• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.5
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• pp.469-475
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• 2002

The rotating biological contactor (RBC) was tested for treatment of aquacultural water in a pilot-scale recirculating aquaculture system. Performance of RBC on the treatment of nitrogen source such as total ammonia nitrogen (TAN), nitrite nitrogen and nitrate nitrogen and chemical oxygen demand (CODcr.) was evaluated. A system was stocked with nile tilapia at an initial rearing densities of $5\%$ and $7\%$ over 30 days. As increasing rearing density from $5\%$ to $7\%$, the TAN removal rates was increased from $39.4 g/m^3{\cdot}day$ to $86.0 g/m^3{\cdot}day$. But TAN removal efficiency was decreased from $24.5\%$ to $16.0\%$. The removal rate of $COD_Cr$ was higher than TAN. The RBC as an aerator was also evaluated for increasing dissolved oxygen concentration. For $5\%$ and $7\%$ of rearing density, the average aeration rate were $280 g/m^3{\cdot}day$ and $255 g/m^3{\cdot}day$, respectively.

• Clean Technology
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• v.26 no.2
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• pp.102-108
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• 2020

In recent years, packed column has been widely used in separation processes, such as absorption, desorption, distillation, and extraction, in the petrochemical, fine chemistry, and environmental industries. Packed column is used as a contacting facility for gas-liquid and liquid-liquid systems filled with random packed materials in the column. Packed column has various advantages such as low pressure drop, economical efficiency, thermally sensitive liquids, easy repairing restoration, and noxious gas treatment. The performance of a packed column is highly dependent on the maintenance of good gas and liquid distribution throughout a packed bed; thus, this is an important consideration in a design of packed column. In this study, hydraulic pressure drop, hold-up as a function of liquid load, and mass transfer in the air, air/water, and air-NH₃/water systems were studied to find the geometrical characteristic for raschig super-ring experiment dry pressure drop. Based on the results, design factors and operating conditions to handle noxious gases were obtained. The dry pressure drop of the random packing raschig super-ring was linearly increased as a function of gas capacity factor with various liquid loads in the Air/Water system. This result is lower than that of 35 mm Pall-ring, which is most commonly used in the industrial field. Also, it can be found that the hydraulic pressure drop of raschig super-ring is consistently increased by gas capacity factor with various liquid loads. When gas capacity factor with various liquid loads is increased from 1.855 to 2.323 kg^-1/2 m^-1/2 S^-1, hydraulic pressure drop increases around 17%. Finally, the liquid hold-up related to packing volume, which is a parameter of specific liquid load depending on gas capacity factor, shows consistent increase by around 3.84 kg^-1/2 m^-1/2 S^-1 of the gas capacity factor. However, liquid hold-up significantly increases above it.

• Management & Information Systems Review
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• v.22
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• pp.137-165
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• 2007

It seems high time to increase productivity by adopting e-business to overcome challenges posed by both external factors including the appreciation of Korean won, oil hikes and fierce global competition and domestic issues represented by disparities between large corporations and small and medium enterprises (SMEs), Seoul metropolitan and local cities, and export and domestic demand all of which weaken future growth engines in the Korean economy. The demands of the globalization era are for innovative changes in businessprocess and industrial structure aiming for creating new values. To this end, e-business is expected to play a core role in the sophistication of the Korean economy through new values and innovation. In order to examine business performance in e-business-adopting industries, this study analyzed the home shopping industry by closely looking into the financial ratios including the ratio of net profit to sales, the ratio of operation income to sales, the ratio of gross cost to sales cost, the ratio of gross cost to selling, general and administrative (SG&A) expense, and return of investment (ROI). This study, for best outcome, referred to corporate financial statements as a main resource to calculate financial ratios by utilizing Data Analysis, Retrieval and Transfer System (DART) of the Financial Supervisory Service, one of the Korea's financial supervisory authorities. First of all, the result of the trend analysis on the ratio of net profit to sales is as following. CJ Home Shopping has registered a remarkable increase in its ratio of net profit rate to sales since 2002 while its competitors find it hard to catch up with CJ's stunning performances. This is partly due to the efficient management compared to CJ's value of capital. Such significance, if the current trend continues, will make the front-runner assume the largest market share. On the other hand, GS Home Shopping, despite its best organized system and largest value of capital among others, lacks efficiency in management. Second of all, the result of the trend analysis on the ratio of operation income to sales is as following. Both CJ Home Shopping and GS Home Shopping have, until 2004, recorded similar growth trend. However, while CJ Home Shopping's operating income continued to increase in 2005, GS Home Shopping observed its operating income declining which resulted in the increasing income gap with CJ Home Shopping. While CJ Home Shopping with the largest market share in home shopping industryis engaged in aggressive marketing, GS Home Shopping due to its stability-driven management strategies falls behind CJ again in the ratio of operation income to sales in spite of its favorable management environment including its large capital. Companies in the Group B were established in the same year of 2001. NS Home Shopping was the first in the Group B to shift its loss to profit. Woori Home Shopping has continued to post operating loss for three consecutive years and finally was sold to Lotte Group in 2007, but since then, has registered a continuing increase in net income on sales. Third of all, the result of the trend analysis on the ratio of gross cost to sales cost is as following. Since home shopping falls into sales business, its cost of sales is much lower than that of other types of business such as manufacturing industry. Since 2002 in gross costs including cost of sales, SG&A expense, and non-operating expense, cost of sales turned out to have remarkably decreased. Group B has also posted a notable decline in the same sector since 2002. Fourth of all, the result of the trend analysis on the ratio of gross cost to SG&A expense is as following. Due to its unique characteristics, the home shopping industry usually posts ahigh ratio of SG&A expense. However, more than 80% of SG&A expense means the result of lax management and at the same time, a sharp lower net income on sales than other industries. Last but not least, the result of the trend analysis on ROI is as following. As for CJ Home Shopping, the curve of ROI looks similar to that of its investment on fixed assets. As it turned out, the company's ratio of fixed assets to operating income skyrocketed in 2004 and 2005. As far as GS Home Shopping is concerned, its fixed assets are not as much as that of CJ Home Shopping. Consequently, competition in the home shopping industry, at the moment, is among CJ, GS, Hyundai, NS and Woori Home Shoppings, and all of them need to more thoroughly manage their costs. In order for the late-comers of Group B and other home shopping companies to advance further, the current lax management should be reformed particularly on their SG&A expense sector. Provided that the total sales volume in the Internet shopping sector is projected to grow over 20 trillion won by the year 2010, it is concluded that all the participants in the home shopping industry should put strategies on efficient management on costs and expenses as their top priority rather than increase revenues, if they hope to grow even further after 2007.

