• Journal of the Korean GEO-environmental Society
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• v.12 no.1
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• pp.51-60
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• 2011

Electrical resistivity is applied for understanding details about layers and obtaining basic properties of soils to various measurement devices. The objective of this study is development of TRP(Temperature-compensated Resistivity Probe), analysis about effects of temperature changes during cone penetration test, and observation of characteristics of cone penetration. In order to observation of temperature changes according to a diameter difference of resistivity cone probe, the cone which has wedge type cone tip is made to two types, 2mm and 5mm. Temperature sensor is attached at 15mm below from cone tip because of an electrical interference with elecrical resistance probe. Delectrical connector is used to prevent electric disturbance between motor type penetrating machine and electrical resistivity cone probe. Application tests are carried out in acrylic cell whose diameter is 30cm with uniform Jumunjin sand according to densification caused by blows. The test results indicate that the temperature is increased uniformly during penetration and a tendency, characteristics of cone penetration, is discovered during altering state of soils. This study suggests that the temperature effects and characteristics of penetration should be considered in penetrating tests in order to conduct an accurate ground investigation using TRP(Temperature-compensated Resistivity Probe).

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.260-269
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• 2022

In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.63-71
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• 2021

Among drone autonomous flight technologies, obstacle avoidance is a very important technology that can prevent damage to drones or surrounding environments and prevent danger. Although the LiDAR sensor-based obstacle avoidance method shows relatively high accuracy and is widely used in recent studies, it has disadvantages of high unit price and limited processing capacity for visual information. Therefore, this paper proposes an obstacle avoidance algorithm for drones using camera-based PPO(Proximal Policy Optimization) reinforcement learning, which is relatively inexpensive and highly scalable using visual information. Drone, obstacles, target points, etc. are randomly located in a learning environment in the three-dimensional space, stereo images are obtained using a Unity camera, and then YOLov4Tiny object detection is performed. Next, the distance between the drone and the detected object is measured through triangulation of the stereo camera. Based on this distance, the presence or absence of obstacles is determined. Penalties are set if they are obstacles and rewards are given if they are target points. The experimennt of this method shows that a camera-based obstacle avoidance algorithm can be a sufficiently similar level of accuracy and average target point arrival time compared to a LiDAR-based obstacle avoidance algorithm, so it is highly likely to be used.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.851-861
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• 2022

In this study, we analyzed the effects of trees planted in urban areas on PM_2.5 reduction using a computational fluid dynamics (CFD) model. For realistic numerical simulations, the meteorological components(e.g., wind velocity components and air temperatures) predicted by the local data assimilation and prediction system (LDAPS), an operational model of the Korea Meteorological Administration, were used as the initial and boundary conditions of the CFD model. The CFD model was validated against, the PM_2.5 concentrations measured by the sensor networks. To investigate the effects of trees on the PM_2.5 reduction, we conducted the numerical simulations for three configurations of the buildings and trees: i) no tree (NT), ii) trees with only drag effect (TD), and iii) trees with the drag and dry-deposition effects (DD). The results showed that the trees in the target area significantly reduced the PM_2.5 concentrations via the dry-deposition process. The PM_2.5 concentration averaged over the domain in DD was reduced by 5.7 ㎍ m^-3 compared to that in TD.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.365-371
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• 2022

In order to obtain excellent spatial resolution in the PET detector, when the detector module is designed using very small scintillation pixels, overlap occurs at the edges and corners of the scintillation pixel array in the flood image. By using a light guide, the occurrence of overlap can be reduced. In this study, after using a scintillator of 0.8 mm × 0.8 mm × 20 mm to form a 14 × 14 array, 3 mm × 3 mm SiPM pixels are combined with 4 × 4 photosensor to reduce the occurrence of overlap. The optimal thickness of the light guide used for this purpose was derived. Quantitative evaluation was performed based on scintillation pixel images of edges and corners where overlap occurs mainly in the acquired flood image. Quantitative evaluation was calculated through the interval and full width at half maximum between scintillation pixel images, and when a light guide with a thickness of 2 mm was used, the best image was obtained with a k value of 2.60. In addition, as a result of measuring the energy resolution through the energy spectrum, the light guide with a thickness of 2 mm showed the best result at 28.5%. If a 2 mm light guide is used, it is considered that the best flood image and energy resolution with minimal overlap can be obtained.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.78-88
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• 2022

Objectives: To develop the smart sensor to protect worker's health from chemical exposure by adopting ICT (Information and Communications Technology) technologies. Methods: To develope real-time chemical exposure monitoring system, IoT (Internet of Things) sensor technology and regulations were reviewed. We developed and produced smart sensor. A smart sensor is a system consisting of a sensor unit, a communication unit, and a platform. To verify the performance of smart sensors, each sensor has been certified by the Korea Laboratory Accreditation Scheme (KOLAS). Results: Chemicals (TVOC; Total Volatile Organic Compounds, Cl₂: Chlorine, HF: Hydrogen fluoride and HCN: Hydrogen cyanide) were selected according to a priority logic (KOSHA Alert, acute poisoning statistics, literature review). Notifications were set according to OEL (occupational exposure limit). Sensors were selected based on OEL and the capabilities of the sensors. Communication is designed to use LTE (Long Term Evolution) and Wi-Fi at the same time for convenience. Electronic platform were applied to build this monitoring system. Conclusions: Real-time monitoring system for OEL of hazardous chemicals in workplace was developed. Smart sensor can detect chemicals to complement monitoring of traditional workplace environmental monitoring such as short term and peak exposure. Further research is needed to expand the scope of application, improve reliability, and systematically application.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.119-129
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• 2023

