• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.49 no.3
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• pp.125-134
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• 2023

Objectives: The aim of the study was to quantify and compare craniofacial asymmetry in subjects with and without symptoms of temporomandibular joint disorders (TMDs). Materials and Methods: A total of 126 adult subjects were categorized into two groups (63 with a TMDs and 63 without a TMDs), based on detection of symptoms using the Temporomandibular Joint Disorder-Diagnostic Index (TMD-DI) questionnaire. Posteroanterior cephalograms of each subject were traced manually and 17 linear and angular measurements were analyzed. Craniofacial asymmetry was quantified by calculating the asymmetry index (AI) of bilateral parameters for both groups. Results: Intra- and intergroup comparisons were analyzed using independent t-test and Mann-Whitney U test, respectively, with a P<0.05 considered statistically significant. An AI for each linear and angular bilateral parameter was calculated; higher asymmetry was found in TMD-positive patients compared with TMD-negative patients. An intergroup comparison of AIs found highly significant differences for the parameters of antegonial notch to horizontal plane distance, jugular point to horizontal plane distance, antegonial notch to menton distance, antegonial notch to vertical plane distance, condylion to vertical plane distance, and angle formed by vertical plane, O point and antegonial notch. Significant deviation of the menton distance from the facial midline was also evident. Conclusion: Greater facial asymmetry was seen in the TMD-positive group compared with the TMD-negative group. The mandibular region was characterized by asymmetries of greater magnitude compared with the maxilla. Patients with facial asymmetry often require management of temporomandibular joint (TMJ) pathology to achieve a stable, functional, and esthetic result. Ignoring the TMJ during treatment or failing to provide proper management of the TMJ and performing only orthognathic surgery may result in worsening of TMJ-associated symptoms (jaw dysfunction and pain) and re-occurrence of asymmetry and malocclusion. Assessments of facial asymmetry should take into account TMJ disorders to improve diagnostic accuracy and treatment outcomes.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.638-642
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• 2005

For gas hydrate exploration, long offset multichannel seismic data acquired using by the 4km streamer length in Ulleung basin of the East Sea. The dataset was processed to define the BSRs (Bottom Simulating Reflectors) and to estimate the amount of gas hydrates. Confirmation of the presence of Bottom Simulating reflectors (BSR) and investigation of its physical properties from seismic section are important for gas hydrate detection. Specially, faster interval velocity overlying slower interval velocity indicates the likely presences of gas hydrate above BSR and free gas underneath BSR. In consequence, estimation of correct interval velocities and analysis of their spatial variations are critical processes for gas hydrate detection using seismic reflection data. Using Dix's equation, Root Mean Square (RMS) velocities can be converted into interval velocities. However, it is not a proper way to investigate interval velocities above and below BSR considering the fact that RMS velocities have poor resolution and correctness and the assumption that interval velocities increase along the depth. Therefore, we incorporated Migration Velocity Analysis (MVA) software produced by Landmark CO. to estimate correct interval velocities in detail. MVA is a process to yield velocities of sediments between layers using Common Mid Point (CMP) gathered seismic data. The CMP gathered data for MVA should be produced after basic processing steps to enhance the signal to noise ratio of the first reflections. Prestack depth migrated section is produced using interval velocities and interval velocities are key parameters governing qualities of prestack depth migration section. Correctness of interval velocities can be examined by the presence of Residual Move Out (RMO) on CMP gathered data. If there is no RMO, peaks of primary reflection events are flat in horizontal direction for all offsets of Common Reflection Point (CRP) gathers and it proves that prestack depth migration is done with correct velocity field. Used method in this study, Tomographic inversion needs two initial input data. One is the dataset obtained from the results of preprocessing by removing multiples and noise and stacked partially. The other is the depth domain velocity model build by smoothing and editing the interval velocity converted from RMS velocity. After the three times iteration of tomography inversion, Optimum interval velocity field can be fixed. The conclusion of this study as follow, the final Interval velocity around the BSR decreased to 1400 m/s from 2500 m/s abruptly. BSR is showed about 200m depth under the seabottom

