• Science of Emotion and Sensibility
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• v.5 no.2
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• pp.29-34
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• 2002

Our previous studies investigated that narrow field of view (FOV : 50˚) and slow navigation speed decreased the frequency of occurrence and severity of cybersickness during immersion in the virtual reality (VR). It would cause a significant reduction of cybersickness if it were provided cybersickness alleviating virtual environment (CAVE) using biofeedback method whenever subject underwent physiological agitation. For verifying the hypothesis, we constructed a real-time cybersickness detection and feedback system with artificial neural network whose inputs are electrophysiological parameters of blood pulse volume, skin conductance, eye blink, skin temperature, heart period, and EEG. The system temporary provided narrow FOV and decreased speed of navigation as feedback outputs whenever physiological measures signal the occurrence of cybersickness. We examined the frequency and severity of cybersickness from simulator sickness questionnaires and self-report in 36 subjects. All subjects experienced VR two times in CAVE and non-CAVE condition at one-month intervals. The frequency and severity of cybersickness were significantly reduced in CAVE than non-CAVE condition. Virtual environment of narrow FOV and slow navigation provided by electrophysiological features based artificial neural network caused a significant reduction of cybersickness symptoms. These results showed that efficiency of a cybersickness detection system we developed was relatively high and subjects expressed more comfortable in the virtual navigation environment.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.7
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• pp.1-9
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• 2012

In this paper, resistance temperature detector (RTD) integrated into the LED package is proposed in order to solve the temperature dependence of LED's optical properties. To measure the package temperature in real time, the RTD type temperature sensor having excellent accuracy and linearity between temperature change and resistance change was adopted. A stable metallic film is required for long term reliability and stability of the RTD type temperature sensor. Therefore, deposition and annealing condition for the film were determined. Based on the determined condition, the RTD type temperature sensor with the sensitivity of about $1.560{\Omega}/^{\circ}C$ was fabricated inside the LED package. In order to configurate the LED package system keeping the constant brightness regardless of the temperature, additional conversion circuit and control circuit boards were fabricated and added to the fabricated LED package. The proposed system was designed to compensate the light intensity caused by temperature change using the variable duty rate of driving current. As a result, the duty rate of PWM signal which is the output signal of the configurated system was changed with the temperature change, and the duty rate was similarly varied with the target duty rate. Consequently, it was focused the fabricated RTD can be used for compensating the optical properties of LED and the LED package which exhibits constant brightness regardless of the temperature change.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.709-716
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• 2004

This paper describes an intelligent real-time monitoring system of a semiconductor processing equipment, which determines normal or not for a wafer in processing, using multiple time-series pattern recognition. The proposed system consists of three phases, initialization, learning and real-time prediction. The initialization phase sets the weights and tile effective steps for all parameters of a monitoring equipment. The learning phase clusters time series patterns, which are producted and fathered for processing wafers by the equipment, using LBG algorithm. Each pattern has an ACI which is measured by a tester at the end of a process The real-time prediction phase corresponds a time series entered by real-time with the clustered patterns using Dynamic Time Warping, and finds the best matched pattern. Then it calculates a predicted ACI from a combination of the ACI, the difference and the weights. Finally it determines Spec in or out for the wafer. The proposed system is tested on the data acquired from etching device. The results show that the error between the estimated ACI and the actual measurement ACI is remarkably reduced according to the number of learning increases.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.63-71
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• 2020

In this paper, we propose a fire detection technology using YOLOv3 and EfficientDet, the most reliable artificial intelligence detection algorithm recently, an alert service that simultaneously transmits four kinds of notifications: text, web, app and e-mail, and an AWS system that links fire detection and notification service. There are two types of our highly accurate fire detection algorithms; the fire detection model based on YOLOv3, which operates locally, used more than 2000 fire data and learned through data augmentation, and the EfficientDet, which operates in the cloud, has conducted transfer learning on the pretrained model. Four types of notification services were established using AWS service and FCM service; in the case of the web, app, and mail, notifications were received immediately after notification transmission, and in the case of the text messaging system through the base station, the delay time was fast enough within one second. We proved the accuracy of our fire detection technology through fire detection experiments using the fire video, and we also measured the time of fire detection and notification service to check detecting time and notification time. Our AI fire detection and notification service system in this paper is expected to be more accurate and faster than past fire detection systems, which will greatly help secure golden time in the event of fire accidents.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.283-290
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• 2022

