• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3820-3841
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• 2018

Most of the accidents occur due to drowsiness while driving, avoiding road signs and due to driver's distraction. Driver's distraction depends on various factors which include talking with passengers while driving, mood disorder, nervousness, anger, over-excitement, anxiety, loud music, illness, fatigue and different driver's head rotations due to change in yaw, pitch and roll angle. The contribution of this paper is two-fold. Firstly, a data set is generated for conducting different experiments on driver's distraction. Secondly, novel approaches are presented that use features based on facial points; especially the features computed using motion vectors and interpolation to detect a special type of driver's distraction, i.e., driver's head rotation due to change in yaw angle. These facial points are detected by Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). Various types of classifiers are trained and tested on different frames to decide about a driver's distraction. These approaches are also scale invariant. The results show that the approach that uses the novel ideas of motion vectors and interpolation outperforms other approaches in detection of driver's head rotation. We are able to achieve a percentage accuracy of 98.45 using Neural Network.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.33 no.4
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• pp.297-306
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• 2007

Distraction osteogenesis was pioneered by Ilizarov in the treatment of injured extremities. Its subsequent application to Oral and Maxillofacial Surgery has opened a new chapter in the treatment of facial deformity. Careful monitoring of the period of distraction and consolidation of the callus is important and has been well described. Complications, such as infection, haematoma and premature ossification, are difficult to diagnose and can compromise the outcome after the surgery. Too slow rate of distraction results in premature fusion of cortices and too rapid information of bone 'cyst' within the callus distraction. I experienced 2 patients of congenital unilateral mandibular hypoplasia, so called Hemifacial Microsomia. After distraction surgery, I evaluated callus formation of mandibular distraction with Ultrasound Sonography during distraction and consolidation period. Plain radiography, although it enables accurate measurement of the distraction gap, did not give sufficient detail to allow assessment of early stages of bone formation, But, ultrasound monitoring could enable continuous monitoring of the distraction gap without exposure to ionizing radiation and allow detection of fine detail, which may influence manipulation of the callus.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.82-88
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• 2021

In this paper, we propose an automatic detection scheme of work distraction for remote management of telecommuting. The proposed scheme periodically captures two consequent computer screens and generates the difference image of these two captured images. The scheme applies the difference image to our deep learning model and makes a decision of abnormal patterns in the difference image. Our deep learning model is designed with the transfer learning technique of VGG16 deep learning. When the scheme detects an abnormal pattern in the difference image, it hides all texts in the difference images to protect disclosure of privacy-related information. Evaluation shows that the proposed scheme provides about 96% detection accuracy.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.33 no.4
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• pp.331-339
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• 2007

Background: Distraction osteogenesis(DO) is a useful method for treating cases demanding the generation of new bone. During DO, the angiogenic activity is crucial factor in the new bone formation. The aim of this study was to detect the autocrine growth activity in the cellular components of the distracted bone with observation of the co-expression of vascular endothelial growth factor(VEGF) and its receptors following the mandibular DO. Materials and methods: Unilateral mandibular distraction(0.5 mm twice per day for 10 days) was performed in six mongrel dogs. Two animals were killed at 7, 14, and 28 days after completion of distraction, respectively. Immediately after the animals were killed, the right mandibles were harvested en block. Immunohistochemical staining was processed for observation of the VEGF expression, and double immunofluorescent staining was also processed for detection of the co-expression of osteocalcin and VEGF's two distinct receptors(VEGFR-1 and VEGFR-2). Results: At 7 and 14 days after distraction, the expressions of VEGF were significantly increased in the osteogenic cells of the distracted bone. Up to 28 days after distraction, VEGF was still expressed moderate in the osteoblastic cells of distracted bone. The co-expressions of osteocalcin/VEGFR-1 and osteocalcin/VEGFR-2 were observed in the distracted bone at 7 and 14 days after distraction. In the double immunofluorescent staining, the co-expression' s level of osteocalcin/VEGFR-1 was more than that of osteocalcin/VEGFR-2. Conclusion: Taken together, this study suggested that VEGF plays an important role in the osteogenesis, and these osteoblastic cell-derived VEGF might act as autocrine growth factor during distraction osteogenesis. In the other word, the cellular components, such as osteoblasts and immature fibroblast-like cellsor mesenchymal cells in the distracted bone, might have autocrine growth activity during distraction osteogenesis.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.557-571
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• 2020

