• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.449-456
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• 2019

This paper is a study on the construction of a wall-climbing mobile robot using vacuum suction and wheel-type movement, and a comparison of the performance of an automatic wall crack detection algorithm based on machine learning that is suitable for such an embedded environment. In the embedded system environment, we compared performance by applying recently developed learning methods such as YOLO for object learning, and compared performance with existing edge detection algorithms. Finally, in this study, we selected the optimal machine learning method suitable for the embedded environment and good for extracting the crack features, and compared performance with the existing methods and presented its superiority. In addition, intelligent problem - solving function that transmits the image and location information of the detected crack to the manager device is constructed.

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.1-7
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• 2019

Thisstudy presentsthe development of a fast-time airport surface simulator. The simulator usesthe output from a first-come first-served (FCFS) scheduler and has adopted one-dimensional dynamic model to simulate the movement of the aircraft on the surface. Higher collision risks situations in the airport surface traffic are analyzed to classify those situations into six cases. A conflict detection and resolution algorithm is implemented to maintain separation distance and to prevent deadlock. The simulator was tested with a scenario at the Incheon International Airport that contains 72 aircraft. Without the conflict detection and resolution, various conflict situations are identified. When the conflict detection and resolution algorithm is managing the traffic, it is confirmed that the conflicts are removed at the price of additional delays. In the conflict resolution algorithm, three prioritization strategies are implemented, and delayed aircraft count and average additional delays are compared. Prioritization based on remaining time or distance showed smaller total additional delay compared to choosing minimum delay priority for each situation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.67-75
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• 2024

Crosswalks play an important role for the safe movement of pedestrians in a complex urban environment. However, for the visually impaired, crosswalks can be a big risk factor. Although assistive tools such as braille blocks and acoustic traffic lights exist for safe walking, poor management can sometimes act as a hindrance to safety. This paper proposes a method to improve accuracy in a deep learning-based real-time crosswalk detection model that can be used in applications for pedestrian assistance for the disabled at the beginning. The image was binarized by utilizing the characteristic that the white line of the crosswalk image contrasts with the road surface, and through this, the crosswalk could be better recognized and the location of the crosswalk could be more accurately identified by using two models that learned the whole and the middle part of the crosswalk, respectively. In addition, it was intended to increase accuracy by creating a boundary box that recognizes crosswalks in two stages: whole and part. Through this method, additional frames that the detection model did not detect in RGB image learning from the crosswalk image could be detected.

• Investigative Magnetic Resonance Imaging
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• v.16 no.1
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• pp.55-66
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• 2012

Purpose : During brain MRI scanning, subject's head motion can adversely affect MRI images. To minimize MR image distortion by head movement, we developed an optical tracking system to detect the 3-D movement of subjects. Materials and Methods: The system consisted of 2 CCD cameras, two infrared illuminators, reflective sphere-type markers, and frame grabber with desktop PC. Using calibration which is the procedure to calculate intrinsic/extrinsic parameters of each camera and triangulation, the system was desiged to detect 3-D coordinates of subject's head movement. We evaluated the accuracy of 3-D position of reflective markers on both test board and the real MRI scans. Results: The stereo system computed the 3-D position of markers accurately for the test board and for the subject with glasses with attached optical reflective marker, required to make regular head motion during MRI scanning. This head motion tracking didn't affect the resulting MR images even in the environment varying magnetic gradient and several RF pulses. Conclusion: This system has an advantage to detect subject's head motion in real-time. Using the developed system, MRI operator is able to determine whether he/she should stop or intervene in MRI acquisition to prevent more image distortions.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.33-38
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• 2012

An free-fall object is received only force of gravity. Movement that only accept gravity is free-fall movement, and a free-falling object is free falling body. In other words, free falling body is only freely falling objects under the influence of gravity, regardless of the initial state of objects movement. In this paper, we assume, ignoring the resistance of the air, and the free-fall acceleration by the height does not change within the range of the short distance in the vertical direction. Under these assumptions, we can know about time and maximum height to reach the peak point from jumping vertically upward direction, time and speed of the car return to the starting position, and time and speed when the car fall to the ground. It can be measured by jumping degree and risk of accident from car or motorcycle in telematics.

• Journal of Navigation and Port Research
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• v.42 no.4
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• pp.277-282
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• 2018

Recently, the Vessel Traffic Service (VTS) coverage has expanded to include coastal areas following the increased attention on vessel traffic safety. However, it has increased the workload on the VTS operators. In some cases, when the traffic volume increases sharply during the rush hour, the VTS operator may not be aware of the risks. Therefore, in this paper, we proposed a new method to recognize ship movement anomalies automatically to support the VTS operator's decision-making. The proposed method generated traffic pattern model without any category information using the unsupervised learning algorithm.. The anomaly score can be calculated by classification and comparison of the trained model. Finally, we reviewed the experimental results using a ship-handling simulator and the actual trajectory data to verify the feasibility of the proposed method.

