer low performance MCU. It is an initial model of the omni-directional camera that takes images from a 360 view drawing from several CMOS camera utilizing a 110 degree view. We then connected a single MCU with four low-power CMOS cameras and implemented controls that include synchronization, controlling, and transmit/receive functions of individual camera compared with the traditional system. The synchronization of the respective cameras were controlled and then memorized by handling each interrupt through the MCU. We were able to improve the efficiency of data transmission that minimizes re-synchronization amongst a target, the CMOS camera, and the MCU. Further, depending on the choice of users, respective or groups of images divided into 4 domains were then provided with a target. We finally analyzed and compared the performance of the developed camera system including the synchronization and time of data transfer and image data loss, etc.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.