• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.5
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• pp.51-68
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• 2023

Due to the recent integrated water management policy, it is important to identify a reliable supply amount for establishing an agricultural water supply plan. In order to identify the amount of agricultural water supply, it is essential to calculate the discharge by measuring the water level and flow velocity of reservoirs and canal agricultural water, and quality control to ensure reliability must be preceded. Unlike agricultural reservoirs, canal agricultural water are more sensitive to the surrounding environment and reservoir irrigation methods (continuous, intermittent irrigation, etc.), making it difficult to estimate general water level patterns and at the same time a lot of erroneous data. The Korea Rural Community Corporation is applying a filter technique as a quality control method capable of processing large quantities and real-time processing of canal agricultural water level data, and applicability evaluation is needed. In this study, the types of errors generated by the automatic water level measurement system were first determined. In addition, by using the manual quality control data, a technique with high applicability is derived by comparing and analyzing data calibrated with Gaussian, Savitzky-Golay, Hampel, and Median filter techniques, RMSE, and NSE, and the optimal parameters of the technique range was derived. As a result, the applicability of the Median filter was evaluated the highest, and the optimal parameters were derived in the range of 120min to 240min. Through the results of this study, it is judged that it can be used for quantitative evaluation to establish an agricultural water supply plan.

• Korean Journal of Community Nutrition
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• v.9 no.2
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• pp.191-203
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• 2004

This study was performed to compare the foodservice management practices in the employee feeding operations of Jeonnam and Chungchong area. Questionnaires were developed and mailed to 160 dietitians with management in employee foodservice of Jeonnam and Chungchong area. Completed questionnaires were received from 124 dietitians with a response rate of 77.5%. The results of this study can be summarized as follows:. Age, work experience, concurrent position and work time of dietitians were significantly higher in the Chungchong area than those in the Jeonnam area. Times of meals and amount of meals served per day in the Chungchong area were significantly higher than those in the Jeonnam area. The type of menu by foodservice operation was high non-selective menu in both areas, especially non-selective menu was high in self-operated place whereas selective menu was high in contract management. Period of cycle menu was 10-15 days in Jeonnam area, but that was 7 days in Chungchong area and so cycle menu of both areas was significantly different (p ＜ 0.001). Most considerable factor in menu planning was preference in Jeonnam area and was cost in the Chungchong area. Food purchasing method was used mostly by automatic computerized order in the Jeonnam area whereas telephone or mail order was high in the Chungchong area.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.140-146
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• 2019

In order to manage non-point sources, the paradigm of the system should be changed so that the management of non-point sources will be systematized from the beginning of the use and development of the land. It is necessary to change the method of national subsidy support and poeration plan for the non-point source management area. In order to increase the effectiveness of the non-point source reduction project, it is necessary to provide a minimum support ratio and to provide additional support according to the performance of the local government. A new system should be established to evaluate the performance of non-point source reduction projects and to monitor the operational effectiveness. It is necessary to establish the related rules that can lead the local government to take responsible administration so that the local governments faithfully carry out the non-point source reduction project and achieve the planned achievement and become the sustainable maintenance. Alternative solutions are needed, such as problems with the use of $100{\mu}m$ filter in automatic sampling and analysis, timely acquisition of water sampling and analysis during rainfall, and effective management of non-point sources network operation management. As an alternative, it is necessary to consider improving the performance of sampling and analysis equipment, and operate the base station. In addition, countermeasures are needed if the amount of pollutant reduction according to the non-point source reduction facility promoted by the national subsidy is required to be used as the development load of the TMDLs. As an alternative, it is possible to consider supporting incentive type of part of the maintenance cost of the non-point source reduction facility depending on the amount of pollutants reduction.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of Bio-Environment Control
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• v.22 no.4
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• pp.341-348
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• 2013

