• Korean Journal of Occupational Health Nursing
• /
• v.28 no.1
• /
• pp.21-35
• /
• 2019

Purpose: The purpose of this study is to propose directions for the development of Occupational Health Nursing Intervention by identifying the current status and quality of Occupational Health Nursing Intervention Research in domestic industries. Methods: Between 2000 and August of 2018, total of 1,181 Occupational Health Nursing related published references were searched using 4 domestic databases, and of the total, 29 final theses that suited the requirements were analysed In this research, the quality assessment of literature that were selected as suitable was conducted using a tool for assessing the biasing risk of non-randomized studies, RoBANS(Risk of Biasing Assessment Tool for Non-randomized Study). Results: For all research, nonequivalent control group pre-posttest design was the most used as quasi-experimental designs. The effectiveness of intervention was found both in terms of physical and psychological aspects, and the result of the risk of biasing assessment showed a high risk levels in both "confounding variables" and "detection bias". Conclusion: Occupational Health Nursing Intervention have been steadily making improvements in terms of both quality and quantity, and as for more effective intervention developments that improves the physical and mental health of the workers, supplementation in strict research design and in ethical aspects deems necessary.

• Journal of Positioning, Navigation, and Timing
• /
• v.12 no.1
• /
• pp.11-22
• /
• 2023

In this paper, we propose an efficient satellite selection method for multi-constellation GNSS. The number of visible satellites has increased dramatically recently due to multi-constellation GNSS. By the increased availability, the overall GNSS performance can be improved. Whereas, due to the increase of the number of visible satellites, the computational burden in implementing advanced processing such as integer ambiguity resolution and fault detection can be increased considerably. As widely known, the optimal satellite selection method requires very large computational burden and its real-time implementation is practically impossible. To reduce computational burden, several sub-optimal but efficient satellite selection methods have been proposed recently. However, these methods are prone to the local optimum problem and do not fully utilize the information redundancy between different constellation systems. To solve this problem, the proposed method utilizes the inter-system biases and geometric assignments. As a result, the proposed method can be implemented in real-time, avoids the local optimum problem, and does not exclude any single-satellite constellation. The performance of the proposed method is compared with the optimal method and two popular sub-optimal methods by a simulation and an experiment.

• Journal of the Semiconductor & Display Technology
• /
• v.23 no.1
• /
• pp.71-78
• /
• 2024

In indoor environments, since global positioning system (GPS) signals can be blocked by obstacles, such as building structure. the performance of GPS-based positioning methods can be degraded because of the loss of GPS signals. To solve this problem, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope, accelerometer, and magnetometer, have been proposed to enhance the positioning accuracy in indoor environments. IMU-based positioning methods can estimate the location of the user by calculating the velocity and heading angle of the user without the help of GPS. However, low-cost MEMS IMUs may lead to drift error and large bias. In addition, positioning errors in IMU-based positioning approaches can be caused by the irrelevant motion of the pedestrian. In this study, we propose an enhanced indoor positioning method that provides more reliable localization results by using the camera, light detection and right (LiDAR), and ARKit framework on the iPhone. Through reliable positioning results and augmented reality (AR) experiences, our indoor positioning system can provide indoor space guidance services.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_3
• /
• pp.1779-1790
• /
• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2014.02a
• /
• pp.298-298
• /
• 2014

