• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.87-92
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• 2019

This paper describes the pattern analysis for data of the factory energy consumption by using machine learning method. While usual statistical methods or approaches require specific equations to represent the physical characteristics of the plant, machine learning based approach uses historical data and calculate the result effectively. Although rule-based approach calculates energy usage with the physical equations, it is hard to identify the exact equations that represent the factory's characteristics and hidden variables affecting the results. Whereas the machine learning approach is relatively useful to find the relations quickly between the data. The factory has several components directly affecting to the electricity consumption which are machines, light, computers and indoor systems like HVAC (heating, ventilation and air conditioning). The energy loads from those components are generated in real-time and these data can be shown in time-series. The various sensors were installed in the factory to construct the database by collecting the energy usage data from the components. After preliminary statistical analysis for data mining, time-series clustering techniques are applied to extract the energy load pattern. This research can attributes to develop Factory Energy Management System (FEMS).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.558-564
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• 2021

With the recent introduction of 5G, electromagnetic radiation sources are spreading throughout life, so it is necessary to establish a citizen-centered electromagnetic safety management system. In particular, the beamforming method of the 5G antenna increases the power density measurement of electromagnetic waves by more than 10 times when the wireless base station is installed, so it is unreasonable to determine the safety by physical measurement. Therefore, it is necessary to determine the presence or absence of electromagnetic wave safety in daily life through a predictive method by calculation through systematic model analysis. In this paper, in order to check the possibility of a 5G wireless base station using an electromagnetic wave numerical analysis tool as a way to solve this problem, we compared the measured values of the actual base stations and the predicted values through the prediction model to compare the reliability. A method of constructing a real-time base station electromagnetic wave strength prediction evaluation system combined with software was also proposed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.85-92
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• 2021

Ambient Air Vaporizer (AAV) is an essential facility in the process of generating natural gas that uses air in the atmosphere as a medium for heat exchange to vaporize liquid natural gas into gas-state gas. AAV is more economical and eco-friendly in that it uses less energy compared to the previously used Submerged vaporizer (SMV) and Open-rack vaporizer (ORV). However, AAV is not often applied to actual processes because it is heavily affected by external environments such as atmospheric temperature and humidity. With insufficient operational experience and facility operations that rely on the intuition of the operator, the actual operation of AAV is very inefficient. To address these challenges, this paper proposes an artificial intelligence-based model that can intelligent AAV operations based on operational big data. The proposed artificial intelligence model is used deep neural networks, and the superiority of the artificial intelligence model is verified through multiple regression analysis and comparison. In this paper, the proposed model simulates based on data collected from real-world processes and compared to existing data, showing a 48.8% decrease in power usage compared to previous data. The techniques proposed in this paper can be used to improve the energy efficiency of the current natural gas generation process, and can be applied to other processes in the future.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.199-205
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• 2021

The distributing board in directly installed on the ground or the bottom surface of the building, and when vibrations such as earthquakes or external shocks occur, the possibility of damage or malfunction of electric components such as internal power devices, wiring, and protection relays increases. Recently, the need for a seismic type distributing board is increasing, and research and development of a distributing board having a vibration damping function and product launch are being conducted. In this paper, an IoT-based data collection device system capable of measuring vibration and environmental data of distributing board was designed and implemented. When vibration occurred on the distributing board, data was stored and visualized in the MySQL DB through Node-RED for monitoring and data storage using the MQTT protocol for reliable messaging transmission. The test was conducted by attaching the IoT device of the distributing board, and data was collected in real-time and monitored through Node-RED.

• Journal of Drive and Control
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• v.19 no.4
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• pp.19-28
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• 2022

This paper introduces an automatic steering system for straight traveling capable of being mounted on drivable agricultural machinery which user can handle it such as a tractor, a transplant, etc. The modular automatic steering device proposed in the paper is composed of RTK GNSS, IMU, HMI, hydraulic valve, and wheel sensor. The path generation method of the automatic steering system is obtained from two location information(latitude and longitude on each point) measured by GNSS in advance. From HMI, a straight path(AB line) can be created by connecting latitude and longitude on each point and the device makes the machine able to follow the path. During traveling along the reference path, it acquires the real time position data every sample time(0.1s), compares the reference with them and calculates the lateral deviation. The values of deviation are used to control the steering angle of the machine using hydraulic valve mounted on the axle of front wheel. In this paper, Pure Pursuit algorithm is applied used in autonomous vehicles frequently. For the analysis of traveling characteristics, field tests were executed about these conditions: velocity of 2, 3, 4km/h which is applied to general agricultural work and ground surface of solid(asphalt) and weak condition(soil) such as farmland. In the case of weak ground state, two experiments were executed about no-load(without work) and load(with work such as plowing). The maximum average deviations were presented 2.44cm, 7.32cm, and 11.34cm during traveling on three ground conditions : asphalt, soil without load and with load(plowing).

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.819-834
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• 2022

Artificial Intelligence (AI) techniques have been effectively used for image classification, object detection, and image segmentation. Along with the recent advancement of computing power, deep learning models can build deeper and thicker networks and achieve better performance by creating more appropriate feature maps based on effective activation functions and optimizer algorithms. This review paper examined technical and academic trends of Convolutional Neural Network (CNN) and Transformer models that are emerging techniques in remote sensing and suggested their utilization strategies and development directions. A timely supply of satellite images and real-time processing for deep learning to cope with disaster monitoring will be required for future work. In addition, a big data platform dedicated to satellite images should be developed and integrated with drone and Closed-circuit Television (CCTV) images.