Maintenance of adequate soil tension or content during the period of crop growth is necessary to support optimum plant growth and yields. A better understanding of soil tension and content for precision irrigation would allow optimal soil water condition to crops and minimize the adverse effects of water stress on crop growth and development. This research reports on a comparison of soil water tension and content variations in differently textured soils over time under drip irrigation using two different water management methods, i.e. pulse time and required water irrigation methods. The pulse time-based irrigation was performed by turning the solenoid valve on and off for preset times to allow the wetting front to disperse in root zone before additional water was applied. The required water estimation method was a new water control logic designed by Rural Development Administration that applies the amount of water required based on a conversion of the measured water tension into water content. The use of the pulse time irrigation method under drip irrigation at a high tension of -20 kPa and high temperatures over $30^{\circ}C$ was not successful at maintaining moisture tensions within an appropriate range of 5 kPa because the preset irrigation times used for water control could not compensate for the change in evapotranspiration during day and night. The response time and pattern of water contents for all of the tested soils measured with capacitance-based sensor probes were faster and more direct than those of water tensions measured with porous and ceramic cup-based tensiometers when water was applied, indicating water content would be a better control variable for automatic irrigation. The required water estimation-based irrigation method provided relatively stable control of moisture tension, even though somewhat lower tension values were obtained as compared to the target tension of -20 kPa, indicating that growers could expect to be effective in controlling low tensions ranging from -10 to -20 kPa with the required water estimation system.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.221-241
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• 2018

As we enter the knowledge society, the importance of information as a new form of capital is being emphasized. The importance of information classification is also increasing for efficient management of digital information produced exponentially. In this study, we tried to automatically classify and provide tailored information that can help companies decide to make technology commercialization. Therefore, we propose a method to classify information based on Korea Standard Industry Classification (KSIC), which indicates the business characteristics of enterprises. The classification of information or documents has been largely based on machine learning, but there is not enough training data categorized on the basis of KSIC. Therefore, this study applied the method of calculating similarity between documents. Specifically, a method and a model for presenting the most appropriate KSIC code are proposed by collecting explanatory texts of each code of KSIC and calculating the similarity with the classification object document using the vector space model. The IPC data were collected and classified by KSIC. And then verified the methodology by comparing it with the KSIC-IPC concordance table provided by the Korean Intellectual Property Office. As a result of the verification, the highest agreement was obtained when the LT method, which is a kind of TF-IDF calculation formula, was applied. At this time, the degree of match of the first rank matching KSIC was 53% and the cumulative match of the fifth ranking was 76%. Through this, it can be confirmed that KSIC classification of technology, industry, and market information that SMEs need more quantitatively and objectively is possible. In addition, it is considered that the methods and results provided in this study can be used as a basic data to help the qualitative judgment of experts in creating a linkage table between heterogeneous classification systems.

• Tuberculosis and Respiratory Diseases
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• v.52 no.2
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• pp.156-165
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• 2002

Background: A tracheal stenosis is caused by mucosal ischemic injury related to a high cuff pressure ($P_{cuff}$) of the endotracheal tube. In contrast, aspiration of the upper airway secretion and impaired gas exchange due to cuff leakage is related to a low $P_{cuff}$. To prevent these complications, the $P_{cuff}$ should be kept appropriately because the appropriate $P_{cuff}$ appears to change according to the patient's daily respiratory mechanics. However, the constant cuff volume($V_{cuff}$) has frequently been instilled to the cuff balloon on a daily basis to maintain the optimal $P_{cuff}$ instead of monitoring the $P_{cuff}$ directly at the patients' bedside. To address the necessity of continuous $P_{cuff}$ monitoring, the change in the $P_{cuff}$ was evaluated at various $V_{cuff}$ levels on a daily basis in patients with long-term mechanical ventilation. The utility of mercury column sphygmomanometer for the continuous monitoring $P_{cuff}$ was also investigated. Method: The change in $P_{cuff}$ according to the increase in $V_{cuff}$ was observed in 17 patients with prolonged endotracheal intubation for mechanical ventilation for 2 week or more. This maneuver measured the change in $P_{cuff}$ daily during the mechanical ventilation days. In addition, the $P_{cuff}$ measured by mercury column sphygmomanometer was compared with the $P_{cuff}$ measured by an automatic cuff pressure manager. Results : There were no statistically significant changes of $P_{cuff}$ during more than 14 days of intubation for mechanical ventilation. However the $V_{cuff}$ required to maintain the appropriate $P_{cuff}$ varied from 1.9 cc to 9.6 cc. In addition, the intra-individual variation of the $P_{cuff}$ was observed from 10 $cmH_2O$ to 46 $cmH_2O$ at constant 3 cc $V_{cuff}$. The $P_{cuff}$ measured by the bedside mercury column sphygmomanometer is well coincident with that measured by the automatic cuff pressure manager. Conclusion: Continuous monitoring and management of the $P_{cuff}$ to maintain the appropriate $P_{cuff}$ level in order to prevent cuff related problems during long-term mechanical ventilation is recommended. For this purpose, mercury column sphygmomanometer may replace the specific cuff pressure monitoring equipment.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.