• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.282-285
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• 2009

Nanostructured OLED light extraction films have been made via roll-to-roll coating processes. Their on-axis and integrated outcoupling efficiencies reach 2X and 1.3-1.8X, respectively. Optical performance and effects of the nanostructured film on pixel blur and image ghosting will be discussed.

• Ocean Systems Engineering
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• v.7 no.2
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• pp.157-177
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• 2017

This research is based on the concept of safety airbag to design a self-rescue system for the autonomous underwater vehicle (AUV) using micro inertial sensing module. To reduce the possibility of losing the underwater vehicle and the difficulty of searching and rescuing, when the AUV self-rescue system (ASRS) detects that the AUV is crashing or encountering a serious collision, it can pump carbon dioxide into the airbag immediately to make the vehicle surface. ASRS consists of 10-DOF sensing module, sensing attitude algorithm and air-pumping mechanism. The attitude sensing modules are a nine-axis micro-inertial sensor and a barometer. The sensing attitude algorithm is designed to estimate failure attitude of AUV properly using sensor calibration and extended Kalman filter (SCEKF), feature extraction and backpropagation network (BPN) classify. SCEKF is proposed to be used subsequently to calibrate and fuse the data from the micro-inertial sensors. Feature extraction and BPN training algorithms for classification are used to determine the activity malfunction of AUV. When the accident of AUV occurred, the ASRS will immediately be initiated; the airbag is soon filled, and the AUV will surface due to the buoyancy. In the future, ASRS will be developed successfully to solve the problems such as the high losing rate and the high difficulty of the rescuing mission of AUV.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.181-184
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• 2000

The new method of feature extraction is proposed, considering the statistic feature of human voice, unlike the conventional methods of voice extraction. PCA(principal Component Analysis) is applied to this new method. PCA removes the repeating of data after finding the axis direction which has the greatest variance in input dimension. Then the new method is applied to real voice recognition to assess performance. When results of the number recognition in this paper and the conventional Mel-Cepstrum of voice feature parameter are compared, there is 0.5% difference of recognition rate. Better recognition rate is expected than word or sentence recognition in that less convergence time than the conventional method in extracting voice feature. Also, better recognition tate is expected when the optimum vector is used by statistic feature of data.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.474-486
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• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.461-469
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• 2020

In this paper, we propose a PCA-based feature feedback method for extracting important areas of handwritten numeric data sets and face data sets. A PCA-based feature feedback method is proposed by extending the previous LDA-based feature feedback method. In the proposed method, the data is reduced to important feature dimensions by applying the PCA technique, one of the dimension reduction machine learning algorithms. Through the weights derived during the dimensional reduction process, the important points of data in each reduced dimensional axis are identified. Each dimension axis has a different weight in the total data according to the size of the eigenvalue of the axis. Accordingly, a weight proportional to the size of the eigenvalues of each dimension axis is given, and an operation process is performed to add important points of data in each dimension axis. The critical area of the data is calculated by applying a threshold to the data obtained through the calculation process. After that, induces reverse mapping to the original data in the important area of the derived data, and selects the important area in the original data space. The results of the experiment on the MNIST dataset are checked, and the effectiveness and possibility of the pattern recognition method based on PCA-based feature feedback are verified by comparing the results with the existing LDA-based feature feedback method.

• The korean journal of orthodontics
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• v.46 no.4
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• pp.242-252
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• 2016

Objective: Orthodontic mini-implants (OMI) generate various horizontal and vertical force vectors and moments according to their insertion positions. This study aimed to help select ideal biomechanics during maxillary incisor retraction by varying the length in the anterior retraction hook (ARH) and OMI position. Methods: Two extraction models were constructed to analyze the three-dimentional finite element: a first premolar extraction model (Model 1, M1) and a residual 1-mm space post-extraction model (Model 2, M2). The OMI position was set at a height of 8 mm from the arch wire between the second maxillary premolar and the first molar (low OMI traction) or at a 12-mm height in the mesial second maxillary premolar (high OMI traction). Retraction force vectors of 200 g from the ARH (-1, +1, +3, and +6 mm) at low or high OMI traction were resolved into X-, Y-, and Z-axis components. Results: In M1 (low and high OMI traction) and M2 (low OMI traction), the maxillary incisor tip was extruded, but the apex was intruded, and the occlusal plane was rotated clockwise. Significant intrusion and counter-clockwise rotation in the occlusal plane were observed under high OMI traction and -1 mm ARH in M2. Conclusions: This study observed orthodontic tooth movement according to the OMI position and ARH height, and M2 under high OMI traction with short ARH showed retraction with maxillary incisor intrusion.

