• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.3
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• pp.14-20
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• 2018

An estimation law of air mass flow rate for high speed engine control is presented. The variables of mass estimation equations are modified to measurable variables which can be obtained during flight, and the effectiveness of each variable to the estimation accuracy is evaluated. The equation is modified to a simplified form, and the uncertainty is evaluated. In addition, reference data for the selection of estimation methods is suggested by considering the sensitivity analysis of sensor error.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.21-31
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• 2012

Threat Evaluation(TE) which has air intelligence attained by identifying friend or foe evaluates the target's threat degree, so it provides information to Weapon Assignment(WA) step. Most of TE data are passed by sensor measured values, but existing techniques(fuzzy, bayesian network, and so on) have many weaknesses that erroneous linkages and missing data may fall into confusion in decision making. Therefore we need to efficient Threat Evaluation system that can refine various sensor data's linkages and calculate reliable threat values under unpredictable war situations. In this paper, we suggest new threat evaluation system based on information fusion JDL model, and it is principle that combine fuzzy which is favorable to refine ambiguous relationships with bayesian network useful to inference battled situation having insufficient evidence and to use learning algorithm. Finally, the system's performance by getting threat evaluation on an air defense scenario is presented.

• Proceedings of the KSRS Conference
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• v.2
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• pp.997-1000
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• 2006

We estimate the net heat flux in the tropical and subtropical Atlantic Ocean using satellite data. These fluxes are related to changes in sea surface temperature (SST). This variable influences atmospheric circulations and is indicative of surface and subsurface oceanic circulations. We employ data from the geostationary METEOSAT-7 and 8 satellites and from the Special Sensor Microwave/Imager (SSM/I) for the shortwave and long-wave radiative fluxes, and for estimates of SST. For turbulent flux calculations, we use the bulk aerodynamic method with satellite estimates for wind speed and atmospheric humidity and temperature.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.119-128
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• 2017

G-induced Loss of Consciousness(G-LOC) can be predicted by measuring Electromyogram(EMG) signals. Existing studies have mainly focused on specific body parts and lacked of consideration with quantitative EMG indices. The purpose of this study is to analyze the indices of EMG signals by human body parts for monitoring G-LOC condition. The data of seven EMG features such as Root Mean Square(RMS), Integrated Absolute Value(IAV), and Mean Absolute Value(MAV) for reflecting muscle contraction and Slope Sign Changes(SSC), Waveform Length (WL), Zero Crossing(ZC), and Median Frequency(MF) for representing muscle contraction and fatigue was retrieved from high G-training on a human centrifuge simulator. A total of 19 trainees out of 47 trainees of the Korean Air Force fell into G-LOC condition during the training in attaching EMG sensor to three body parts(neck, abdomen, calf). IAV, MAV, WL, and ZC under condition after G-LOC were decreased by 17 %, 17 %, 18 %, and 4 % comparing to those under condition before G-LOC respectively. Also, RMS, IAV, MAV, and WL in neck part under condition after G-LOC were higher than those under condition before G-LOC; while, those in abdomen and calf part lower. This study suggest that measurement of IAV and WL by attaching EMG sensor to calf part may be optimal for predicting G-LOC.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.293-302
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• 2019

In the past, there was a theory that influenza wasn't transmitted directly from birds but was infected to humans via swains. Recently, molecular level research has progressed, and it was confirmed that the avian influenza virus can directly infected to human lung and intestinal epithelial cells. Three pandemicsin the past 100 years were also infected to humans directly from birds. In view of such scientific background, we are developing a method for screening sick birds by monitoring the physiological characteristics of birds in a contactless manner with sensors. Here, the movement of respiratory muscles and abdominal muscles under autonomic innervation was monitored using a magnet and Hall sensor sewn on the thoracic wall, and other multimedia devices. This paper presents and discusses the results of experiments involving continuous periodic noise discovered during flight experiments with a data logger mounted on a Japanese pheasant from 2012 to 2015. A brief summary is given as the below: 1. Magnet and Hall sensor sewn to the left and right chest walls, bipolar electrocardiograms between the thoracic walls, posterior thoracic air sac pressure, angular velocity sensors sewn on the back and hips, and optical reflection of LEDs (blue and green) from the skin of the hips allow observation of periodic vibrations(fasciculations) in the waves. No such analysis has been reported before. 2. These fasciculations are presumed to be derived from muscle to maintain and control air sac pressure. 3. Since each muscle fiber is spatially Gaussian distributed from the sympathetic nerve, the envelope is assumed to plot a Gaussian curve. 4. Since avian trunk muscles contract periodically at all time, we assume that the sympathetic nerve dominates in their control. 5. The technique of sewing a magnet to the thoracic wall and measuring the strength of the magnetic field with a Hall sensor can be applied to screen for early stage of avian influenza, with a sensor attached to the chicken enclosure.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.121-129
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• 2021

In addition to yellow dust occurring in China, fine dust has become a hot topic in Korea through news and media. Although there is fine dust generated from the outside, the purchase rate of air purifier products is increasing as external fine dust flows into the inside. The air purifier uses a filter internally, and the sensor notifies the user through the LED alarm whether the filter is replaced. However, there is currently no product measuring how much the filter rate is reduced and determining the pressure of the blower to operate. Therefore, in this paper, data are generated directly using Arduino, fine dust sensor, and differential pressure sensor. In addition, a program was developed using Python programming to calculate how old the filter is and to analyze the wind power of the blower according to the filter rate by calculating the measured dust and pressure values.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.48-55
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• 2020

Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.551-558
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• 2021

In this paper, we made the integrated intelligent air ventilation of the actuator module that can be remotely controlled based on IoT and sensors. we implemented a ventilation window system by configuring an algorithm design and a driving circuit to control the operation of the actuator to open and close the ventilation port based on a predetermined number of data that detects indoor gas/CO2/humidity temperature and outdoor fine dust related indoor/outdoor environment. It is difficult to store, manage, and analyze data due to the large number of sensors and conditions for the transmission data of indoor air circulation module. The remote monitoring and remote wireless control screens were constructed to automate the separation and operation conditions by extracting and managing the state. We apply MQTT to enhance big data transmission and construct the system using Rocket MQ to ensure safe transmission of operational big data against system errors.

• Journal of Sensor Science and Technology
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• v.27 no.3
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• pp.143-149
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• 2018

In this paper, we introduce an edge-spike modulation method for visible light communication (VLC). This method is effective in preventing LED flicker and 120 Hz noise interference in base-band VLC. In the VLC transmitter, edge-spikes are generated by passing the digital data through a simple RC-high pass filter (HPF). The LED modulation of the edge-spikes does not change the average power of the LED light; thus it prevents LED flicker. In the VLC receiver, the 120 Hz noise from other lighting lamps is easily eliminated by RC-HPF, while the edge-spike signal is detected normally. In our experiment, the message of an air-quality sensor was successfully transmitted using edge-spike modulation. This structure is useful in constructing, e.g., wireless gas monitoring sensor systems to warn and prevent harmful gas leakage accidents in buildings using LED light.

• Journal of Sensor Science and Technology
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• v.17 no.2
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• pp.151-155
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• 2008

In this paper, it was investigated that the pattern recognition of multiplication environment of lactic acid bacteria in the process of curd yogurt preparation using household fermentation system, which was manufactured by combining incubator with sensor module, data processing circuit and computer. It will be sufficiently applicable to determine the maximum ratio of the amount of air to mixed milk for preparation of high quality yogurt.