• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.28 no.4
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• pp.393-405
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• 2018

Objective: This study examines the types of hazardous factors in the working environment and the time-trend for their exposure levels over 10 years (2007 to 2016). Study Design and Method: The types of hazardous factors and exposure levels were drawn from the 19 measurement reports on the working environment over 10 years at a shock absorber manufacturing facility. Risk assessment of the types of factors and time-trend of exposure levels were evaluated using the factors and exposure levels. Results: A total of 34 hazardous factors were evaluated. The types were noise, 15 organic compounds, seven kinds of acid sand alkalis, eight kinds of heavy metals, and three other compounds. Special management materials used were nickel, hexavalent chrome, and sulfuric acid. Human carcinogens (1A) used were trichloroethylene, nickel, and sulfuric acid. There were six types of substances belonging to the IARC's 2B (body carcinogens) classification or higher, including, methyl isobutyl ketone, ethyl benzene, and trichloroethylene. No detection was found for 627 out of the 2065 total measurements in 19 exposure survey reports, representing 30.4%. Organic solvents, acid and alkali products, and heavy metals showed continuous low exposure concentrations. Noise, welding fumes, and the evaluation of mixed solvents show a gradual decrease in geometric mean and maximum over the time-trend of 10 years. Conclusions: In the case of a shock absorber manufacturing facility, the hazardous factors of noise and the evaluation of mixed solvents still indicate high concentrations exceeding the exposure limits and necessitate reduction studies. These two factors and welding fumes showed a continuous decrease in their ten-year tendency. Organic compounds, acids/alkalis, and heavy metals were managed smoothly in a work environment of continuous low concentrations.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.43.1-43.1
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• 2020

Cassiopeia A (Cas A) is a young supernova remnant (SNR) where we observe the interaction of SNR blast wave with circumstellar medium. From the early optical studies, dense, slowly-moving, N-rich "quasi-stationary flocculi" (QSF) have been known. These are probably dense CNO-processed circumstellar knots that have been engulfed by the SNR blast wave. We have carried out near-infrared, high-resolution (R=45,000) spectroscopic observations of ~40 QSF, and here we present the result on a QSF knot (hereafter 'Knot 24') near the SNR boundary of Cas A. The average [Fe II] 1.644 um spectrum of Knot 24 has a remarkable shape with a narrow (~8 km/s) line superposed on the broad (~200 km/s) line emitted from shocked gas. The spatial morphology and the line parameters indicate that Knot 24 has been partially destroyed by a shock wave and that the narrow line is emitted from the unshocked material heated/ionized by the shock radiation. This is the first detection of the emission from the pristine circumstellar material of the Cas A supernova progenitor. We also detected H Br gamma and other [Fe II] lines corresponding to the narrow [Fe II] 1.644 um line. For the main clump where we can clearly identify the shock emission associated with the unshocked material, we analyze the observed line ratios using a shock model that includes radiative precursor. The analysis indicates that the majority of Fe in the unshocked material is in the gas phase, not depleted onto dust grains as in the general interstellar medium. We discuss the non-depletion of Fe in QSF and its implications on the immediate progenitor of the Cas A supernova.

• Journal of IKEEE
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• v.24 no.1
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• pp.132-139
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• 2020

The ionizer module used in this air cleaner supplies high voltages of 3.5KV / -4KV to the discharge electrode HV+ / HV- using a winding transformer to generate positive and negative ions by electric field radiation of carbon fiber brush. The ionizer module circuit using the existing MCU has the disadvantage of large PCB size and expensive price, and the gate driver chip using the existing ring oscillator has oscillation period sensitive to PVT (Process-Voltage-Temperature) fluctuation and there is risk of fire or electric shock because there is no fault detection function by short circuit of HV+ and GND as well as HV- and GND. Therefore, in this paper, even though PVT fluctuates, by using 7-bit binary up counter, HV+ voltage reaches the target voltage by adjusting oscillation period. And an HV+ short fault detection circuit for detecting a short circuit between HV+ and GND, an HV- short fault detection circuit for detecting a short circuit between HV- and GND, and an OVP (Over-Voltage Protection) for detecting that HV+ rises above an overvoltage are newly proposed.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.109-114
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• 2017

In this study, we have developed the active leakage current detection module based on a MSP430 processor, 16bit signal processor. This module can be operated in a desired trip threshold within 0.03 seconds as specified in KS C 4613. This developed module is expected to be applicable as a module for prevention of electric shock in smart distribution panel of smart grid.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.465-467
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• 1995

High impedance fault can not be easily detected by conventional method. But if it would not be detected and cleared quickly, it can result in fires, and electric shock. In this paper, ANN, which has learning capability, is used for high impedance fault detection. The potential of the neural network approach is demonstrated by simulation using KEPCO's measured data. Among ANN models used in this paper, CPN shows better result than BPN in respect of convergence and reliability.

