• Journal of Acupuncture Research
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• v.20 no.1
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• pp.22-34
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• 2003

Objective : To ascertain whether the concept of the treatment side is associated with changes in the blind spot mapping that represents the brain function. Methods : Among the outpatients who visited to Department of Acupuncture & Moxibustion, National Medical Center from March 2002 to October 2002, we selected 40 clinical trial volunteers that showed right side physiological blind spot more enlarged than left, and underwent the examinations of Department of Opthalmology, National Medical Center for ruling out the pathological conditions. Physiological blind spot maps were used as an integer of brain activity before and after electroacupuncture application on the unilateral ST36 meridian point by dividing 40 subjects into two comparative groups for double-blind controlled study. Results: The significant changes in the blind spots were observed. Electroacupuncture application on the ipsilateral or contralateral ST36 of an enlargement cortical map were associated with the concept of determining the treatment side. In the case of electroacupuncture application on the ipsilateral side of an enlarged blind spot, there were decrease of $4.11{\pm}8.56cm$(17.3%) in blind spot perimetry length(p < 0.05). In the case of contralateral side, there were increase of $3.19{\pm}5.40cm$(13.7%) in blind spot perimetry length(p<0.05). The Differences were statistically significant(p<0.05). Conclusions: We found that eletroacupuncture application was associated with an increase or decrease in the brain function in the view of blind spot changes depending on the treatment side. These results suggest that the traditional acupuncture therapeutic strategy with determining the treatment side has clinical significance in the view of the brain function.

• Transportation Technology and Policy
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• v.8 no.3
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• pp.31-39
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• 2011

• Journal of Drive and Control
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• v.17 no.4
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• pp.8-14
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• 2020

Intelligent devices using ICT technology have been introduced in the field of construction machinery to improve productivity and stability. Among the intelligent devices, Machine Guidance is a device that provides real-time posture, location, and work range to drivers by installing various sensors, controllers, and satellite navigation systems on construction machines. Conversely, the efficiency of equipment that requires location information, such as machine guidance, will be greatly reduced in buildings, and tunnels in the GPS blind spots. Thus, the other high-precision positioning technologies are required in the GPS blind spot zone. In this study, we will develop a relative position measurement system that provides precise location information such as construction machinery and robots in a local area where the GPS reception is difficult. A relative position measurement system tracks a marker in the form of a sphere installed on a vehicle by using the image base tracking technology, and measures the distance and direction information to the marker to calculate a position.

• Journal of health informatics and statistics
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• v.43 no.4
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• pp.318-328
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• 2018

Objectives: People are living longer, but often with diseases or chronic conditions. As a consequence, interest in resolving insurance blind spots is growing. This study provides substandard risk-relevant statistics to help substandard risks who are likely to fall in insurance blind spots obtain insurance coverage, such as the reimbursement of medical costs, as well as to stimulate insurance product development. Methods: This study uses National Health Insurance Service (NHIS) cohort data to determine the relevant statistics. The incidence rates of severe diseases are derived and compared against standard risks to establish a set of relative risk factors. These incidence rates of standard and substandard risks are then compared. Results: Currently, an individual's cancer history is used in the underwriting process for simplified issue insurance. However, underwriting focusing on hospitalization and procedures related to serious illnesses could lower premiums for substandard risks. Moreover, the statistical results could be used to expand the coverage of health insurance products. Conclusions: This study's relative risk factors can be used to derive simplified issue premium rates for substandard risks. They can also be used to implement discount and loading schemes for medical reimbursement insurance and help insurance companies implement proactive risk management.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.760-767
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• 2022

This paper introduces alert fatigue and presents methods to measure alert fatigue by using physiological signals. Alert fatigue is a phenomenon that which an individual is constantly exposed to frequent alarms and becomes desensitized to them. Blind spots are one leading cause of struck-by accidents, which is one most common causes of fatal accidents on construction sites. To reduce such accidents, construction equipment is equipped with an alarm system. However, the frequent alarm is inevitable due to the dynamic nature of construction sites and the situation can lead to alert fatigue. This paper introduces alert fatigue and proposes methods to use physiological signals such as electroencephalography, electrodermal activity, and event-related potential for the measurement of alert fatigue. Specifically, this paper presents how raw data from the physiological sensors measuring such signals can be processed to measure alert fatigue. By comparing the processed physiological data to behavioral data, validity of the measurement is tested. Using preliminary experimental results, this paper validates that physiological signals can be useful to measure alert fatigue. The findings of this study can contribute to investigating alert fatigue, which will lead to lowering the struck-by accidents caused by blind spots.

