• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.81-87
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• 2006

In this paper, an experimental optical head tracker system is designed and constructed. The system is composed of the infrared LEDs and two infrared CCD cameras to filter out the interference of another light in the limited environment like the cockpit. Then the optical head tracker algorithm is designed by using the feature detection algorithm and the 3D motion estimation algorithm. The feature detection algorithm, used to obtain the 2D position coordinates of the features on the image plane, is implemented by using the thresholding and the masking techniques. The 3D motion estimation algorithm which estimates the motion of a pilot's head is implemented by using the extended Kalman filter (EKF). Also, we used the precise rate table to verify the performance of the experimental optical head tracker system and compared the rotational performance of this system with the inertial sensor.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.421-424
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• 1999

Automatic human face detection in a complex background is one of the difficult problems In this paper. we propose an effective automatic face detection system that can locate the face region in natural scene images when the system is used as a pre-processor of a face recog- nition system. We use two natural and powerful visual cues, the color and the human head shape. The outline of the human head can be generally described as being roughly elliptic in nature. In the first step of the proposed system, we have tried the approach of fitting the best Possible ellipse to the outline of the head In the next step, the method based on the human skin color space by selecting flesh tone regions in color images and histogramming their r(＝R/(R＋G＋B)) and g(＝G/R＋G＋B)) values. According to our experiment. the proposed system shows robust location results

• Journal of Mechanical Science and Technology
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• v.20 no.3
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• pp.426-434
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• 2006

The impact of leakage was incorporated into the transfer functions of the complex head and discharge. The impedance transfer functions for the various leaking pipeline systems were also derived. Hydraulic transients could be efficiently analyzed by the developed method. The simulation of normalized pressure variation using the method of characteristics and the impulse response method shows good agreement to the condition of turbulent flow. The leak calibration could be performed by incorporation of the impulse response method with Genetic Algorithm (GA) and Harmony Search (HS). The objective functions for the leakage detection can be made using the pressure-head response at the valve, or the pressure-head or the flow response at a certain point of the pipeline located upstream from the valve. The proposed method is not constrained by the Courant number to control the numerical dissipation of the method of characteristics. The limitations associated with the discreteness of the pipeline system in the inverse transient analysis can be neglected in the proposed method.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4223-4249
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• 2015

A novel jamming detection technique to detect the presence of jamming in the downstream direction for cluster based wireless sensor networks is proposed in this paper. The proposed technique is deployed in base station and in cluster heads. The proposed technique is novel in two aspects: Firstly, whenever a cluster head receives a packet it verifies whether the source node is legitimate node or new node. Secondly if a source node is declared as new node in the first step, then this technique observes the behavior of the new node to find whether the new node is legitimate node or jammed node. In order to monitor the behavior of the existing node and new node, the second step uses two metrics namely packet delivery ratio (PDR) and received signal strength indicator (RSSI). The rationality of using PDR and RSSI is presented by performing statistical test. PDR and RSSI of every member in the cluster is measured and assessed by the cluster head. And finally the cluster head determines whether the members of the cluster are jammed or not. The CH can detect the presence of jamming in the cluster at member level. The base station can detect the presence of jamming in the wireless sensor network at CH level. The simulation result shows that the proposed technique performs extremely well and achieves jamming detection rate as high as 99.85%.

• Journal of KIISE
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• v.44 no.8
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• pp.774-781
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• 2017

Mention detection systems use nouns or noun phrases as a head and construct a chunk of text that defines any meaning, including a modifier. The term "mention detection" relates to the extraction of mentions in a document. In the mentions, a coreference resolution pertains to finding out if various mentions have the same meaning to each other. A pointer network is a model based on a recurrent neural network (RNN) encoder-decoder, and outputs a list of elements that correspond to input sequence. In this paper, we propose the use of mention detection using pointer networks. Our proposed model can solve the problem of overlapped mention detection, an issue that could not be solved by sequence labeling when applying the pointer network to the mention detection. As a result of this experiment, performance of the proposed mention detection model showed an F1 of 80.07%, a 7.65%p higher than rule-based mention detection; a co-reference resolution performance using this mention detection model showed a CoNLL F1 of 52.67% (mention boundary), and a CoNLL F1 of 60.11% (head boundary) that is high, 7.68%p, or 1.5%p more than coreference resolution using rule-based mention detection.

• Korean Journal of Head & Neck Oncology
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• v.29 no.1
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• pp.26-28
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• 2013

Thyroid hemiagenesis is rare congenital anomaly that one lobe of thyroid fails to develop. It is often asymptomatic and discovered incidentally with other thyroid disease such as hypothyroidism, hyperthyroidism, multinodular goiter, benign adenoma and cancer. Most cases reported are left thyroid lobe agenesis and occurred in female. Compensatory hypertrophy occurs in most cases. Many cases are asymptomatic and detected incidentally, so awareness of its existence can help its detection and proper treatment. Here, we report a case of thyroid hemiagenesis accompanying hypothyroidism with a review of literature.

• Clinics in Shoulder and Elbow
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• v.18 no.2
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• pp.96-101
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• 2015

In general, the long head of the biceps brachii originates from the superior glenoid labrum and the supraglenoid tubercle, crosses the rotator cuff interval, and extends into the bicipital groove. However, rare anatomic variations of the origins of the long head have been reported in the past. In this report, we review the clinical history, radiologic findings, and arthroscopic identifications of 3 anatomic variants of the biceps tendon long head. As the detection of long head of biceps tendon pathology during preoperative radiologic assessment can be difficult without prior knowledge, surgeons should be aware of such possible anatomic variations.

• Korean Journal of Head & Neck Oncology
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• v.3 no.1
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• pp.5-13
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• 1987

Cancer of the head and neck is an uncommon disease accounting for 5 % of all cancers. In an anatomic area so readily visible and palpable for examination without special and expensive diagnositic tools, it is unfortunate that many patients still present with advanced diseases. Since the prognosis is so intimately related to stage of disease, it is very important to detect the earliest stage of cancer with a complete head and neck examination. In the evaluation of cancer at any anatomic site, the description of the extent of the lesion is important. Not only does proper staging of the tumor lead to make decision of the most appropriate treatment, it also serves as a guide for the results of treatment. Proper staging demands a careful clinical assesment of the extent of the cancer. The current staging system for head and neck cancer uses the TNM system devised by American Joint Committee for Cancer Staging and End Result Reporting. T represent the primary tumor, N, regional nodal metastases, and M, distant metastases. The detection, diagnosis, and appropriate treatment of eary cancer will result in improved survival.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.5
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• pp.9-14
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• 2014

Recently, various contents using human motion are developed in computer vision and game industries. If we try to apply human motion to application programs and contents, users can experience a sense of immersion getting into it so that the users feel a high level of satisfaction from the contents. In this research, we analyze human head motion using images captured from an webcam and then we apply the result of motion recognition to a game without special devices as an interface. The proposed method, first, segments human head region using an image composed of MHI(Motion History Image) and the result of skin color detection, and then we calculate the direction and distance by the MHI sequence. In experiments, the proposed method for human head motion recognition was tested for controlling a game player. From the experimental results we proved that the proposed method can make a gammer feel more immersed into the game. Furthermore, we expect the proposed method can be an interface of a serious game for medical or rehabilitation purposes.