• Journal of Digital Convergence
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• v.10 no.10
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• pp.313-318
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• 2012

In this study, we propose a low-noise transceiver for 10GHz motion sensor. The transceiver presented here has a circuit(Hittite HMC908LC5) that is composed of a two way-$0^{\circ}$ power splitter(the 1:2 block) and a $90^{\circ}$ Hybrid. The noise reduction circuit utilizes an LNA followed by an image reject mixer which is driven by an LO buffer amplifier. A modeling and analysis have been pursued using CST MWS. A prototype sensor was manufactured to measure the performance and experimental results show that the proposed sensor is good enough to use for a accurate motion sensor.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.9
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• pp.103-109
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• 2006

This research is contents about output characteristic of optic current sensor that use faraday effect. optic current sensor used in an experiment is consisted of three parts.(1) Source of light used laser diode of 1310[nm].(2) Sensor section manufactured circularly according to gas insulated switchgear. And $9/125[{\mu}m]$ standard single mode optical fiber for communication was installed winding 20 [turn] on sensor section core surroundings of diameter 31 [cm].(3) Electrical signal of PD(Photo detector) is collected using NI company's 16bit DAQ board via terminal block. Collected data analyzed by different three signal processing methods. NI company's $Labview^{TM}$ was used to signal processing software. As a result, In signal processing of optic current sensor, we could know that noise greatly more influences the error generation than fluctuation of light intensity. also, 1 class CT(current transformer) manufacture that have error rate less than 1[%] was available by removing these

• Journal of Applied Reliability
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• v.16 no.3
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• pp.180-191
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• 2016

Purpose: The purpose of this study was to develop the accelerated life test method for Constant Electrical Potential Electrolysis gas sensor (CEPE gas sensor). Methods: The parts and modules of CEPE gas sensor were analyzed by using Reliability Block Diagram (RBD). Failure Mode and Effect Analysis (FMEA) and Quality Function Deployment (QFD) methods were performed for each part to determine the most affecting stress factor in its life cycle. The long term testing was conducted at three different dry heat levels and the acceleration factor was developed by using Arrhenius relationship. Conclusion: The acceleration factor for CEPE gas sensor was developed by using FMEA, QFD, and statistical analysis for its failure data. Also qualification tests were designed to meet the target life.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1005-1018
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• 2017

This paper proposes an App Visualization (AppV) based on IoT Self-diagnosis Micro Control Unit (ISMCU) for accident prevention. It collects a current status of a vehicle through a sensor, visualizes it on a smart phone and prevents vehicles from accident. The AppV consists of 5 components. First, a Sensor Layer (SL) judges noxious gas from a current vehicle and a driver's driving habit by collecting data from various sensors such as an Accelerator Position Sensor, an O2 sensor, an Oil Pressure Sensor, etc. and computing the concentration of the CO collected by a semiconductor gas sensor. Second, a Wireless Sensor Communication Layer (WSCL) supports Zigbee, Wi-Fi, and Bluetooth protocol so that it may transfer the sensor data collected in the SL to ISMCU and the data in the ISMCU to a Mobile. Third, an ISMCU integrates the transferred sensor information and transfers the integrated result to a Mobile. Fourth, a Mobile App Block Programming Tool (MABPT) is an independent App generation tool that changes to visual data just the vehicle information which drivers want from a smart phone. Fifth, an Embedded Module (EM) records the data collected through a Smart Phone real time in a Cloud Server. Therefore, because the AppV checks a vehicle' fault and bad driving habits that are not known from sensors and performs self-diagnosis through a mobile, it can reduce time and cost spending on accidents caused by a vehicle's fault and noxious gas emitted to the outside.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1189-1199
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• 2003

This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using tile pipeline and the data flow technique. The proposed method has been implemented by using an embedded system. The proposed block matching algorithm has been implemented on PLDs(Programmable Logic Device) and clustering algorithm has been implemented by ARM processor. Experimental results show that the proposed system detects the motion of vehicles in real-time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.18-30
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• 2022

