• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.99-110
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• 2019

As the 4th industrial revolution progressing, manufacturers are trying to apply intelligent information technologies such as IoT(internet of things) and machine learning. In the semiconductor/LCD/tire manufacturing process, schedule plan that minimizes setup change and due date violation is very important in order to ensure efficient production. Therefore, in this paper, we suggest the deep learning based scheduling generation model minimizes setup change and due date violation in parallel machines. The proposed model learns patterns of minimizing setup change and due date violation depending on considered order using the amount of historical data. Therefore, the experiment results using three dataset depending on levels of the order list, the proposed model outperforms compared to priority rules.

• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.4-4
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• 2016

기후변화에 따른 강우패턴의 변화로 인하여 도시홍수에 의한 인명 및 재산피해가 증가하여 대응 방안의 마련이 필요한 상황이다. 도시홍수 피해원인을 조사한 기존의 연구결과(심우배, 2008)를 살펴보면, 도시유역에서의 침수피해는 배수능력부족, 하수관거 용량부족 등의 치수시설물의 성능부족이 주원인으로 나타나고 있다. 이와 같은 문제를 해결하기 위해서는 시설물의 설계기술을 향상시켜 치수능력의 증대를 기대할 수 있는 연구성과가 필요하다. 본 연구에서는 내수배제시설의 성능강화를 위하여 내수배제시설 계획수립 기준, 내수배제시설의 성능개선을 위한 정량적 설계지침 개발, 배수시스템의 개선 기법 개발을 수행하였다. 내수배제시설의 계획수립 및 기준 개발을 위하여 침수위험지역 특성에 따른 내배수시설 도입 기준과 내배수시설 설치에 침수위험 저감 효과 분석기법 및 내배수시설 최적 조합을 통한 내수배제능력 평가기법을 개발하였다. 내수배제시설의 성능개선을 위해서는 빗물펌프장 성능 평가 기법과 유입 유출부 및 흡수조 개선 기술, 유출부 주변 부속시설 안정성 향상 기술 개발을 주요 연구내용으로 설정하였다. 마지막으로, 배수시스템의 개선 기법 개발을 위해서는 도시하천 설계빈도 상향에 따른 우수관거 구조개선 기술을 개발하고, 우수관거 시스템 저류능력 평가 기술 및 우수관거 연계 저류시스템 설계 기술개발을 수행하였다. 본 연구에서는 내수배제시설에 대한 정량적 설계기법을 개발하여 도시침수에 대한 구조적인 대응방안을 수립하였다. 시설물 계획단계에서 고려하여야하는 문제점을 연구내용에 반영하여 내수배제시설 설계실무에 실용적으로 적용할 수 있는 성과를 도출하였다. 향후 내수배제시설 설계실무자의 의견을 반영하여 연구성과를 고도화한다면 실무에 적용가능한 성과가 도출될 것으로 기대된다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.797-808
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• 2012

In smart work environment, a company provides employees a flexible work environment for tele-working using mobile phone or portable devices. On the other hand, such environment are exposed to the risks which the attacker can intrude into computer systems or leak personal information of smart-workers' and gain a company's sensitive information. To reduce these risks, the security administrator needs to analyze the usage patterns of employees and detect abnormal behaviors by monitoring VPN(Virtual Private Network) access log. This paper proposes a decision support system that can notify the status by using visualization and similarity measure through clustering analysis. On average, 88.7% of abnormal event can be detected by this proposed method. With this proposed system, the security administrator can detect abnormal behaviors of the employees and prevent account theft.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.213-224
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• 2012

The integrated core network architecture and various mobile subscriber behavior can result in a significant increase of signaling load inside the evolved packet core network proposed by 3GPP in Release 8. Consequently, an authentication signaling analysis can provide insights into reducing the authentication signaling loads and latency, satisfying the quality-of-experience. In this paper, we evaluate the signaling loads in the EPS architecture via analytical modeling based on the renewal process theory. The renewal process theory works well, irrespective of a specific random process (i.e. Poisson). This paper considers various subscribers patterns in terms of call arrival rate, mobility, subscriber's preference and operational policy. Numerical results are illustrated to show the interactions between the parameters and the performance metrics. The sensitivity of vertical handover performance and the effects of heavy-tail process are also discussed.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.195-201
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• 2020