• The korean journal of orthodontics
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• v.52 no.1
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• pp.42-52
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• 2022

Objective: This study compared soft tissue changes after extraction of the four premolars followed by maximum retraction of the anterior teeth according to the type of anterior teeth movement: tipping and translation. Methods: Patients who had undergone orthodontic treatment involving the extraction of four premolars were retrospectively selected and divided into either the tipping (n = 27) or translation (n = 26) groups based on the retraction of the incisor root apex and the axis changes of the incisors during the treatment period. Lateral pre- and post-treatment cephalograms were analyzed. Results: There were no significant differences between the tipping and translation groups before treatment. The retraction amounts of the root apex of the upper and lower incisors in the tipping group were 0.33 and 0.26 mm, respectively, and 5.02 and 5.31 mm, respectively, in the translation group (p < 0.001). The posterior movements of soft tissue points A and B in the tipping group were 0.61 and 1.25 mm, respectively, and 1.10 and 3.25 mm, respectively, in the translation group (p < 0.01). The mentolabial sulcus angle increased by 5.89° in the tipping group, whereas it decreased by 8.13° in the translation group (p < 0.001). Conclusions: An increased amount of retraction of the incisor root apex led to the increased posterior movement of soft tissue points A and B, and this appeared more distinct in cases involving the lower incisor and lower lip.

• Journal of Periodontal and Implant Science
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• v.25 no.3
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• pp.557-567
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• 1995

The purpose of this study was to investigated the effect of root planing and decalcified freeze dried allografts on the resorption of transplanted roots and the healing of preveously diseased recipient extraction sockets. The experimental chronic periodontitis was induced by elastic ligatures on the 2nd and 3rd mandibular premolars of 4 adult dogs, and after 8 weeks, crowns were removed and the teeth extracted. The extracted roots were split in half along the long-axis, and the extednt of plaque exposure was morked on the root surfaces with burs. The roots were either root-planed(Test group), or left uninstrumented(Control group), and transplanted in the extraction sockets with decalcified freeze-dried allografts filling the void. The flaps were sutured to cover the sockets completely. The animals were sacrificed after 12 weeks of healing, and the specimens were examined histologically. The results were as follows : 1. No signs of inflammation or disease activity were observed in either groups. 2. Replacement root resorption was observed in both groups. 3. More connective tissue attachments and less ankylosis were observed in the test groups compared to the control. 4. The unresorbed remains of DFDB particles were observed in both groups. 5. DFDB particles in the apical portion of the alveolar sockets were encased in newly-formed bone, while those in the coronal areas were seen encapsulated with connective tissue. 6. No significant difference was found between root-planed and uninstrumented roots relative to the healing and the bone fromation in the recipient extraction sockdets. From the present study, there seemed to be no significant benefits in root planing the transplanted roots or grafting the sockets with DFDB in order to curve the replacement resorption, although the root-planed roots showed more connective tissue attachments. There was also no significant benefits in root transplantation and DFDB for and enhanced healing and bone formation in alveolar extraction sockets.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.155-158
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• 2004

This paper describes a lane following control of vision based mobile robot that follows guidline. Summation of binarization conversion and image data of vertical axis was used in image processing. As an extraction of specific parameters of lane image, the raw image was converted to the binary data, and the binary data was summerized to the specific data vertically. The specific parameters were made to the inputs of neural network. Summation of image data was used for input of the net, and optimized value of turn angles of learned mobile robot was output. By using neural network algorithm, possibility of mobile robot moving to the target point and following the guidlines quickly and effectively was proved.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.81-87
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• 2006

This paper describes a method for extracting surfaces from multi-material CT (Computed Tomography) data. Most contouring methods such as Marching Cubes algorithm assume that CT data are composed of only two materials. Some extended methods such as [3, 6] can extract surfaces from the multi-material (non-manifold) implicit representation. However, these methods are not directly applicable to CT data that are composed of three or more materials. There are two major problems that arise from fundamentals of CT. The first problem is that we have to use n(n-1)/2 threshold values for CT data contains n materials and select appropriately one threshold value for each boundary area. The second is that we cannot reconstruct only from CT data in which area three or more materials are adjacent each other. In this paper, we propose a method to solve the problems by using image analysis and demonstrate the effectiveness of the method with application examples construct polygon models from CT data of machine parts.