• Journal of People, Plants, and Environment
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• v.24 no.3
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• pp.301-309
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• 2021

Background and objective: The purpose of this study is to analyze the case of healing experience for lifestyle and environmental diseases through life and activities in the forest from the perspecitive of critical realism, and how the causal power and mechanism of the healing experience relate to forest healing factors and programs. Methods: 93 video data of people who started living in the forest for disease treatment were analyzed using a qualitative content analysis method from the perspective of critical realism. Categories for analysis include general categories (age, duration, occupation, disease name), forest therapy categories (climate therapy, plant therapy, water therapy, diet therapy, kinesiotherapy, psychotherapy), and other categories (ecology, learning and management, life tools), etc., and the unit of analysis is the context unit. Results: 1) The diseases that motivated life in the forest were digestive system diseases, lung diseases, cardiovascular diseases, endocrine system diseases, and various lifestyle-related diseases and environmental diseases in similar proportions. This indicates that forest life does not have specificity to respond to specific diseases, but provides treatment and recovery for all lifestyle and environmental diseases. 2) Among the forest therapies, climate therapy and plant therapy are related to the climatic and residential environment in the forest where 'natural persons' live. And others such as water therapy, diet therapy, kinesiotherapy, psychotherapy indicate the change from the lifestyle that caused the disease to the lifestyle for treatment and recovery. Conclusion: Life and activities in the forest provide an environment for treatment and recovery in which the healing principles such as aromatherapy, nutritional and dietary therapy, kinesiotherapy, and emotional psychotherapy are integrated in the 'real world'.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.12a
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• pp.56-56
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• 2020

감초는 다년생 콩과(Leguminocae) 식물로 국내에서 시중가격이 높은 만주감초가 일부 재배되고 있다. 우리나라에서 감초 재배법이 불완전한 상황에서 한반도의 기후변화에 의한 온도 상승은 약용작물의 생산 및 품질에 많은 영향을 미칠 것으로 예상되므로 본 연구에서는 재배환경 중 온도 조건만 조절할 수 있는 온도구배터널(temperature gradient tunnel system)을 이용하여 4개의 T1(외기온도+0.5~1.3℃), T2(+1.3~2.2℃), T3(+2.2~3.2℃), T4(+3.2~4.0℃) 처리로 온도구배 하여 4년생 만주감초(Glycyrrhiza uralensis F.)를 재배하였다. 지하부가 오래된 모주와 신초1의 경우 저온(T1)과 중간구간(T2, T3)에서 초장과 총화수가 우세하였고, 번식이 가장 늦은 신초2의 경우 중간구간(T2, T3)에서의 생육 및 개화반응이 뚜렷했다. 각 온도처리구마다 3개의 감초 개체를 선발하여 모주의 정단으로부터 5개의 성엽을 채취하였다. Reverse transcription quantitative PCR (RT-qPCR)은 AccuPower® GreenStar^TM RT-qPCR Master Mix (Bioneer, Korea)를 이용하여 진행되었다. Primer 디자인은 NCBI Primer-blast 프로그램을 사용해 제작하였고 ABI StepOne real time system (Applied Biosystem)의 melting curve analysis에서 one-peak test를 통해 gene specific primer임을 확인하였다. 각 온도처리구의 감초 잎에서 RNA를 추출하였고, RT-qPCR을 통해 감초의 유전자 발현양상을 비교, 분석하였다. Phytochrome interacting factor 4 (PIF4)는 식물 호르몬을 유발하는 전사조절을 조정함으로써 고온 신호전달에 핵심적인 역할을 수행한다. 활성화된 Phytochrome B(PhyB)는 PIF4의 활성을 억제한다고 알려졌다. Eukaryotic initiation factors(eIFs)는 mRNA 번역 개시인자로 유전자 발현과 특정 단백질 생산을 조절하는 역할을 한다. 본 결과는 온도조건에서 반응하는 생리적 변화를 전사체 수준에서 조사 분석하여 생리해석의 기초자료로 활용, 국내 감초 재배를 위한 환경조건 구명 및 적지 선정 기초자료로서 활용을 기대한다.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.483-490
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• 2009

In this paper, we develop a speech interface that has acoustic echo cancelling and barge-in functionalities in the car environment. In the echo canceller, DT (Double-Talk) detection algorithm using the correlation coefficients between reference and desired signals can make DT detection errors often in the background noise. We reduce the DT detection errors by using the average power of noise and echo estimated from the input signal. In addition, to make it possible for drivers to give speech command to the system by interrupting the speaker output, barge-in functionality is implemented with the combination of DT detection and appropriate gain control of the speaker output. Through the computer simulation with the assumed car environment and experiment in the real laboratory environment, implemented speech interface has shown good performance in removing acoustic echo signals in the noisy environment with proper operation of barge-in functionality.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.123-128
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• 2024

When mid-span spectral inversion (MSSI), which inverts the propagated wave into phase-conjugated wave in the middle of the entire transmission distance, is combined with dispersion-managed link, it is very effective in compensating for the wavelength division multiplexed (WDM) signal distortion due to chromatic dispersion and nonlinear effects. In this MSSI combined dispersion-managed link, the shape of the dispersion map, channel data rate, channel wavelength and wavelength spacing, etc. affect the compensation and, consequently, determine the transmission distance and capacity of the WDM signal. In this paper, the compensation according to the extinction ratio of the return-to-zero (RZ) pulse that constitutes the WDM signal in the MSSI combined distributed control link was numerically analyzed. As a result of the simulation, it was conformed that the extinction ratio to obtain the best compensation should be determined depending on the shape of the dispersion map and the size of the residual dispersion per span, which determines the specific shape of the dispersion map. These results show a significant difference from the results in a general optical transmission system, where as the extinction ratio increases, the power difference between the '1' and '0' signals increases, thereby improving reception performance.