Quantum dot infrared photodetectors (QDIPs) based on Stranski-Krastanov (SK) quantum dots (QDs) have been widely explored for improved device performance using various designs of heterostructures. However, one of the biggest limitations of this approach is the "pancake" shape of the dot, with a base of 20-30 nm and a height of 4-6 nm. This limits the 3D confinement in the quantum dot and reduces the ratio of normal incidence absorption to the off-axis absorption. One of the alternative growth modes to the formation of SK QDs is a sub-monolayer (SML) deposition technique, which can achieve a much higher density, smaller size, better uniformity, and has no wetting layer as compared to the SK growth mode. Due to the advantages of SML-QDs, the SML-QDIP design has attractive features such as increased normal incidence absorption, strong in-plane quantum confinement, and narrow spectral wavelength detection as compared with SK-DWELL. In this study, we report on the improved device performance of InAs/InGaAs SML-QDIP with different composition of $Al_xGa1-_xAs$ barrier. Two SML-QDIPs (x=0.07 for sample A and x=0.20 for sample B) are grown with the 4 stacks 0.3 ML InAs. It is investigated that sample A with a confinement-enhanced (CE) $Al_{0.22}Ga_{0.78}As$ barrier had a single peak at $7.8{\mu}m$ at 77 K. However, sample B with an $Al_{0.20}Ga_{0.80}As$ barrier had three peaks at (${\sim}3.5{\mu}m$, ${\sim}5{\mu}m$, ${\sim}7{\mu}m$) due to various quantum confined transitions. The measured peak responsivities (see Fig) are ~0.45 A/W (sample A, at $7.8{\mu}m$, $V_b=-0.4V$ bias) and ~1.3 A/W (sample B, at $7{\mu}m$, $V_b=-1.5V$ bias). At 77 K, sample A and B had a detectivity of $1.2{\times}10^{11}cm.Hz^{1/2}/W$ ($V_b=-0.4V$ bias) and $5.4{\times}10^{11}cm.Hz^{1/2}/W$ ($V_b=-1.5V$ bias), respectively. It is obvious that the higher $D^*$ of sample B (than sample A) is mainly due to the low dark current and high responsivity.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.2
• /
• pp.31-43
• /
• 2005

Four time points of the fractional area data during the 15 years of the highest group of land surface temperature and the lowest group of NDVl of the Kunsan city Chollabuk_do, Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the intention to detect the changes of urban land cover. As long as the effective contributions of satellite images in the continuous monitoring of the wide area for wide range of time period, Landsat-5 TM and Landsat-7 ETM+ artificial satellite images, acquisited over the Kunsan city area, are surveyed by the compared calibration after quantization and classification of the deviations between TM and ETM+ images substituted approved error correction thresholds such as gains and biases or offsets. This experiment and research applied Landsat-5 TM and Landsat-7 ETM+ artificial satellite images in change detection of urban land cover in urbanized Kunsan city, then detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of NDVI which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of NDVI will be able to give proof an effective suitability to the land city change detection monitoring.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.1011-1014
• /
• 2006

Coarse resolution (9 - 50 km pixels) Sea Surface Temperature satellite data are frequently considered adequate for open ocean research. However, coastal regions, including coral reef, estuarine and mesoscale upwelling regions require high-resolution (1-km pixel) SST data. The AVHRR SST data often suffer from navigation errors of several kilometres and still require manual navigation adjustments. The second serious problem is faulty and ineffective cloud-detection algorithms used operationally; many of these are based on radiance thresholds and moving window tests. With these methods, increasing sensitivity leads to masking of valid pixels. These errors lead to significant cold pixel biases and hamper image compositing, anomaly detection, and time-series analysis. Here, after manual navigation of over 40,000 AVHRR images, we implemented a new cloud filter that differs from other published methods. The filter first compares a pixel value with a climatological value built from the historical database, and then tests it against a time-based median value derived for that pixel from all satellite passes collected within ${\pm}3$ days. If the difference is larger than a predefined threshold, the pixel is flagged as cloud. We tested the method and compared to in situ SST from several shallow water buoys in the Florida Keys. Cloud statistics from all satellite sensors (AVHRR, MODIS) shows that a climatology filter with a $4^{\circ}C$ threshold and a median filter threshold of $2^{\circ}C$ are effective and accurate to filter clouds without masking good data. RMS difference between concurrent in situ and satellite SST data for the shallow waters (< 10 m bottom depth) is < $1^{\circ}C$, with only a small bias. The filter has been applied to the entire series of high-resolution SST data since1993 (including MODIS SST data since 2003), and a climatology is constructed to serve as the baseline to detect anomaly events.

• Journal of Radiation Protection and Research
• /
• v.35 no.3
• /
• pp.117-123
• /
• 2010

Plutonium is by far the most important of the transuranic elements which have been released into the environment due to radio-toxicity and long term radiation effects on humans. And Pu isotope ratio ($^{240}Pu/^{239}Pu$) is of great interest because this ratio is used as a fingerprint for different sources. Mass spectrometry has been used as an useful atom counting technique with several advantages over decay counting techniques for the determination of Pu isotopes. It enables a determination of Pu isotope ratio in the environmental samples with a low detection limit and a short determination time. An ICP-MS is the representative mass spectrometry for Pu determination. In this study, the precision of $^{240}Pu/^{239}Pu$ isotope ratio was improved by using 4 multiple ion counters of MC-ICP-MS. The detection limit of $^{239}Pu$ and $^{240}Pu$ were $0.10\;fg\;ml^{-1}$ ($0.24\;{\mu}Bq\;ml^{-1}$), $0.12\;fg\;ml^{-1}$ ($0.97\;{\mu}Bq\;ml^{-1}$), respectively. The relative standard deviation of $^{240}Pu/^{239}Pu$ isotope ratio was less than 1 % in trace level. The various reference materials (seawater, soil and sediment) were analyzed to verify this method and their analytical results were in good agreement with the certified (or recommended value) value.