In this study, an IoT inspection system that can be linked with a server was developed using a gas timer and ESP-01 Wi-Fi module installed on a gas valve in the home. The server environment of the gas leak IoT inspection system was installed with APM (Apache, PHP, MySQL) to collect gas pressure data by generation so that leakage checks could be performed. In order to control the gas leak IoT inspection system, the app inventory was used to manage the gas leak check value in real time. In addition, user convenience has been enhanced so that membership management, WiFi settings, and leakage check values can be checked through mobile apps. In order to manage subscribers by region, the user list was checked by logging in in in the administrator mode so that the information on whether or not the leak test was conducted and the results could be provided. In addition, when the user presses the gas leak check button, the pressure is automatically checked, and the measured value is stored in the server, and when a gas leak occurs, the leakage check is performed after alarm and repair so that it can be used if normal. In addition, in order to prevent overlapping membership, membership management can be performed based on MAC addresses.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.254-261
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• 2024

Accurate guidance during landing and take-off is important, and instrument landing system (ILS) has been used for stability and verification. Regular inspections are conducted for stable operation, and there is research to perform inspection using drones in addition to ground vehicles and measurement aircraft. Using SDR and single board computer, which can receive wide frequency range, we designed a small system that receives and processes localizer signals through GNU Radio. To check signal processing characteristics through GNU Radio, we simulated with MATLAB Simulink and confirmed the theoretical values. Difference in depth of modulation (DDM) and approach angle can be calculated when the aircraft enters the runway. And GNU Radio implemented real-time signal processing wirelessly using transmission control protocol (TCP). This gives the results within the error of 0.5% when the aircraft entered the runway center line and 0.27% for the angle of 1° degree. Compared to the inspecting and maintaining ILS signals using aircraft or ground vehicles, it is possible to implement a receiving system using small SDR that can be mounted for drone.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.209-216
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• 2014

Various characteristics of social network contents such as real-time, people relationship and big data can help to improve personalized recommender systems. Among them, 'people relationship' is a key factor of recommendation, so many personalized recommender systems utilizing it have been proposed. However, existing researches can not reflect personal tendency and are unable to provide precise recommendations in various domains, because they do not consider intimacy among people. In this paper, to solve these problems, we propose PReAmacy, a Personalized Recommendation Algorithm, considering intimacy among users and various characteristics of social network contents. Our experimental results indicate that not only the precision of PReAmacy is higher than that of existing algorithms, but intimacy is of great importance in PReAmacy.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.164-164
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• 2021