• Journal of the Korean Society of Radiology
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• v.81 no.2
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• pp.351-364
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• 2020

Missed lung cancers on chest radiograph (CXR) may delay the diagnosis and affect the prognosis. CXR is the primary imaging modality to evaluate the lungs and mediastinum in daily practice. The purpose of this article is to review chest radiographs for common blind spots and highlight the importance of various radiologic presentations in primary lung cancer to avoid significant diagnostic errors on CXR.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.605-611
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• 2023

Accidents at construction sites have a very high rate of fatalities due to the nature of being prone to severe injury patients. In order to reduce the mortality rate of severely injury patients, quick response is required, and some systems that detect accidents using AI technology and cameras have been devised to respond quickly to accidents. However, since existing accident detection systems use only a single camera, there are blind spots, Thus, they cannot detect all accidents at a construction site. Therefore, in this paper, we present the system that minimizes the detection blind spot by using multiple cameras. Our implemented system extracts feature points from the images of multiple cameras with the YOLO-pose library, and inputs the extracted feature points to a Long Short Term Memory-based recurrent neural network in order to detect accidents. In our experimental result, we confirme that the proposed system shows high accuracy while minimizing detection blind spots by using multiple cameras.

• Journal of IKEEE
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• v.22 no.1
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• pp.168-173
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• 2018

To overcome the problems of the existing black box which is exposed to the risk of blind spots in the imaging of a fixed front and rear views of an object, this paper suggests a new intelligent black box that can detect and shoot side views of an object. This paper proposes an algorithm of the intelligent black box with a rotating function in order to compensate for the side blind spot of the vehicle. This intelligent black box with rotating screen adopts the infrared distance sensor to sense an object which approaches to the vehicle and rotates automatically towards the object.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.38-44
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• 2018

In this paper, we propose Intelligent Driver Assistance System (I-DAS) for driver safety. The proposed system recognizes safety and danger status by analyzing blind spots that the driver cannot see because of a large angle of head movement from the front. Most studies use image pre-processing such as face detection for collecting information about the driver's head movement. This not only increases the computational complexity of the system, but also decreases the accuracy of the recognition because the image processing system dose not use the entire image of the driver's upper body while seated on the driver's seat and when the head moves at a large angle from the front. The proposed system uses a convolutional neural network to replace the face detection system and uses the entire image of the driver's upper body. Therefore, high accuracy can be maintained even when the driver performs head movement at a large angle from the frontal gaze position without image pre-processing. Experimental result shows that the proposed system can accurately recognize the dangerous conditions in the blind zone during operation and performs with 95% accuracy of recognition for five drivers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.162-164
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• 2022

Efforts are being made to prevent traffic accidents within the child protection zone. Efforts are being made to prevent accidents by enacting safety facilities and laws to prevent traffic accidents in the school zone. However, traffic accidents in school zones continue to occur. If the driver can know the situation in the child protection zone in advance, accidents can be reduced. In this paper, we design a camera that eliminates blind spots in school zones and a number recognition camera system that can collect pre-traffic information. Design a LIDAR system that recognizes vehicle speed and pedestrians. Design an LED guidance system that delivers information to drivers without smart devices. We study time series analysis and artificial intelligence algorithms that collect and process pedestrian and vehicle information recognized by cameras and LIDAR. In the artificial intelligence traffic accident prevention system learned by deep learning, before entering the school zone, the school zone information is sent to the driver through the Force Push Service and the school zone information is delivered to the driver on the LED sign. try to reduce accidents.