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.829-837
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• 2014

The KOMPSAT-3 can acquire panchromatic stereo image with 0.7 m spatial resolution, and provides Rational Polynomial Coefficient (RPC). In order to determine ground coordinate using the provides RPC, which include interior-exterior orientation errors, its adjustment is needed by using the Ground Control Point (GCP). Several thousands of national Unified Control Points (UCPs) are established and overall distributed in the country by the Korean National Geographic Information Institute (NGII). UCPs therefore can be easily searched and downloaded by the national-control-point-record-issues system. This paper introduced the point-extraction method and the distance-bearing method to detect of UCPs. As results, the distance-bearing method was better detected through the experiment. RPC adjustment using this method was compared with that by only one UCP and GCPs using GPS. The proposed method was more accurate than the other method in the horizontal. As demonstrated in this paper, the proposed UCPs detection method could be replaced GPS surveying for RPC adjustment.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.323-330
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• 2009

The objective of this research was to develop a practical integrated approach using extracted features from electrical resistance measurements and coupled electromechanical models of damage, for in-situ damage detection and sensing in carbon fiber reinforced plastic(CFRP) composites. To achieve this objective, we introduced specific known damage (in terms of type, size, and location) into CFRP laminates and established quantitative relationships with the electrical resistance measurements. For processing of numerous measurement data, an autonomous data acquisition system was devised. We also established a specimen preparation procedure and a method for electrode setup. Coupon and panel CFRP laminate specimens with several known damage were tested. Coupon specimens with various sizes of artificial delaminations obtained by inserting Teflon film were manufactured and the resistance was measured. The measurement results showed that increase of delamination size led to increase of resistance implying that it is possible to sense the existence and size of delamination. A quasi-isotropic panel was manufactured and electrical resistance was measured. Then three different sizes of holes were drilled at a chosen location. The panel was prepared using the established procedures with six electrode connections on each side making a total of twenty-four electrodes. Vertical, horizontal, and diagonal pairs of electrodes were chosen and the resistance was measured. The measurement results showed the possibility of the established measurement system for an in-situ damage detection method for CFRP composite structures.

• Journal of the Korean Geophysical Society
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• v.1 no.1
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• pp.59-68
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• 1998

Ground penetrating radar (GPR) experiments were performed in a sand tank to study the ability of detection of buried pipes and to characterize the signal of the reflection wave. The ratios of diameter of buried pipes to the depth were set 4 up to 24 % and materials were metal, synthetic resin, and wood. In case of groundwater table below buried materials, strong reflection signals were observed irrespective of diameter and depth except for wood. While it is very difficult to detect the reflection signals in case that the groundwater table is set to higher than buried materials. The reflection signals from the bottom of the sand tank, however, were clearly observed even in case of higher groundwater table. This implies that the weak reflection signals from the buried materials are not all due to the wave attenuation. The vertical reflection profiling method is recommended in case that the object of the survey is to find horizontal position of buried material because this method has the advantage in cost and time of survey. However, the full or partial CMP gather method is recommended in case that the objects of the survey are to get the detailed subsurface information, i.e. the depth to buried material, interval velocity of geological layer, and mapping the groundwater table.

• Korean Chemical Engineering Research
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• v.49 no.2
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• pp.224-229
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• 2011

In this study, we have developed shear horizontal(SH) surface acoustic wave(SAW) sensors for the detection of immunoglobulin G(IgG) on the gold coated delay line of SH-SAW devices. As the result of the experiment, we could uniformly immobilize anti-MIgG(mouse IgG) conjugate on the surface of gold. When displaying results of immobilization on the surface of gold using G-anti MIgG conjugate and blocking buffer in frequency shift, G-anti MIgG conjugate showed frequency shift of 75.1 kHz in the initial frequency, and blocking buffer showed frequency shift of 215.7 kHz. When various concentrations of MIgG was added in 100MHz type sensor, the sensor showed 46.3, 127.45, 161.21 and 262.39 kHz frequency shift at 25, 50, 75 and 100 ${\mu}g$ MIgG concentration, respectively.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.88-100
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• 1999

