• Journal of Trauma and Injury
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• v.31 no.3
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• pp.151-158
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• 2018

Purpose: The regional emergency medical centers manage the patients with major blunt trauma according to the process appropriate to each hospital rather than standardized protocol of the major trauma centers. The primary purpose of this study is to evaluate the effectiveness and influence on prognosis of additional cervical-thoracic-lumbar-spine computed tomography (CTL-spine CT) scan in diagnosis of spinal injury from the victim of major blunt trauma with impaired consciousness. Methods: The study included patients visited the urban emergency medical center with major blunt trauma who were over 18 years of age from January 2013 to December 2016. Data were collected from retrospective review of medical records. Sensitivity, specificity, positive predictive value, and negative predictive value were measured for evaluation of the performance of diagnostic methods. Results: One hundred patients with Glasgow coma scale ${\leq}13$ underwent additional CTL-spine CT scan. Mechanism of injury was in the following order: driver, pedestrian traffic accident, fall and passenger accident. Thirty-one patients were diagnosed of spinal injury, six of them underwent surgical management. The sensitivity of chest, abdomen and pelvis CT (CAP CT) was 72%, specificity 97%, false positive rate 3%, false negative rate 28% and diagnostic accuracy 87%. Eleven patients were not diagnosed of spinal injury with CAP CT and C-spine lateral view, but all of them were diagnosed of stable fractures. Conclusions: C-spine CT scan be actively considered in the initial examination process. When CAP CT scan is performed in major blunt trauma patients with impaired consciousness, CTL-spine CT scan or simple spinal radiography has no significant effect on the prognosis of the patient and can be performed if necessary.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.284-288
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• 2021

Human-computer interaction is a discipline concerned with the design, evaluation, and implementation of interactive systems for human use. In this paper we suggest designing a smart deaf emergency application based on Human-Computer Interaction (HCI) principles whereas nowadays everything around us is becoming smart, People already have smartphones, smartwatches, smart cars, smart houses, and many other technologies that offer a wide range of useful options. So, a smart mobile application using Text Telephone or TeleTYpe technology (TTY) has been proposed to help people with deafness or impaired hearing to communicate and seek help in emergencies. Deaf people find it difficult to communicate with people, especially in emergency status. It is stipulated that deaf people In all societies must have equal rights to use emergency services as other people. With the proposed application the deafness or impaired hearing can request help with one touch, and the location will be determined, also the user status will be sent to the emergency services through the application, making it easier to reach them and provide them with assistance. The application contains several classifications and emergency status (traffic, police, road safety, ambulance, fire fighting). The expected results from this design are interactive, experiential, efficient, and comprehensive features of human-computer interactive technology which may achieve user satisfaction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.388-390
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• 2021

This paper introduces a system that can help visually impaired people to board a bus using an embedded board with keypad, dot matrix, lidar sensor, NFC reader, a public data portal Open API system, and deep learning algorithm (YOLOv5). The user inputs the desired bus number through the NFC reader and keypad, and then obtains the location and expected arrival time information of the bus through the Open API real-time data through the voice output entered into the system. In addition, by displaying the bus number as the dot matrix, it can help the bus driver to wait for the visually impaired, and at the same time, a deep learning algorithm (YOLOv5) recognizes the bus number that stops in real time and detects the distance to the bus with a distance detection sensor such as lidar sensor.

• 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.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.1
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• pp.17-21
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• 2015

There have been sustained developments of advanced technologies using traffic safety facilities recently and techniques for identifying failure modes and devices which could result in fatal outcomes. The purpose of this research is aimed at improving the driving conditions in advance through analyzing the IT convergence, driving education, researches for vehicles, field of construction and robotics. The researchers evaluate on usability tests of the driving with 26 candidates through focusing on safety, convenience, efficiency, effectiveness. Using specialized LED panel to enhance driving performances of disabled people are for cautious road conditions like foggy weather or heavy rain. As a result, there were improvements in the driving conditions, and candidates reported this system was helpful. It allows them for maintaining proper driving all times and was especially informative for people with low vision or visually impaired. This system plays a pivotal role as a prevention mechanism not only for regular drivers but also for further delict of traffic violations or accident offenders who already have former record on tort.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.41-47
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• 2019

