• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1193-1201
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• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.

• Journal of Naturopathy
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• v.10 no.2
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• pp.114-119
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• 2021

Background: Many anionic phytoncides exist in the forest. Purpose: This study aimed to measure and investigate the number of negative ions in aerosol composition in Samdasu Forest, Jeju. Methods: We counted the number of negative ions in the aerosol with an anion meter at 17 points in the Samdasu forest area. Results: The average number of negative ions measured at 17 points in the aerosol of the Samdasu forest area was 719.7 ions/cm³, the temperature was 25.2℃, the humidity was 80.9%, the altitude was 503 m, and the wind speed was 0.6 m/sec. When looking at the content of anion number in the air quality in order, the highest place was waterfall-entrance-course R-course B- pine forest- course exit> exit wetland. The highest altitude of the collection point was in the order of pine forest-course R-course exit-waterfall-course B- exit wetland-entrance. The elevation difference in elevation was statistically significant. There was no correlation between altitude and anion content. It could be seen that the air quality fluctuates from time to time. Conclusions: A large amount of anionic phytoncide was contained in the air quality in Samdasu Forest in the over results. Therefore, Samdasu Forest is a helpful area as a place to visiting. The visit to the Jeju region, which has a high content of anionic phytoncide, has provided essential information that it has beneficial conditions for health management.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.117-124
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• 2023

Through reorganization in 2008, The ministry of Agriculture, Food and Rural Affairs integrated management of the food industry by transferred functions which was scattered in the Ministry of Health and Welfare, and established comprehensive policies covering the primary, secondary, and tertiary industries. In the agricultural industry sector, new business concepts such as smart farm and food tech have recently emerged alongside the fourth industrial revolution. In order for the Ministry of Agriculture, Food, and Rural Affairs to develop appropriate policies for the fourth industrial revolution, it is necessary to accurately estimate the size of agricultural and livestock-related businesses. In 2017, the Ministry of Agriculture, Food, and Rural Affairs initiated research for the agriculture, livestock and food industry's special classification, which was approved by the National Statistical Office in 2020. The estimation of the agriculture, livestock and food industry's size based on special classification is crucial because it has a substantial impact on the formulation and significance of policies. In this paper, the appropriate rate was derived from samples extracted from the special classification and the Korean standard industrial classification. Proposed are a method for estimating the population of the agricultural and livestock food industry, as well as a method for calculating the appropriate rate that more accurately reflects the population than the method currently in use.

• Journal of Nutrition and Health
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• v.56 no.2
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• pp.184-202
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• 2023

Purpose: This study investigates the necessary educational materials from the perspective of caregivers managing food allergies of preschoolers. Methods: An online survey enrolled 400 caregivers of preschoolers with food allergies. The study was conducted in July 2022, and data were analyzed using the IBM SPSS Statistics 25. Results: The caregivers of preschoolers with food allergies showed low food allergy knowledge. The highest percentage of incorrect answers were for items related to the cause (74.2%) and response (65.2%) to food allergies. Moreover, categorizing the levels of knowledge as high, medium, and low, we found that caregivers with younger children exhibited a better understanding of food allergies. Approximately 56.9% of subjects in the high class were caregivers with preschoolers under three years, whereas caregivers with preschoolers over four years comprised 43.2% of the high-class subjects. Regarding food allergy treatment, four questions measured how well the caregivers tended to the children. With higher levels of knowledge, caregivers were more likely to read nutrient information and check for food allergens. The caregivers of preschoolers who were clinically diagnosed with food allergies demonstrated a higher percentage of using separate ingredients and cooking utensils. Conclusion: This study shows how the caregivers' knowledge levels are critical in managing and treating food allergies among preschoolers. With caregivers' lower knowledge of food allergies and preschoolers younger than four years, self-diagnosis of food allergies and existing food allergies were not managed efficiently. Hence, customized education for caregivers is essential to improve their knowledge level regarding limiting foods that may cause allergies, reading food labels, and using ingredients and cooking utensils separately.

• Korean Journal of Veterinary Service
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• v.45 no.4
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• pp.325-330
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• 2022

Distichiasis is one of the diseases commonly encountered in companion animals, and these abnormal eyelashes cause corneal ulcers, continuous eye irritation, eye pain, glare, epiphora, foreign body sensation and can cause corneal opacity and vision loss in severe cases. In this study, an eyelash epilation needle for animals was developed and applied to a real case, and the results were observed. In a case of corneal ulcer caused by distichiasis of a 2-year-old Shih Tzu, a high-frequency surgical instrument for animals was converted into an electric epilation needle to attempt a procedure to destroy the eyelash hair follicles on the upper eyelid. A epilation needle was developed to have a diameter of 0.1 mm and a length of 4 mm at the end of the handle of DOCTANZ 400, an electrosurgical instrument for animals only. In the procedure, 2~3 mm of an epilation needle was inserted into the hair follicle, and 1 watt of electric power was applied to the hair follicle for about 5 sec. to carry out electrolysis until white bubbles were generated around the meibomian glands thereby destroying the hair follicle. As a result, no eyelashes grew any longer in the treated area indicating that the treatment was successful. It is hoped that the method developed in this study will be applied so that it will be widely used as a treatment method for distichiasis in companion animals that can be frequently seen hereafter.