Predicting remaining useful life (RUL) becomes significant to implement prognostics and health management of industrial systems. The relevant studies have contributed to creating RUL prediction models and validating their acceptable performance; however, they are confined to drive reasonable preventive maintenance strategies derived from and connected with such predictive models. This paper proposes a data-driven preventive maintenance method that predicts RUL of industrial systems and determines the optimal replacement time intervals to lead to cost minimization in preventive maintenance. The proposed method comprises: (1) generating RUL prediction models through learning historical process data by using machine learning techniques including random forest and extreme gradient boosting, and (2) applying the system failure time derived from the RUL prediction models to the Weibull distribution-based minimum-repair block replacement model for finding the cost-optimal block replacement time. The paper includes a case study to demonstrate the feasibility of the proposed method using an open dataset, wherein sensor data are generated and recorded from turbofan engine systems.

• Fire Science and Engineering
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• v.34 no.3
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• pp.67-75
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• 2020

In this study, the risk of heat generation due to normal and overload currents that vary with the abnormal loosening angle of wire-connecting bolts were identified. The risks were analyzed based on the thermal characteristics to minimize the carbonization accidents of terminal blocks inside distribution panels typically used in industrial sites. We applied a method for measuring the heating temperature and temperature variations in the terminal blocks in real-time by installing a resistance temperature detector sensor board in the terminal block. The experimental results showed that the terminal block model with a low-rated current exhibited a higher heating temperature, thus, confirming the need to select the terminal block capacity based on load currents. Additionally, the higher the rated current of the terminal block with a high-rated current and the higher the degree of loosening, the faster the carbonization point. Such heating temperature monitoring enabled real-time thermal temperature measurement and a step-by-step risk level setting through thermal analysis. The results of the measurement and analysis of carbonization risks can provide a theoretical basis for further research regarding the risk of fire due to carbonization. Furthermore, the deterioration measurement method using the temperature sensor board developed in this study is widely applicable to prevent fires caused by poor electrical contact as well as risk-level management.

• Journal of the Korean Society of Safety
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• v.16 no.1
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• pp.88-93
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• 2001

This study discusses frequency analysis based on autoregressive (AR) time series model, and process characterization in orthogonal cutting of a fiber-matrix composite materials. A sparsely distributed idealized composite material, namely a glass reinforced polyester (GFRP) was used as workpiece. Analysis method employs a force sensor and the signals from the sensor are processed using AR time series model. The resulting pattern vectors of AR coefficients are then passed to the feature extraction block. Inside the feature extraction block, only those features that are most sensitive to different types of cutting mechanisms are selected. The experimental correlations between the different chip formation mechanisms and AR model coefficients are established.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.585-590
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• 2017

In this paper, a low power of safety oriented sidewalk block was implemented using dimming technology using LED and illuminance sensor to prevent glare by high - intensity light source and prevent night traffic accident. The dimming system of this paper used a light bulb color with less fatigue to prevent glare and consumed 6.10Wh power. Also, it is confirmed that the power saving is about 56.9% when compared with the existing system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3071-3095
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• 2013

Configuring optimization of wireless sensor networks, which can improve the network performance such as utilization efficiency and network lifetime with minimal energy, has received considerable attention in recent years. In this paper, a cross layer optimal approach is proposed for multi-source linear network and grid network under Rayleigh block-fading channels, which not only achieves an optimal utility but also guarantees the end-to-end reliability. Specifically, in this paper, we first strictly present the optimization method for optimal nodal number $N^*$, nodal placement $d^*$ and nodal transmission structure $p^*$ under constraints of minimum total energy consumption and minimum unit data transmitting energy consumption. Then, based on the facts that nodal energy consumption is higher for those nodes near the sink and those nodes far from the sink may have remaining energy, a cross layer optimal design is proposed to achieve balanced network energy consumption. The design adopts lower reliability requirement and shorter transmission distance for nodes near the sink, and adopts higher reliability requirement and farther transmission distance for nodes far from the sink, the solvability conditions is given as well. In the end, both the theoretical analysis and experimental results for performance evaluation show that the optimal design indeed can improve the network lifetime by 20-50%, network utility by 20% and guarantee desire level of reliability.