In this study, a smart assistive device is designed to recognize pedestrian signal and to provide audio instructions for visually impaired people in crossing streets safely. Walking alone is one of the biggest challenges to the visually impaired and it deteriorates their life quality. The proposed device has a camera attached on a pair of glasses which can detect traffic lights, recognize pedestrian signals in real-time using a machine learning algorithm on GPU board and provide audio instructions to the user. For the portability, the dimension of the device is designed to be compact and light but with sufficient battery life. The embedded processor of device is wired to the small camera which is attached on a pair of glasses. Also, on inner part of the leg of the glasses, a bone-conduction speaker is installed which can give audio instructions without blocking external sounds for safety reason. The performance of the proposed device was validated with experiments and it showed 87.0% recall and 100% precision for detecting pedestrian green light, and 94.4% recall and 97.1% precision for detecting pedestrian red light.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.149-156
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• 2011

Considerable evaluation is needed to design a new longitudinal tunnel in advance because it damaged drivers' driving safety and heightened the possibility of traffic accidents with its physical characteristics. Specifically, considering traffic psychological and ergonomic factors was very important to prevent the difficulty of maintaining safe speed, the increase of the drowsy driving, the fatality of traffic accidents, and subjective feelings such as anxiety while driving a car through the tunnel, from design to construction. This study dealt with driving safety evaluation of an original road alignment design for the longitudinal tunnel (length: above 10km) with a driving simulator, and helped us to improve an original road alignment design and make an alternative road alignment design with presenting risky districts. The results of experiment showed that inflection points were revealed more risky districts, because they impaired driving safety and elevated driver workload while driving a car through around the inflection points of two-way route. Finally, the limitations and implications of this study were discussed.

• Journal of the Korea Institute of Building Construction
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• v.20 no.4
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• pp.375-382
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• 2020

Rock drop obstacles on major roads in the border area in South Korea has been installed and operated to prevent and block the movement of enemy units. However, the increase in traffic volume due to the development of the border region causes many problems such as road traffic congestion due to rock drop, traffic safety, and impaired urban aesthetics. Therefore, this study aimed to provide guidelines for demolition and replacement facility installation for rock drop obstacles, which are differently applied to each unit, and to suggest the direction of the Ministry of National Defense's policy regarding maintenance cost for necessary rock drop obstacles required for operation. In this study, as part of a guideline study on the removal of rock drop obstacles and the installation of alternative facilities, a standard unit price was suggested for essential rock drop obstacles, so as to be used as judgment data when deciding whether to remove rock drop obstacles.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.1-10
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• 2024

Individuals with visual impairments face numerous challenges in their daily lives, with navigating streets and public spaces being particularly daunting. The inability to identify safe crossing locations and assess the feasibility of crossing significantly restricts their mobility and independence. Globally, an estimated 285 million people suffer from visual impairment, with 39 million categorized as blind and 246 million as visually impaired, according to the World Health Organization. In Saudi Arabia alone, there are approximately 159 thousand blind individuals, as per unofficial statistics. The profound impact of visual impairments on daily activities underscores the urgent need for solutions to improve mobility and enhance safety. This study aims to address this pressing issue by leveraging computer vision and deep learning techniques to enhance object detection capabilities. Two models were trained to detect objects: one focused on street crossing obstacles, and the other aimed to search for objects. The first model was trained on a dataset comprising 5283 images of road obstacles and traffic signals, annotated to create a labeled dataset. Subsequently, it was trained using the YOLOv8 and YOLOv5 models, with YOLOv5 achieving a satisfactory accuracy of 84%. The second model was trained on the COCO dataset using YOLOv5, yielding an impressive accuracy of 94%. By improving object detection capabilities through advanced technology, this research seeks to empower individuals with visual impairments, enhancing their mobility, independence, and overall quality of life.

• Journal of the Korea Institute of Construction Safety
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• v.2 no.2
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• pp.56-62
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• 2019

As of 2015, the number of handicapped people accounted for 26 percent of the total population and the number has been increasing every year. There are many restrictions on transportation, especially for visually impaired and wheelchair users, from existing buildings to other buildings. This study takes note of this and develops algorithms for producing applications for the direction of traffic for people who are blind and wheelchair users The algorithms developed through this study take into account stairs, thresholds and widths for wheelchair users, while guiding elevators and ramps first and supporting all guidance, including obstacles, by voice for the blind. This study is judged to contribute greatly to the development of applications for the actual traffic infirm in the future.