• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.105-113
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• 2019

Convergence education, which is operated by many engineering colleges, is mainly led by government-led projects. Convergence majors are established in consideration of the research field of the university professors rather than systematically analyzing the needs of the industry. The purpose of this study is to present the directions of convergence technology education related to new industry fields by analyzing industry needs. Participants were 299 industrial workers in various fields. Instrument consisted of three parts: necessity for convergence education, demand for convergence new technology education from industry perspective, and opinions about undergraduate convergence education. As a result, it was found that the level of awareness of industry needs for fusion technology education was high, and it was confirmed that there is a high demand for IoT convergence, bio-health, advanced new material, and renewable energy fields among convergence technology fields. In addition, the results of the industry demand for convergence new technology education were presented. The suggestions for expectations, problems, and improvements in undergraduate education were presented and implications for convergence technology education were discussed based on the results of the study.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.506-514
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• 2019

This study classified the different types of service attributes being provided through cable VOD services and looked at how the key service attribute types affect the willingness to use paid VOD for each group of paid and non-experienced users. Studies have shown that for a group of non-experienced people, 'content information-oriented attributes' have the greatest impact, and for a group of experienced people, 'convenience-oriented attributes' have the greatest impact. Thus, expanding users of paid VOD services requires setting up step-by-step strategies that match their respective collective characteristics. For a group of non-experienced people, it is necessary to take a direct persuasion strategy through the provision of relevant information and an indirect approach strategy through the expansion of promotion opportunities, and for an experienced group, a strategy to expand functional convenience.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.110-110
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• 2016

도시 유역의 강우-유출 모의에는 지표 투수율 및 하수관거 영향 등 인위적 배수계통의 영향을 고려할 수 있는 도시유출모형이 널리 이용되고 있으며, 모형 검증을 통해 모의 성능을 평가한다. 도시유출모형의 검증은 일반적인 강우-유출 모형과 같이 강우사상별 유량의 관측시계열과 모의시계열의 목적함수가 최소가 되는 최적 매개변수를 탐색하는 과정이다. 도시유출모형의 검증에서 발생하는 문제점은 크게 다음과 같다. 첫째, 대규모 도시 유역의 복잡하고 다양한 하수관거에 대한 최적매개변수를 관거별로 구하는 것은 물리적으로 불가능하다. 따라서 동일 배수분구내 하수관거의 매개변수 값은 동일하다고 가정하거나, 모형 단순화 과정을 통해 매개변수의 물리적 범위 내에서 최적해를 탐색해야 하는 단순화에서 기인한 불확실성이 있다. 둘째, 다양한 매개변수들의 물리적 범위를 고려하기 위해서는 전역최적화기법이 유효하다. 그러나 전역최적화 종류, 목적함수, 모의횟수, 목표성능별 최적 매개변수 결과가 각각 다르므로 추정된 최적 매개변수의 범위에 대한 불확실성이 있다. 이에 본 연구에서는 Bayesian 모형과 EPA SWMM(Storm Water Management Model)을 연계하여 도시유출모형의 매개변수 불확실성을 정량적으로 분석할 수 있는 모형을 제안하고자 한다. 이를 위해 서울 우이천 유역을 대상으로 SWMM 모형을 구축하고, 절단 정규분포(truncated Gaussian distribution)를 사전분포(prior)로 가정하여 매개변수의 물리적 범위를 고려하였다. 최종적으로 결합확률분포로 계산된 각 매개변수간 사후분포를 통해 모의된 유출량의 불확실성을 정량적으로 분석하였다. 본 연구에서 제안된 모형은 대규모 도시 유역의 도시유출모형 구축 시 다양한 매개변수의 물리적 범위를 고려한 최적화와 동시에 내재된 불확실성을 정량적으로 분석할 수 있으므로, 침수예측 및 홍수예경보 등의 문제에서 상당한 신뢰성을 확보할 수 있을 것으로 판단된다.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.21-28
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• 2021

In this study, we propose a deep learning-based NILM technique using actual measured power data for 5 kinds of home appliances and verify its effectiveness. For about 3 weeks, the active power of the central power measuring device and five kinds of home appliances (refrigerator, induction, TV, washing machine, air cleaner) was individually measured. The preprocessing method of the measured data was introduced, and characteristics of each household appliance were analyzed through spectogram analysis. The characteristics of each household appliance are organized into a learning data set. All the power data measured by the central power measuring device and 5 kinds of home appliances were time-series mapping, and training was performed using a LSTM neural network, which is excellent for time series data prediction. An algorithm that can disaggregate five types of energies using only the power data of the main central power measuring device is proposed.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.171-183
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• 2022