• Journal of the Ergonomics Society of Korea
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• v.35 no.3
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• pp.125-133
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• 2016

Objective: The aim of this study is to figure out the level of Functional Movement Screen (FMS) of 122 automobile manufacturing workers and to set the FMS score for predicting risk of musculoskeletal disorders. Background: Although today's industrial sites have been becoming automated rapidly, the risks of work-related musculoskeletal disorders (WMSDs) have been on the rise. In the case of WMSDs, it is important to control WMSDs at the early stage. Early detection of WMSDs is very important for the successful treatment. However, the medical examination puts a great financial burden on most workers. To reduce their burden, there is one test to check the musculoskeletal functional condition and to predict the risk of injury, which is called FMS. Method: This research tested the FMS score of 122 workers at a motor company, and also conducted a questionnaire survey of individual characteristics and job characteristics. Results: For the 122 subjects, the average score of FMS is $14.63{\pm}2.27$. There is a negative correlation between FMS and their ages and BMI (p <0.05). FMS is higher when exercising regularly (p <0.05). The FMS scores of musculoskeletal disorder patients are lower than those of normal workers (p <0.05). While it is more likely to become a musculoskeletal disorder patient when FMS score is less than 14, it is more likely to become a normal worker when FMS score is more than or equal to 14. Conclusion: According to the result of FMS test, there is a score difference between individuals with musculoskeletal disorders and normal ones. FMS scores can also predict and identify workers with risk of the musculoskeletal disorders. Application: According to this study, FMS can be expected to have a positive effect on the prevention of WMSDs in worksites.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.6
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• pp.684-689
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• 2017

We examined the possibility of developing an early monitoring system using the shell valve movement activity of Pacific oyster (Crassostrea gigas) for early detection of low salinity water in coastal areas. At salinity levels of 30 psu and 20 psu, SVMs were detected $7.32{\pm}3.21times/hr$ and $7.11{\pm}3.90times/hr$, respectively, The patterns and times of SVMs were not significantly different between the two experiment phases. However, at 10 psu and 5 psu, shell valves were observed to be permanently closed in all experiments. Under combined condition (Group 1: temperature $15^{\circ}C$ ${\times}$ salinity 15 psu), SVMs were observed from 20 psu to 30 psu over a 2 - 3 hr period, and then remained closed. In Group 2 (temperature $30^{\circ}C$ ${\times}$ salinity 15 psu), SVMs were observed, which indicated that the physiological condition of the oysters reached a critical point. Thus, it may be possible to utilize SVMs as an early warning signal for low salinity water.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.256-257
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• 2022

In this paper, we introduce a method of extracting three-dimensional feature points through the movement of a single mobile device. Using a monocular camera, a 2D image is acquired according to the camera movement and a baseline is estimated. Perform stereo matching based on feature points. A feature point and a descriptor are acquired, and the feature point is matched. Using the matched feature points, the disparity is calculated and a depth value is generated. The 3D feature point is updated according to the camera movement. Finally, the feature point is reset at the time of scene change by using scene change detection. Through the above process, an average of 73.5% of additional storage space can be secured in the key point database. By applying the algorithm proposed to the depth ground truth value of the TUM Dataset and the RGB image, it was confirmed that the\re was an average distance difference of 26.88mm compared with the 3D feature point result.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.89-89
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• 2022

Soybean (Glycine max (L.) Merr.) is a representative food resource. To preserve the integrity of soybean, it is necessary to protect soybean yield and seed quality from threats of various pests and diseases. Riptortus pedestris is a well-known insect pest that causes the greatest loss of soybean yield in South Korea. This pest not only directly reduces yields but also causes disorders and diseases in plant growth. Unfortunately, no resistant soybean resources have been reported. Therefore, it is necessary to identify the distribution and movement of Riptortus pedestris at an early stage to reduce the damage caused by insect pests. Conventionally, the human eye has performed the diagnosis of agronomic traits related to pest outbreaks. However, due to human vision's subjectivity and impermanence, it is time-consuming, requires the assistance of specialists, and is labor-intensive. Therefore, the responses and behavior patterns of Riptortus pedestris to the scent of mixture R were visualized with a 3D model through the perspective of artificial intelligence. The movement patterns of Riptortus pedestris was analyzed by using time-series image data. In addition, classification was performed through visual analysis based on a deep learning model. In the object tracking, implemented using the YOLO series model, the path of the movement of pests shows a negative reaction to a mixture Rina video scene. As a result of 3D modeling using the x, y, and z-axis of the tracked objects, 80% of the subjects showed behavioral patterns consistent with the treatment of mixture R. In addition, these studies are being conducted in the soybean field and it will be possible to preserve the yield of soybeans through the application of a pest control platform to the early stage of soybeans.