• Smart Media Journal
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• v.12 no.10
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• pp.55-62
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• 2023

Innovation and change are occurring rapidly in the agriculture and livestock industry, and new technologies such as smart bams are being introduced, and data that can be used to control equipment is being collected by utilizing various sensors. However, there are various challenges in the operation of bams, and virtual sensor technology is needed to solve these challenges. In this paper, we define various data items and sensor data types used in livestock farms, study cases that utilize virtual sensors in other fields, and implement and design a virtual sensor system for the final smart livestock farm. MBE and EVRMSE were used to evaluate the finalized system and analyze performance indicators. As a result of collecting and managing data using virtual sensors, there was no obvious difference in data values from physical sensors, showing satisfactory results. By utilizing the virtual sensor system in smart livestock farms, innovation and efficiency improvement can be expected in various areas such as livestock operation and livestock health status monitoring. This paper proposes an innovative method of data collection and management by utilizing virtual sensor technology in the field of smart livestock, and has obtained important results in verifying its performance. As a future research task, we would like to explore the connection of digital livestock using virtual sensors.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.47-60
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• 2023

A thorough inventory of ship emissions, particularly ship's emission of in-port area is necessary to identify significant sources of exhaust gases such as NOx, SOx, PM, and CO₂ and trends in emission levels over time, and reduce their serious effects on the environment and human health. Therefore, the goal of this study is to assess the volume of emissions from ships in Mokpo port, which serves as a gateway to the southwest coast of Korea, using a bottom-up methodology and data from the automatic identification system (AIS) and the Korean Port Management Information System (Port-MIS). In this work, an analysis of ship movement utilizing AIS data and an actual set of data on ship specification were gathered. By examining ship movement using AIS data, We also proposed a new approach for identifying cruising/maneuvering mode. Finally, the results were classified by ship operating mode, by exhaust gas, by ship type, and by berth, which provides a thorough and in-depth analysis of the air pollution caused by ships in Mokpo port.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.445-454
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• 2023

Recently, various fault diagnosis studies are being conducted utilizing data from collaborative robots. Existing studies performing fault diagnosis on collaborative robots use static data collected based on the assumed operation of predefined devices. Therefore, the fault diagnosis model has a limitation of increasing dependency on the learned data patterns. Additionally, there is a limitation in that a diagnosis reflecting the characteristics of collaborative robots operating with multiple joints could not be conducted due to experiments using a single motor. This paper proposes an LSTM diagnostic model that can overcome these two limitations. The proposed method selects representative normal patterns using the correlation analysis of vibration and current data in single-axis and multi-axis work environments, and generates residual patterns through differences from the normal representative patterns. An LSTM model that can perform gear wear diagnosis for each axis is created using the generated residual patterns as inputs. This fault diagnosis model can not only reduce the dependence on the model's learning data patterns through representative patterns for each operation, but also diagnose faults occurring during multi-axis operation. Finally, reflecting both internal and external data characteristics, the fault diagnosis performance was improved, showing a high diagnostic performance of 98.57%.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.815-822
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• 2023

Organic pollution is one of the most common forms of water contamination. Under the Water Quality Conservation Act, indicators for measuring organic substances include BOD, COD, and TOC. Analysis of BOD and COD is labor-intensive, and in the case of organic substances where biological decomposition is not feasible or toxic substances are present, the accuracy is often low. Therefore, the Ministry of Environment is shifting towards TOC-centric management. With advancements in sensor technology today, various parameters can be monitored using sensors. In this study, digital monitoring of river TOC using a spectrophotometer called Spectro::lyser V3 was conducted. Initially, experiments were carried out at the Andong River Experiment Center to assess the applicability of the measurement equipment. Subsequently, data collected at the confluence of the Nakdong River was analyzed for the spatial distribution of TOC using the Kriging technique. This research proposes the utilization of sensors for river TOC monitoring and spatial distribution analysis. Real-time monitoring of changes in river TOC concentration can serve as fundamental data for pollution monitoring and response. Sensor-based river monitoring offers advantages in terms of temporal resolution and real-time data acquisition. When various spatial information interpretation methods are applied, it is expected to contribute to diverse studies such as aquatic ecological health, river water source selection, and stratification analysis in the future.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.