The purpose of this paper is to study the direction of improving kiosk design for convenient use by all users by increasing the usability of kiosks based on universal design principles. The direction of design improvement was studied by deriving essential improvements through additional surveys verifying the results of age-specific surveys and analysis related to the use of kiosks. The results of the study are as follows. High contrast between kiosk screen background and design elements, yellow color, and outline design elements increase readability. Then, reduce and enlarge the font based on 10pt. In addition, in consideration of wheelchair passengers, the area where the lower part cannot be designed and the minimum height of adjusting the height of the kiosk were derived. In the future, kiosk design requires a design and system that can diversify the functions of kiosks according to individual characteristics, and design should be focused on the application of universal design. Since this study has limited research subjects, further studies on various samples are required, and verification studies related to color and readability will also be conducted.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.23-31
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• 2022

This study analyzed the actual frozen container operation data of Starcool provided by H Shipping. Through interviews with H's field experts, only Critical and Fatal Alarms among the four failure alarms were defined as failures, and it was confirmed that using all variables due to the nature of frozen containers resulted in cost inefficiency. Therefore, this study proposes a method for detecting failure of frozen containers through characteristic importance and PCA techniques. To improve the performance of the model, we select variables based on feature importance through tree series models such as XGBoost and LGBoost, and use PCA to reduce the dimension of the entire variables for each model. The boosting-based XGBoost and LGBoost techniques showed that the results of the model proposed in this study improved the reproduction rate by 0.36 and 0.39 respectively compared to the results of supervised learning using all 62 variables.

• Journal of Food Hygiene and Safety
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• v.37 no.2
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• pp.55-62
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• 2022

The bacterial soft-rot disease is one of the most critical diseases in vegetables such as Chinese cabbage. The researchers isolated two bacteria (Pseudomonas kribbensis and Pantoea vagans) from diseased tissue samples of Chinese cabbages and confirmed them as being the strains that cause soft-rot disease. Lactic-acid bacteria (LAB), were screened and used to control soft-rot disease bacteria. The researchers tested the treatments with hypochlorous acid water (HAW) and LAB supernatant to control soft-rot disease bacteria. The tests confirmed that treatments with the HAW (over 120 ppm) or LAB (Lactobacillus plantarum PL203) culture supernatants (0.5 mL) completely controlled both P. kribbensis and P. vagans.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.473-490
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• 2022

This study was conducted to examine Sci-Hub, which provides the original text of academic papers to be provided for a fee by bypassing copyright, and to establish a basic basis for understanding the usage behavior of researchers with access restriction in Korea by analyzing the domestic Sci-Hub usage based on the dataset released by Sci-Hub in 2017. Therefore, after grasping the current status of the world related to Sci-Hub, the categories were set and analyzed by region where the dataset was downloaded, subject matter of academic papers, publisher, OA status, and published year. As a result of the study, the most downloaded areas were Seoul and the metropolitan area, and papers and journals in the field of natural science were downloaded the most, and about 20% of papers were in Open Access state. The papers published between 2010 and 2017 were the most downloaded, and IEEE's papers were the most downloaded, showing that recently published academic papers in the natural sciences were the most downloaded by the time they were downloaded.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.29-36
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• 2022

In this paper, we propose an efficient agricultural products price prediction model based on dataset which provided in DACON. This model is XGBoost and CatBoost, and as an algorithm of the Gradient Boosting series, the average accuracy and execution time are superior to the existing Logistic Regression and Random Forest. Based on these advantages, we design a machine learning model that predicts prices 1 week, 2 weeks, and 4 weeks from the previous prices of agricultural products. The XGBoost model can derive the best performance by adjusting hyperparameters using the XGBoost Regressor library, which is a regression model. The implemented model is verified using the API provided by DACON, and performance evaluation is performed for each model. Because XGBoost conducts its own overfitting regulation, it derives excellent performance despite a small dataset, but it was found that the performance was lower than LGBM in terms of temporal performance such as learning time and prediction time.

• Journal of the Korean Geotechnical Society
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• v.22 no.7
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• pp.55-64
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• 2006

Shallow failures of slopes in weathered soils are caused by infiltration caused by prolonged rainfall. These failures are mainly triggered by the deepening of the wetting band accompanied by a decrease in suction induced by the water infiltration. In this paper, hysteresis on soil-water characteristic curve (SWCC) of granite and gneiss weathered soils is investigated using transient flow analysis respectively. Each case was subjected to artificial rainfall intensities and time duration depending on the laboratory-based drying and wetting processes. The results show that the unsaturated seepage on weathered slopes are very much affected by the initial suction of soils and unsaturated permeability of the soils. In addition, a granite weathered soil has a lower air-entry value, residual matric suction, and wetting front suction and less hysteresis loop than a gneiss weathered soil.