우리나라는 최근 도시화 및 산업화 등과 같은 유역개발이 가속화되면서 유역환경의 급격한 변화를 가져왔다. 도시화는 지표면의 불투수 면적을 증가시키고, 농업지역의 확대는 비료 및 농약의 사용을 증가시키고, 강우시 토양침식에 따른 흙탕물과 비점오염원의 수계 유출로 인해 수질악화 등의 문제를 야기시킨다. 이와 같은 유역환경의 변화는 수질에 직접적인 영향을 끼치므로, 미래 토지이용의 변화에 따른 하천유역의 유출특성과 영향 인자를 규명해야 효율적인 하천유역관리를 할 수 있다. 하지만 우리나라는 기후적 특성상 계절에 따른 수질 및 기후변수의 편차가 크기 때문에 하천유역관리에 있어 어려움이 많다. 특히 남한강 유역은 산림 및 고랭지밭 비중이 높은 지역이며, 여름철에는 강우로인한 토양침식이 심각하여 수질 및 수생태계 건강성을 악화시킨다. 남한강 상류 유역에는 송천과 도암호, 골지천과 같은 비점오염관리지역이 위치하고 있으며 현재까지도 하천유역관리가 어려운 지역에 해당한다. 본 연구는 남한강 유역에 위치한 17개 수질측정망을 대상으로 GIS시스템을 이용해 17개의 소권역으로 나누어 분석하였다. 토지이용자료는 환경공간정보 서비스의 2010년대 말 자료를 이용하였으며, 수질 자료는 유역환경 변화에 영향을 미칠 것이라 판단되는 수질 변수를 선별하여 10년동안의 장기간 수질 데이터를 이용하여 분석하였다. 16개의 수질변수는 정규성을 검증한 후 pairwisse t-test를 이용한 시기별 수질의 차이를 비교하였으며, 수질변수들과 토지이용매개변수 간에 상관관계를 찾아 유의관계가 있는지 확인함으로써 서로 다른 변수간에 상관성을 파악하고자 하였다. 유역의 특성별 상관도를 평가하고 해석하기 위하여 주성분 분석(Principal component analysis, PCA)을 실시하였다. 통계적 방법을 통해 시기에 따른 수질과 토지이용간의 관계를 밝힘으로써 미래하천유역관리에 기초자료로 활용될 것이다.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1669-1679
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• 2020

This study examines the washing effect of precipitation on particulate matter (PM) and the rainwater quality (pH, electrical conductivity (EC), water-soluble ions concentration). Of six rain events in total, rainwater samples were continuously collected every 50 mL from the beginning of the precipitation using rainwater collecting devices at Pukyong National University, Busan, South Korea, from March 2020 to July 2020. The collected rainwater samples were analyzed for pH, EC, and water-soluble ions (cations: Na+, Mg2+, K+, Ca2+, NH4+, and anions: Cl-, NO3-, SO42-). The concentrations of particulate matter were continuously measured during precipitation events with a custom-built PM sensor node. For initial rainwater samples, the average pH and EC were approximately 4.3 and 81.9 μS/cm, and the major ionic components consisted of NO3- (5.4 mg/L), Ca2+ (4.2 mg/L), Cl- (4.1 mg/L). In all rainfall events, rainwater pH gradually increased with rainfall duration, whereas EC gradually decreased due to the washing effect. When the rainfall intensities were relatively weak (<5 mm/h), PM10 reduction efficiencies were less than 40%. When the rainfall intensities were enhanced to more than 7.5 mm/h, the reduction efficiencies reached more than 60%. For heavy rainfall events, the acidity and EC, as well as ions concentrations of initial rainwater samples, were higher than those in later samples. This appears to be related to the washing effect of precipitation on PM10 in the atmosphere.

• Journal of the Korean Society of Radiology
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• v.11 no.3
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• pp.109-115
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• 2017

The purpose of this study was to evaluate the clinical efficacy of 128 MDCT (multi-detector computed tomography) for reducing the CareDose 4D dose and comparing the image quality with the fixed tube current technique. For this purpose, we conducted the phantom and clinical studies to evaluate the exposure dose and image of the subject before and after applying the CareDose 4D system in abdominal examination using 128 MDCT. In the phantom study, ROI (Region of interest) was located at the center, 3, 6, 9, 12 o'clock, into two groups: group A without CareDose 4D and Group B applied were measured. In the clinical study, ROI was located at the liver 8 segments, divided into two groups too. The measured items were CT number, noise, and dose length product (DLP) dose. The result of CTDIvol (CT Dose Index volume) measurements in phantom and clinical studies were lower than those before CareDose 4D application, and dose and effective dose were also measured lower (p<.05). There was no difference in CT number before and after application (p>.05). In conclusion, using CareDose 4D, we can obtain optimal image information without deteriorating image quality while reducing patient dose.