• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.5
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• pp.198-205
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• 2005

Many precedent investigations hate been made for the reliable assessment of the insulation state of large power apparatus for which partial discharge detection is one of tile plausible way. In this work, experimental investigations have been carried out to make the comparison on the PD(partial discharge) pattern analysis related to the five different types of artificial defects such as SFMP (Single Free Moving Particle), MFMP (Multi Free Moving Particle), Void, CFP (Conductor-Fixed Protrusion), EP (Enclosure Protrusion). For each PD pattern, PD detection has been done by tee different types of PD sensors such as HFCT(High Frequency Current Transformer), AE(Acoustic Emission) and UHF(Ultra High Frequency). And, in addition, frequency spectrum by the UHF sensor has been also made for each defect respectively. As a result, it is observed that the possibility of obtaining PD pattern based on PRPD(Phase Resolved Partial Discharge) in connection with the defects tinder investigation is dependant on the type of the sensor while the spectrum analysis is always successful to be achieved for every defect. Therefore, it could be suggested that the nature of PD source can be identified more distinctively when the conventional PRPDA is combined with spectrum analysis.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.794-799
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• 2009

The temperature control of in-place concrete is the most important factor for an early age of curing concrete. Heat stress of mass concrete caused by the heat of hydration can induce the crack of concrete, and a frost damage from cold weather casting concrete results defect on compressive strength and degradation of durability. Therefore, success and failure of concrete work is dependant on the measurement and control of concrete temperature. In addition, the compressive strength assessment of in-place concrete obtained from the maturity calculated from the history of temperature make a reduction of construction cycle time, possible. For that purpose, wireless temperature measuring system was developed to control temperature and assess strength of concrete. And, it was possible to monitor the temperature of concrete over 1km apart from site office and to take a proper measure; mesh-type network was developed for wireless sensor. Furthermore, curing control system that contains the program capable to calculate the maturity of concrete from the history of temperature and to assess the compressive strength of concrete was established. In this study, organization and practical method of developed curing control system are presented; base on in-place application case.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.35-42
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• 2011

Link quality assessment is a crucial part of sensor network formation to stably operate large-scale wireless sensor networks (WSNs). A stability of path consisting of several nodes strongly depends on all link quality between pair of consecutive nodes. Thus it is very important to assess the link quality on the stage of building a routing path. In this paper, we present a link quality assessment method, Hybrid Link Quality Metric (HQLM), which uses both of LQI and RSSI from RF chip of sensor nodes to minimize set-up time and energy consumption for network formation. The HQLM not only reduces the time and energy consumption, but also provides complementary cooperation of LQI and RSSI. In order to evaluate the validity and efficiency of the proposed method, we measure PDR (Packet Delivery Rate) by exchanging multiple messages and then, compare PDR to the result of HQLM for evaluation. From the research being carried out, we can conclude that the HQLM performs better than either LQI- or RSSI-based metric in terms of recall, precision, and matching on link quality.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.61-69
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• 2023

In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.465-470
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• 2013

Dempster-Shafer Evidence Theory is available for multi-sensor data fusion. Basic Probability Assignment is essential for multi-sensor data fusion using Dempster-Shafer Theory. In this paper, we proposed a novel method of BPA calculation with signal assessment. We took notice of the signal that reported from the sensor mote at the time slot. We assessed the variation rate of the reported signal from the terminal. The trend of variation implies significant component of the context. We calculated the variation rate of signal for reveal the relation of the variation and the context. We could reach context inference with BPA that calculated with the variation rate of signal.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.1
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• pp.168-179
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• 2021

This study presents and develops a textile type touch sensor structural design that is easy to implement. First, the design of the touch sensor circuit finds the size of the switch with the easiest finger contact and selects a structure with a long circuit with the lowest resistance value. An experiment is performed on a change in an electrostatic capacitance value that accompanies the distance on the electrode and the magnitude of the electrode area of the structure; however, the structure having the distance on the electrode and the large electrode area shows the best resistance change. The laundry assessment was conducted three times at a time and ten times at a time with an average standard deviation less than one ohm, with little change in resistance. Consequently, there were no problems with durability and performance for laundry. Finally, in the bending evaluation, the difference in resistance can be seen between 1-2 ohms and was developed as a smart wearable in the future; in addition, there was no problem as a difference in resistance can be seen between 1 and 2 ohms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.654-670
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• 2020

Workers at construction sites are easily exposed to many dangers and accidents involving falls, tripping, and missteps on stairs. However, researches on construction site monitoring system to prevent work-related injuries are still insufficient. The purpose of this study was to develop a wearable textile pressure insole sensor and examine its effectiveness in managing the real-time safety of construction workers. The sensor was designed based on the principles of parallel capacitance measurement using conductive textile and the monitoring system was developed by C# language. Three separate experiments were carried out for performance evaluation of the proposed sensor: (1) varying the distance between two capacitance plates to examine changes in capacitance charges, (2) repeatedly applying 1 N of pressure for 5,000 times to evaluate consistency, and (3) gradually increasing force by 1 N (from 1 N to 46 N) to test the linearity of the sensor value. Five subjects participated in our pilot test, which examined whether ascending and descending the stairs can be distinguished by our sensor and by weka assessment tool using k-NN algorithm. The 10-fold cross-validation method was used for analysis and the results of accuracy in identifying stair ascending and descending were 87.2% and 90.9%, respectively. By applying our sensor, the type of activity, weight-shifting patterns for balance control, and plantar pressure distribution for postural changes of the construction workers can be detected. The results of this study can be the basis for future sensor-based monitoring device development studies and fall prediction researches for construction workers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.135-152
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• 2018

The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.397-408
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• 2013

According to increase of concerning in health and entry of aging society, sensor-based smart clothing has developed various type and applications. Sensor-based smart clothing should be designed with considering of the interaction between a human body-device-clothing, such as accuracy of signal, wearability, suitability and the configuration of the sensor and so on. In this respect, these characteristics distinguish sensor-based smart clothing process from clothing process and Sensor-based smart clothing process is expected to be needing requirements Specification for development purpose and interoperability assessment based on requirements engineering. In this study, to assess efficiency of process based on requirement engineering, the sensor-based smart clothing process was deducted in two types by analysis of empirical performance. Presented two process were empirically evaluated through qualitative and quantitative evaluation. As a result, design process II based on requiments engineering were confirmed more effective process than processI.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.44-49
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• 2013

This paper presents a lateral collision risk index between an ego vehicle and a rear-side vehicle. The lateral collision risk is designed to represent a lateral collision risk and provide the appropriate threshold value of activation of the lateral collision management system such as the Blind Spot Detection(BSD). The lateral collision risk index is designed using the Time to Line Crossing(TLC) and the longitudinal collision index at the predicted TLC. TLC and the longitudinal collision index are calculated with the signals from the exterior sensor such as the radar equipped on the rear-side of a vehicle and a vision sensor which detects the distance and time to the lane departure. For the robust situation assessment, the perception of driving environment determining whether the road is straighten or curved should be determined. The relative motion estimation method has been proposed with the road information via the integrated estimator using the environment sensors and vehicle sensor. A lateral collision risk index was composed with the estimated relative motion considering the relative yaw angle. The performance of the proposed lateral collision risk index is investigated via computer simulations conducted using the vehicle dynamics software CARSIM and Matlab/Simulink.