• Korean Chemical Engineering Research
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• v.56 no.1
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• pp.85-95
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• 2018

In this research, a biofilter system equipped with a biofilter process and a humidifier composed of a fluidized aerobic and an anoxic reactor, was constructed to treat odorous waste air containing hydrogen sulfide, ammonia and VOC, frequently generated from pig and poultry housing facilities, compost manufacturing factories and publicly owned facilities. Its optimum operating condition was revealed and discussed. In the experiment of complex feed, the ammonia of fed-waste air was removed by ca. 75% and more than 20% at the stage of the humidifier and the biofilter, respectively. The toluene of the fed-waste air was removed by ca. 20% and more than 70% at the stage of the humidifier and the biofilter, respectively. Therefore the water-soluble ammonia and the water-insoluble toluene were treated mainly at the stage of the humidifier and the biofilter, respectively. In addition, hydrogen sulfide was almost absorbed at the stage of the humidifier so that it was not detected at the biofilter process. In the experiment of ammonia-containing feed, the ammonia of fed-waste air was removed by ca. 65% and 35% at the stage of the humidifier and the biofilter, respectively. Its removal efficiency of ammonia at the stage of the humidifier was 10% less than that in the experiment of complex feed, due to no supply of such carbon source as toluene required in the process of denitrification. In the experiments of complex feed, ammonia-containing feed with and without (instead, glucose) the addition of yeast extract, the absorption rates of ammonia-nitrogen were ca. 0.28 mg/min, 0.23 mg/min and 0.27 mg/min, respectively. The corresponding denitrification rates in the anoxic reactor were 0.42 mg/min, 0.55 mg/min and 0.27 mg/min, respectively. In addition, in the modeling of bubble column(the fluidized aerobic reactor of the humidifier) process, the value of specific surface area(a) of bubbles multiplied by enhanced mass transfer coefficient (E $K_y$) was evaluated to be 0.12/hr.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.278-286
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• 2021

In this study, based on the Computational Fluid Dynamics (CFD) simulation model developed through previous study, inner environmenct of the modified glass greenhouse was predicted. Also, suggested the optimal shape of the greenhouse and location of the heat exchangers for heat energy management of the greenhouse using the developed model. For efficient heating energy management, the glass greenhouse was modified by changing the cross-section design and the location of the heat exchanger. The optimal cross-section design was selected based on the cross-section design standard of Republic of Korea's glass greenhouse, and the Fan Coil Unit(FCU) and the radiating pipe were re-positioned based on "Standard of greenhouse environment design" to enhance energy saving efficiency. The simulation analysis was performed to predict the inner temperature distribution and heat transfer with the modified greenhouse structure using the developed inner environment prediction model. As a result of simulation, the mean temperature and uniformity of the modified greenhouse were 0.65℃, 0.75%p higher than those of the control greenhouse, respectively. Also, the maximum deviation decreased by an average of 0.25℃. And the mean age of air was 18 sec. lower than that of the control greenhouse. It was confirmed that efficient heating energy management was possible in the modified greenhouse, when considered the temperature uniformity and the ventilation performance.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.479-487
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• 2018