• YAKHAK HOEJI
• /
• v.52 no.6
• /
• pp.419-425
• /
• 2008

A qualitative and quantitative analytical method was developed for detection of methamphetamine (MA) and its main metabolite amphetamine (AM) in oral fluid. Oral fluids of eleven drug abusers were provided by Police, specimens were collected by stimulation with a cotton swab treated with 20 mg of citric acid ($Salivette^{(R)}$; Sarstedt, USA). As the preliminary test, oral fluid samples were screened for amphetamines by Fluorescence Polarization Immunoassay (TDxFLx, Abbott Co.). Extraction for MA was performed using solid-phase extraction (SPE) by $RapidTrace^{TM}$ (Zymark, USA) with mixed mode cation exchange cartridge, CLEAN $SCREEN^{(R)}$ (130 mg/3 ml, UCT) after dilution with phosphate buffer. Samples were evaporated and derivatized by pentafluoropropionic acid anhydride (PFPA). Quantitation of MA and AM was performed by gas chromatography-mass spectrometry (GC-MS) using selective ion monitoring (SIM), the quantitation ions were m/z 204 (MA), 208 (MA-$D_5$), 190 (AM) and 194 (AM-$D_5$). The selectivity, linearity of calibration, limit of detection (LOD) and quantification (LOQ) within- and between day precision, accuracy and recoveries were examined as parts of the method validation. All oral fluid samples gave positive results to immunoassay for MA (cut-off level, 50 ng/ml as d-amphetamine). Concentrations of MA and AM by GC-MS in eleven samples were ranged 104.2${\sim}$4603.3 ng/ml and 32.4${\sim}$268.6 ng/ml, respectively. Extracted calibration curves of MA and AM were linear over the two concentration range of 1${\sim}$100 and 50${\sim}$1000 ng/ml with correlation coefficient of above 0.999. LOQ of MA and AM was 1 and 3 ng/ml, respectively. The intraand inter-day run precisions (CV) for MA and AM were less than 10%, and the accuracies (bias) for MA and AM were also less than 10% at the two different concentrations 5 and 100 ng/ml at low calibration range, 50 and 1000 ng/ml at high calibration range. The absolute recoveries of MA and AM at low and high calibration ranges were more than 82% and 75%, respectively. In this study the qualitative and quantitative analytical method of MA in oral fluid was established. Oral fluid testing may detect drug use in past hours because of its shorter detection window than urine, and be useful in post-accident situations. So oral fluids will be most useful for testing drug abuse in the driving under the influence of drug (DUID) as the alternative specimens of urine.

• Korean Journal of Remote Sensing
• /
• v.37 no.2
• /
• pp.233-243
• /
• 2021

Photovoltaic panels are hazardous electronic waste that has heavy metal as one of the hazardous components. Each year, hazardous electronic waste is increasing worldwide and every heavy rainfall exposes the photovoltaic panel to become the source of heavy metal soil contamination. the development needs a monitoring technology for this hazardous exposure. this research use relationships between SAR temporal baseline and coherence of Sentinel-1 satellite to detected photovoltaic panel. Also, the photovoltaic plant detection tested using the difference between that photovoltaic panel and the other difference surface of coherence. The author tested the photovoltaic panel and its environment to calculate differences in coherence relationships. As a result of the experiment, the coherence of the photovoltaic panel, which is assumed to be a permanent scatterer, shows a bias that is biased toward a median value of 0.53 with a distribution of 0.50 to 0.65. Therefore, further research is needed to improve errors that may occur during processing. Additionally, the author found that the change detection using a temporal baseline is possible as the rate of reduction of coherence of photovoltaic panels differs from those of artificial objects such as buildings. This result could be an efficient way to continuously monitor regardless of weather conditions, which was a limitation of the existing optical satellite image-based photovoltaic panel detection research and to understand the spatial distribution in situations such as photovoltaic panel loss.