• Journal of Advanced Marine Engineering and Technology
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• v.10 no.3
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• pp.1-10
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• 1986

This paper describes a new, effective method developed at the National Research Council Canada for rolling element bearing incipient failure detection. This method can detect not only outer race damage, previously published, but also inner race damage with a 100% detection rate based on a sample size of 32. The prediction of the exact angular location of the damage spot along the raceway is illustrated and experimental confirmation is presented. For the first time, a statically measurable parameter for inner and outer race damage is introduced as a means of verifying other techniques which do not offer absolute proof, but resort only to "overwhelming evidence". A brief comparison with other methods such as Shock Pulse Method, Kurtosis Analysis and High Frequency Resonance Technique is presented. A computerized automatic monitoring system utilizing the new method is described and experimental results are presented.presented.

• Fire Science and Engineering
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• v.23 no.2
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• pp.1-5
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• 2009

We studies wish to investigated establishment form of cabinet board, and confirm possibility of electrical disaster prevention through reappearance experiment of odor detection system. Established breaker consists of MCCB, RCD order in cabinet board for house, but industry is used together with. When imposed shock using shaker to terminal block that contact becomes in appropriate, flame was made sure. According to result that experiment attaching odor capsule in terminal block, capsule commissioned exactly by occurred heat. According to establishment position of sensor, difference of inspection time was about 10 seconds. Estimate odor inspection system by thing which electrical device accident prevention is available. When there is abnormal generated heat in connection of electric wire, accident prevention estimates that is possible by giving an alarm state of overheat to administrator.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.213-224
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• 2023

Type II solar radio bursts show frequency drifts from high to low over time. They have been known as a signature of coronal shock associated with Coronal Mass Ejections (CMEs) and/or flares, which cause an abrupt change in the space environment near the Earth (space weather). Therefore, early detection of type II bursts is important for forecasting of space weather. In this study, we develop a deep-learning (DL) model for the automatic detection of type II bursts. For this purpose, we adopted a 1-D Convolution Neutral Network (CNN) as it is well-suited for processing spatiotemporal information within the applied data set. We utilized a total of 286 radio burst spectrum images obtained by Hiraiso Radio Spectrograph (HiRAS) from 1991 and 2012, along with 231 spectrum images without the bursts from 2009 to 2015, to recognizes type II bursts. The burst types were labeled manually according to their spectra features in an answer table. Subsequently, we applied the 1-D CNN technique to the spectrum images using two filter windows with different size along time axis. To develop the DL model, we randomly selected 412 spectrum images (80%) for training and validation. The train history shows that both train and validation losses drop rapidly, while train and validation accuracies increased within approximately 100 epoches. For evaluation of the model's performance, we used 105 test images (20%) and employed a contingence table. It is found that false alarm ratio (FAR) and critical success index (CSI) were 0.14 and 0.83, respectively. Furthermore, we confirmed above result by adopting five-fold cross-validation method, in which we re-sampled five groups randomly. The estimated mean FAR and CSI of the five groups were 0.05 and 0.87, respectively. For experimental purposes, we applied our proposed model to 85 HiRAS type II radio bursts listed in the NGDC catalogue from 2009 to 2016 and 184 quiet (no bursts) spectrum images before and after the type II bursts. As a result, our model successfully detected 79 events (93%) of type II events. This results demonstrates, for the first time, that the 1-D CNN algorithm is useful for detecting type II bursts.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1204-1208
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• 2011

In this study, we proposed the system that calculates the algorithm with an accelerometer signal and detects the fall shock and it's direction. In order to gather the activity patterns of fall status and attach on the subject's body without consciousness, the device needs to be small. With this aim, it is attached on the right side of subject's waist. With roll and pitch angle which represent the activity of upper body, the fall situation is determined and classified into the posture pattern. The impact is calculated by the vector magnitude of accelerometer signal. And in the case of the elderly keep the same posture after fall, it can distinguish the situation whether they can stand by themselves or not. Our experimental results showed that 95% successful detection rate of fall activity with 10 subjects. For further improvement of our system, it is necessary to include tasks-oriented classifying algorithm to diverse fall conditions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.520-528
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• 2001

This paper investigates a resonant microaccelerometer that measures acceleration using a built-in micromechanical resonator, whose resonant frequency is changed by the acceleration-induced axial force. A set of design equations for the resonant microaccelerometer has been developed, including analytic formulae for resonant frequency, sensitivity, nonlinearity and maximum stress. On this basis, the sizes of the accelerometer are designed for the sensitivity of 10$^3$Hz/g in the detection range of 5g, while satisfying the conditions for the maximum nonlinearity of 5%, the minimum shock endurance of 100g and the size constraints placed by microfabrication process. A set of the resonant accelerometers has been fabricated by the combined use of bulk-micromachining and surface-micromachining techniques. From a static test of the cantilever beam resonant accelerometer, a frequency shift of 860Hz has been measured for the proof-mass deflection of 4.3${\pm}$0.5$\mu\textrm{m}$; thereby resulting in the detection sensitivity of 1.10${\times}$10$^3$Hz/g. Uncertainty analysis of the resonant frequency output has been performed to identify important issues involved in the design, fabrication and testing of the resonant accelerometer.