The existing methods for detection of fire smoke in a video easily lead to misjudgment of cloud, fog and moving distractors, such as a moving person, a moving vehicle and other non-smoke moving objects. Therefore, an algorithm for detection of fire smoke in a video based on wavelet energy slope fitting is proposed in this paper. The change in wavelet energy of the moving target foreground is used as the basis, and a time window of 40 continuous frames is set to fit the wavelet energy slope of the suspected area in every 20 frames, thus establishing a wavelet-energy-based smoke judgment criterion. The experimental data show that the algorithm described in this paper not only can detect smoke more quickly and more accurately, but also can effectively avoid the distraction of cloud, fog and moving object and prevent false alarm.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.31-37
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• 2018

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.15-29
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• 2018

This paper proposes an enhanced object tracking algorithm to compensate the lack of temporal information in existing particle swarm optimization based object trackers using the trajectory of the target object. The proposed scheme also enables the tracking and documentation of the location of an online updated set of distractions. Based on the trajectories information and the distraction set, a rule based approach with adaptive parameters is utilized for occlusion detection and determination of the target position. Compare to existing algorithms, the proposed approach provides more comprehensive use of available information and does not require manual adjustment of threshold values. Moreover, an effective weight adjustment function is proposed to alleviate the diversity loss and pre-mature convergence problem in particle swarm optimization. The proposed weight function ensures particles to search thoroughly in the frame before convergence to an optimum solution. In the existence of multiple objects with similar feature composition, this algorithm is tested to significantly reduce convergence to nearby distractions compared to the other existing swarm intelligence based object trackers.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.372-375
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• 2008

Drivers need to process dynamic stimulus in real - time with full attention from Telematics environment. However, as the information technology revolution brings more and more data into vehicles, all of it competing for the drivers' attention, the development of automated assistance for driver information processing becomes increasingly import ant. There for e, drivers' workload is very essential factor for safety driving in Telematics environment. In this paper, we have discussed driver distraction caused by driver conversation while driving and proposed voice activity detection algorithm for measuring driver workload. Finally, we show how voice activity detection system works for measuring driver workload.

• Physical Therapy Korea
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• v.3 no.2
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• pp.95-105
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• 1996

Type I, II, III are regarded as "true" joint receptors, type IV is considered a class of pain receptor. Type I, II and III mechanoreceptors, via static and dynamic input, signal joint position, intraarticular pressure changes, and the direction, amplitude, and velocity of joint movements. Type I mechanoreceptor subserve both static and dynamic physiologic functions. Type I are found primarily in the stratum fibrosum of the joint capsule and ligaments. Type I receptors have a low threshold for activation and are allow to adapt to changes altering their firing frequency. Type II receptors have a low threshold for activation. These dynamic receptors respond to joint movement. Type II receptors are thus termed rapidly adapting. Type II joint receptors are located at the junction of the synovial membrane and fibrosum of the joint capsule and intraarticular and extraarticular fat pads. Type III receptors have been found in collateral ligaments of the joints of the extremities. Morphologically similar to Golgi tendon organ. These dynamic receptors have a high threshold to stimulation and are slowly adating. Type IV receptors possess free nerve ending that have been found in joint capsule and fat pads. They are not normally active, but respond to extreme mechanical deformation of the joint as well as to direct chemical or mechanical irritation. Small amplitude oscillatory and distraction movements(joint mobilization) techniques are used to stimulate the mechanoreceptors that may inhibit the transmission of nociceptors stimuli at the spinal cord or brain stem levels.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.2 no.1
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• pp.9-19
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• 1996

Type I, II, III are regarded as "true" joint receptors, type IV is considered a class of pain receptor. Type I, II and III mechanoreceptors, via static and dynamic input, signal joint position, intraarticular pressure changes, and the direction, amplitude, and velocity of joint movements. Type I mechanoreceptor subserve both static and dynamic physiologic functions. Type I are found primarily in the stratum fibrosum of the joint capsule and ligaments. Type I receptors have a low threshold for activation and are allow to adapt to changes altering their firing frequency. Type II receptors have a low threshold for activation. These dynamic receptors respond to joint movement. Type II receptors are thus termed rapidly adapting. Type II joint receptors are located at the junction of the synovial membrane and fibrosum of the joint capsule and intraarticular and extraarticular fat pads. Type III receptors have been found in collateral ligaments of the joints of the extremities. Morphologically similar to Golgi tendon organ. These dynamic receptors have a high threshold to stimulation and are slowly adating. Type IV receptors possess free nerve ending that have been found in joint capsule and fat pads. They are not normally active, but respond to extreme mechanical deformation of the joint as well as to direct chemical or mechanical irritation. Small amplitude oscillatory and distraction movements(joint mobilization) techniques are used to stimulate the mechanoreceptors that may inhibit the transmission of nociceptors stimuli at the spinal cord or brain stem levels.