The purpose of this study is to analyze photochemical activity of nursery seedlings under drought stress, using chlorophyll fluorescence reaction analysis. Young nursery seedlings of tomato (Lycopersicon esculentum Mill.) and cucumber (Cucumis sativa L.), were grown under drought stress for 8 days. Analysis of chlorophyll fluorescence reaction (OJIP) and parameters, were performed to evaluate photochemical fluctuation in nursery seedlings under drought stress. Chlorophyll fluorescence reaction analysis showed maximal recorded fluorescence (P) decreased from the 5 day after treatment in tomato seedlings, while an amount of chlorophyll fluorescence increased at the J-I step. Thus, physiological activity was reduced. In cucumber seedlings, maximal recorded fluorescence (P) and maximal variable fluorescence ($F_V$) lowered from the 4 day after treatment, and chlorophyll fluorescence intensity of J-I step increased. Chlorophyll fluorescence parameter analysis showed electron transfer efficiency of PSII and PSI were significantly inhibited with decreasing $ET2_O/RC$ and $RE1_O/RC$ from the 5 day after treatment, in tomato seedlings and from the 4 day after treatment, in cucumber seedlings. $ET2_O/RC$ and $PI_{ABS}$ significantly changed. In conclusion, 6 indices such as $F_V/F_M$, $DI_O/RC$, $ET2_O/RC$, $RE1_O/RC$, $PI_{ABS}$ and $PI_{TOTAL}ABS$ were selected for determining drought stress in nursery seedlings. Drought stress factor index (DFI) was used to evaluate whether the crop was healthy or not, under drought stress. Cucumber seedlings were less resistant to drought stress than tomato seedlings, in the process of drought stress.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.249-267
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• 2021

The use of big data accumulated along with the progress of digitalization is bringing disruptive innovation to the global agricultural industry. Recently, the government is establishing an agricultural big data platform and a support organization. However, in the domestic agricultural industry, the use of big data is insufficient except for some companies in the field of cultivation and growth. In this context, this study identifies factors affecting the intention to use big data in terms of technology, organization and environment, and also confirm the moderating effect of technical field, focusing on agricultural ventures which should be the main entities in creating innovation by using big data. Research data was obtained from 309 agricultural ventures supported by the A+ Center of FACT(Foundation of AgTech Commercialization and Transfer), and was analyzed using IBM SPSS 22.0. As a result, Among technical factors, relative advantage and compatibility were found to have a significant positive (+) effect. Among organizational factors, it was found that management support had a positive (+) effect and cost had a negative (-) effect. Among environmental factors, policy support were found to have a positive (+) effect. As a result of the verification of the moderating effect of technology field, it was found that firms other than cultivation had a moderating effect that alleviated the relationship between all variables other than relative advantage, compatibility, and competitor pressure and the intention to use big data. These results suggest the following implications. First, it is necessary to select a core business that will provide opportunities to generate new profits and improve operational efficiency to agricultural ventures through the use of big data, and to increase collaboration opportunities through policy. Second, it is necessary to provide a big data analysis solution that can overcome the difficulties of analysis due to the characteristics of the agricultural industry. Third, in small organizations such as agricultural ventures, the will of the top management to reorganize the organizational culture should be preceded by a high level of understanding on the use of big data. Fourth, it is important to discover and promote successful cases that can be benchmarked at the level of SMEs and venture companies. Fifth, it will be more effective to divide the priorities of core business and support business by agricultural venture technology sector. Finally, the limitations of this study and follow-up research tasks are presented.

• 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 Practical Agriculture & Fisheries Research
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• v.11 no.1
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• pp.103-111
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• 2009

This study was carried out to determine effects of long-term supply of Cordyceps militaris mycelia on cordycepin content in milk in dairy cows. Ten Holstein cows in the early stages of lactation were divided into two groups. Control group received no supplement whereas treatment group received 6% of C. militaris mycelia of their dry matter intake for 6 months. Feed intake, milk urea nitrogen and somatic cell counts were not affected by long-term supply of C. militaris mycelia for the whole period. In addition, milk yield and milk composition were not affected by long-term supply of C. militaris mycelia at any time of the periods with the exception of milk protein content and yield. The average of milk protein content and yield from the whole period was higher for C. militaris mycelia supplement group than for the control group. As expected, cordycepin in whole blood and milk was not detected in the control group. The range of cordycepin content in the treatment was 0.31~0.38µ/ml and 0.18~0.26(µ/ml for whole blood and milk, respectively. Individual variation was found to be very high and, furthermore cordycepin was undetected in some milk samples. Thus, no clear pattern could be seen in cordycepin content in milk throughout the whole period. Overall, the results of the present study suggest that the transfer efficiency of cordycepin to milk by supplementing C. militaris mycelia in dairy cows was unpredictable and low.