Sleep apnea causes various secondary disease such as hypertension, stroke, myocardial infarction, depression and cognitive impairment. Early detection and continuous management of sleep apnea are urgently needed since it causes cardio-cerebrovascular diseases. In this study, wearable device for monitoring respiration during sleep using PVDF film was developed to detect vibration through trachea caused by breathing, which determines normal breathing and sleep apnea. Variables such as respiration rate and apnea were extracted based on the detected breathing sound data, and a noise reduction algorithm was established to minimize the effect even when there is a noise signal. In addition, it was confirmed that irregular breathing patterns can be analyzed by establishing a moving threshold algorithm. The results show that the accuracy of the respiratory rate from the developed device was 98.7% comparing with the polysomnogrphy result. Accuracy of detection for sleep apnea event was 92.6% and that of the sleep apnea duration was 94.0%. The results of this study will be of great help to the management of sleep disorders and confirmation of treatment by commercialization of wearable devices that can monitor sleep information easily and accurately at home during daily life and confirm the progress of treatment.

• Journal of Korean Society of Disaster and Security
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• v.16 no.1
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• pp.105-113
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• 2023

Jeollanam-do has 25 land-to-island and island-to-island bridges, the largest number in Korea. It is a local government rich in specialized marine and tourism resources centered on the archipelago and the sea bridges connecting them. However, in the case of sea-crossing bridges, when strong winds or typhoons occur, there is an issue that increases anxiety among users and local residents due to excessive vibration of the bridge, apart from structural safety of the bridge. In fact, in the case of Cheonsa Bridge in Shinan-gun, which was recently opened in 2019, vehicle traffic restrictions due to strong winds and excessive vibrations frequently occurred, resulting in complaints from local residents and drivers due to increased anxiety. Therefore, based on the data measured using IoT measurement technology, it is possible to relieve local residents' anxiety about the safety management of marine bridges by providing quantitative and accurate bridge vibration levels related to traffic and wind conditions of bridges in real time to local residents. This study uses the existing measurement system and IoT sensor to constantly observe the wind speed and vibration of the marine bridge, and transmits it to local residents and managers to relieve anxiety about the safety and traffic of the sea-crossing bridge, and strong winds and to develop technologies capable of preemptively responding to large-scale disasters.

• PNF and Movement
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• v.21 no.2
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• pp.171-183
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• 2023

Purpose: The purpose of this study was to compare universal goniometry (UG), which is commonly used in clinical practice to measure the range of motion (ROM) of finger joints with a wearable soft sensor glove, and to analyze the reliability to determine its usefulness. Methods: Ten healthy adults (6 males, 4 females) participated in this study. The metacarpophalangeal joint (MCP), interphalangeal joint (IP), and proximal interphalangeal joint (PIP) of both hands were measured using UG and Mollisen HAND soft sensor gloves during active flexion, according to the American Society for Hand Therapists' measurement criteria. Measurements were taken in triplicate and averaged. The mean and standard deviation of the two methods were calculated, and the 95% limits of agreement (LOA) of the measurements were calculated using the intraclass correlation coefficient (ICC) and Bland-Altman plot to examine the reliability and discrepancies between the measurements. Results: The results of the mean values of the flexion angles for the active range of motion (AROM) of the finger joints showed large angular differences in the finger joints, except for the MCP of the thumb. In the inter-rater reliability analysis according to the measurement method, the ICC (2, 1) value showed a low level close to 0, and the mean difference by the Bland-Altman plot showed a value greater than 0, showing a pattern of discrepancy. The 95% LOA had a wide range of differences. Conclusion: This study is a preliminary study investigating the usefulness of the soft sensor glove, and the reliability analysis showed a low level of reliability and inconsistency. However, if future studies can overcome the limitations of this study and the technical problems of the soft sensor glove in the development stage, it is suggested that the measurement instrument can show more accurate measurement and higher reliability when measuring ROM with UG.

• Journal of the Korean Geotechnical Society
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• v.25 no.12
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• pp.5-12
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• 2009

As rock bolts become one of the main support systems in tunnels and underground structures, the integrity of the rock bolts affects the safety of these structures. The purpose of this study is the evaluation of rock bolt integrity using wavelet transforms of the guided ultrasonic waves by using transmission test in the field. After several rock bolts with various defect ratios are embedded into a large scale concrete block and rock mass, guided waves are generated by a piezo disk element and measured by an acoustic emission (AE) sensor. The captured signals are analyzed in the time-frequency domain using the wavelet transform based on a Gabor wavelet. Peak values in the time-frequency domain represent the interval of travel time of each echo. The energy velocities of the guided waves increase with an increase in the defect ratio. The suitable curing time for the evergy velocity analysis is proposed by the laboratory test, and in-situ tests are performed in two tunnelling sites to verify the applicability of rock bolt integrity tests performed after proposed curing time. This study proves that time-frequency domain analysis is an effective tool for the evaluation of the rock bolt integrity.