This study studied scoliosis, one of the most common modern diseases caused by lifestyle patterns of office workers sitting in front of computers all day and modern people who use smart phones frequently. Scoliosis is a typical complication that takes more than 80% of the nation's total population at least once. X-ray are used to test for these complications. X-ray, a non-destructive testing method that allows scoliosis to be easily performed and filmed in various areas such as the chest, abdomen and bone without contrast agents or other instruments. We uses NI DAQ to miniaturize digital X-ray imaging devices and image intensifier in self-shielding housing with Vision Assistant for drawing lines to the top and the bottom of the spine to acquire angles, i.e. curvature in real-time. In this way, the research was conducted to see scoliosis patients and their condition easily and to help rapid treatment for solving the problem of posture correction in modern people.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1874-1881
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• 2021

Black ice, which occurs mainly on the road, vehicle traffic bridges and tunnel entrances due to the sub-zero temperature due to the slip of the road due to heavy snow, is not recognized because the image of asphalt is transmitted in the driver's view, so the vehicle loses braking power because it causes serious loss of life and property. In this paper, we propose a method to identify the black ice by using infrared camera and to identify the road condition by using deep learning to compensate for the disadvantages of existing black ice detection methods (artificial satellite imaging, checking the pattern of slip by ultrasonic reception, measuring the temperature of the road surface, and checking the difference in friction force of the tire during vehicle driving) and to reduce the size of the sensor to detect black ice.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.6
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• pp.92-99
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• 2021

The rotavator is attached to the three-point hitch at the rear of a tractor and uses the power take-off strength of the tractor to perform soil harrowing. During operation, the power transmitted to the gearbox of the rotavator varies with the soil characteristics and depth. These properties influence the reliability of the gearbox. In this study, actual load measurements and analyses were performed using a rotavator. In addition, the safety factor and fatigue life of the gearbox components were determined using the analysis results. Through analysis and tests, the contact pattern of the gear tooth surface was identified. The input power values of the gearbox were minimum and maximum at 54.5% and 84.5% of the tractor power, respectively. Based on the actual load analysis results, the strength and fatigue life of the gearbox components were satisfied. In addition, through the analysis and testing of the gear contact pattern, it was confirmed that a similar contact occurred. Through the analysis, the magnitude of the load acting on the tooth surface of the gear was confirmed.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.1
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• pp.5-21
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• 2023

The purpose of this study is to analyze how library visitors use spaces in the library and to make suggestions for improving library use environments. Library use patterns were analyzed by tracking the users' smartphone WiFi. A library located in Seoul, Korea was selected and detectors were installed in the library. The suggestions from the results analyzing data collected between September, 2016 and December, 2016 were as followed. 27.17% of library visitors used a space in the library. Among them, 28.69% used the lobby to return their checked-out materials. Therefore, the library is recommended to install a device in the area in which users are easy to return their items. Additionally, since the spatial relationship between cultural program room and book shelves was low, those programs might be improved by providing library materials related with them.

• Journal of Navigation and Port Research
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• v.47 no.4
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• pp.212-219
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• 2023

Vessel Traffic Service (VTS) area presents a complex traffic pattern due to ships entering or leaving the port to utilize port facilities, as well as ships passing through the coastal area. To ensure safe and efficient management of maritime traffic, VTS operators continuously monitor and control vessels in real time. However, during periods of high traffic congestion, the workload of VTS operators increases, which can result in delayed or inadequate VTS services. Therefore, it would be beneficial to predict traffic congestion and congested areas to enable more efficient traffic control. Currently, such prediction relies on the experience of VTS operators. In this paper, we defined vessel traffic congestion from the perspective of a VTS operator. We proposed a method to generate traffic networks using historical navigational data and predict traffic congestion and congested areas. Experiments were performed to compare prediction results with real maritime data (Daesan port VTS) and examine whether the proposed method could support VTS operators.