Detecting human face and facial landmarks automatically in an image is as essential step to a fully automatic face recognition system. In this paper, we present a new approach to detect automatically face and its eyes of input image with scale and rotation variations of faces by using an intensity based template matching with a single log-polar face template. In a template-based matching it is necessary to normalize the scale changes and rotations of an input image to a template ones. The log-polar mapping which simulates space-variant human visual system converts scale changes and rotations of input image into constant horizontal and cyclic vertical shifts in the output plane. Intelligent use of this property allows us to shift of the candidate log-polar faces mapped at various fixation points of an input image to be matched to a template over the log-polar plane. Thus, the proposed method eliminates the need of adapting multitemplate and multiresolution schemes, which inevitably give rise to intensive computation involved to cope with scale and rotation variations of faces. Through this scale and rotation involved to cope with scale and method can lead to detecting face and its eyes simultaneously. Experimental results on a database of 795 images show over 98% detection rate.

• Journal of International Society for Simulation Surgery
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• v.2 no.1
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• pp.26-32
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• 2015

Purpose When a surgeon examines the morphology of skull of patient, locations of craniometric landmarks of 3D computed tomography(CT) volume are one of the most important information for surgical purpose. The locations of craniometric landmarks can be found manually by surgeon from the 3D rendered volume or 2D sagittal, axial, and coronal slices which are taken by CT. Since there are many landmarks on the skull, finding these manually is time-consuming, exhaustive, and occasionally inexact. These inefficiencies raise a demand for a automatic localization technique for craniometric landmark points. So in this paper, we propose a novel method through which we can automatically find these landmark points, which are useful for surgical purpose. Materials and Methods At first, we align the experimental data (CT volumes) using Frankfurt Horizontal Plane (FHP) and Mid Sagittal Plane(MSP) which are defined by 3 and 2 cranial landmark points each. The target landmark of our experiment is the anterior nasal spine. Prior to constructing a statistical cubic model which would be used for detecting the location of the landmark from a given CT volume, reference points for the anterior nasal spine were manually chosen by a surgeon from several CT volume sets. The statistical cubic model is constructed by calculating weighted intensity means of these CT sets around the reference points. By finding the location where similarity function (squared difference function) has the minimal value with this model, the location of the landmark can be found from any given CT volume. Results In this paper, we used 5 CT volumes to construct the statistical cubic model. The 20 CT volumes including the volumes, which were used to construct the model, were used for testing. The range of age of subjects is up to 2 years (24 months) old. The found points of each data are almost close to the reference point which were manually chosen by surgeon. Also it has been seen that the similarity function always has the global minimum at the detection point. Conclusion Through the experiment, we have seen the proposed method shows the outstanding performance in searching the landmark point. This algorithm would make surgeons efficiently work with morphological informations of skull. We also expect the potential of our algorithm for searching the anatomic landmarks not only cranial landmarks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1380-1386
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• 2007

This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is blacker white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tacking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm. Experiments using real images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.439-448
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• 2021

Driver negligence accounts for the largest proportion of the causes of traffic accidents, and research to detect them is continuously being conducted. This paper proposes a method to accurately detect a distracted driver and localize the most characteristic parts of the driver. The proposed method hierarchically constructs a CNN basic model that classifies 10 classes based on CAM in order to detect driver distration and 4 subclass models for detailed classification of classes having a confusing or common feature area in this model. The classification result output from each model can be considered as a new feature indicating the degree of matching with the CNN feature maps, and the accuracy of classification is improved by horizontally combining and learning them. In addition, by combining the heat map results reflecting the classification results of the basic and detailed classification models, the characteristic areas of attention in the image are found. The proposed method obtained an accuracy of 95.14% in an experiment using the State Farm data set, which is 2.94% higher than the 92.2%, which is the highest accuracy among the results using this data set. Also, it was confirmed by the experiment that more meaningful and accurate attention areas were found than the results of the attention area found when only the basic model was used.