• Imaging Science in Dentistry
• /
• v.39 no.3
• /
• pp.109-113
• /
• 2009

Purpose : The purpose of this study was to examine the inferior expansion of the maxillary sinus floor following maxillary molar extraction. Materials and Methods : Cone beam computed tomographic images of 59 subjects were used to evaluate the height difference of the maxillary sinus floor between extraction sites and contralateral dentate sites. The height of the maxillary sinus floor was defined as the vertical distance to the Frankfort plane from the level of the anterior nasal spine to the most inferior point of the sinus floor. We examined the difference in sinus pneumatization according to the number of missing teeth and the vertical relationship of the molar roots to the sinus floor. Results : The inferior expansion of the maxillary sinus floor was $1.20{\pm}1.86\;mm$ on the maxillary first molar and $1.90{\pm}2.42\;mm$ on the maxillary second molar. Increased expansion was observed in cases where two proximate molars were extracted. There was no significant difference in sinus pneumatization following extraction according to the vertical relationship of the molar roots to the sinus floor. Conclusion : The results of this study confirm that sinus pneumatization occurs following maxillary molar extraction. In situations where pneumatization can affect treatment after molar extraction, three-dimensional radiography should be considered.

• Korean Journal of Food Science and Technology
• /
• v.24 no.2
• /
• pp.137-141
• /
• 1992

To investigate some factors on oleoresin extraction from red pepper, the content of yield, capsanthin and capsaicin in oleoresin extracted under various factors such as solvent, variety of materials, extraction time and temperature, storage condition of dried red pepper and its parts, particle size of raw material powder and the ratios of red pepper powder to extraction solvent were investigated. Ethyl alcohol and ethylene dichloride were effective in extracting capsanthin and capsaicin from red pepper, respectively. Mixed-solvent bore fruitful in increasing of oleoresin yield, but was fruitless in extracting capsanthin and capsaicin in comparison with single-solvent. In three varieties such as Juktoma, Jinsol and Dabok, Jinsol was excellent in oleoresin extraction. Optimum extracting temperature and time was $20^{\circ}C$ and three to five hours, respectively. Oleoresin quality from long-term storage and/or coarse red pepper were low in point of yield, capsanthin and capsaicin. Capsanthin and capsaicin were distributed into pericarp and seed in abundance, respectively. Optimum mixing ratio of red pepper powder to extracting solvent was suitable for one to three(1 : 3) or one to four(1 : 4) in oleoresin extraction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.1
• /
• pp.1-9
• /
• 2020

ABL (Airborne Bathymetric LiDAR) is an advanced survey technology that uses green lasers to simultaneously measure the water depths and oceanic topography in coastal and river areas. Seabed point cloud extraction is an essential prerequisite to further utilizing the ABL data for various geographic data processing and applications. Conventional seabed detection approaches often use return waveforms. However, their limited accessibility often limits the broad use of the bathymetric LiDAR (Light Detection And Ranging) data. Further, it is often questioned if the waveform-based seabed extraction is reliable enough to extract seabed. Therefore, there is a high demand to extract seabed from the point cloud using other sources of information, such as geometric information. This study aimed to assess the feasibility of a ground filtering method to seabed extraction from geo-referenced point cloud data by using CSF (Cloth Simulation Filtering) method. We conducted a preliminary experiment with the RIGEL VQ 880 bathymetric data, and the results show that the CSF algorithm can be effectively applied to the seabed point segmentation.

• Smart Structures and Systems
• /
• v.30 no.5
• /
• pp.501-511
• /
• 2022

Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.

• Proceedings of the KOSOMBE Conference
• /
• v.1990 no.05
• /
• pp.21-24
• /
• 1990

This paper presents a new algorithm for P-wave detection in the ECG signal, we get the peak, onset and offset point by using significant point extraction algorithm with 5-point derivative. To these set of extracted significant points, we apply amplitude and duration threshold criterion. we define the set of significant point meeting the criterion as P-wave candidate. Then P-wave candidate is classified through match-process with template. The template with maximum number or P-wave candidate is selected to be the P-wave.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.96-99
• /
• 2003

Land cover map is a typical GIS database which shows the Earth's physical surface differentiated by standardized homogeneous land cover types. Satellite images acquired by Landsat TM were primarily used to produce a land cover map of 7 land cover classes; however, it now becomes to produce a more accurate land cover classification dataset of 23 classes thanks to higher resolution satellite images, such as SPOT-5 and IKONOS. The use of the newly produced high resolution land cover map of 23 classes for such activities to estimate non-point sources of pollution like water pollution modeling and atmospheric dispersion modeling is expected to result a higher level of accuracy and validity in various environmental monitoring results. The estimation of pollution from non-point sources using GIS-based modeling with land cover dataset shows fairly accurate and consistent results.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.27 no.1
• /
• pp.37-55
• /
• 2023

In this paper we propose a new algorithm for detecting and counting flowers in a complex background based on digital images. The algorithm mainly includes the following parts: edge contour extraction of flowers, edge contour determination of overlapped flowers and flower counting. We use a contour detection technique in Computer Vision (CV) to extract the edge contours of flowers and propose an improved algorithm with a concave point detection technique to find accurate segmentation for overlapped flowers. In this process, we first use the polygon approximation to smooth edge contours and then adopt the second-order central moments to fit ellipse contours to determine whether edge contours overlap. To obtain accurate segmentation points, we calculate the curvature of each pixel point on the edge contours with an improved Curvature Scale Space (CSS) corner detector. Finally, we successively give three adaptive judgment criteria to detect and count flowers accurately and automatically. Both experimental results and the proposed evaluation indicators reveal that the proposed algorithm is more efficient for flower counting.

• Fibers and Polymers
• /
• v.4 no.1
• /
• pp.27-31
• /
• 2003

A major concern in solvent extraction process is the loss of extractant into the aqueous phase due to its slight solubility in the aqueous phase. Similarly, in membrane extraction processes, extractant loss through extractant leakage from the membrane into the aqueous phase is also a concern. Several published membrane extraction studies using Aliquat 336 ai the extractant, have expressed this concern, but none has studied extractant leakage quantitatively. It is the authors' opinion that the extractant leakage should be considered at a technical parameter of a membrane. In our laboratory active progress has been made in using Aliquat 336 ‘entangled’ into the polymer membranes to remove heavy metal ions from wastewater samples. In this work, we studied the loss of Aliquat 336 from the point of view of its solubility in aqueous solutions. The results showed that the solubilities or Aliquat 3,36 in an aqueous phase acidified with 2 M HCI it about 0.1 g/100 m/ of the solution. This figure provides a useful guideline for evaluating the leakage of the Aliquatoat 336 extractant from the membranes.

• The KIPS Transactions:PartB
• /
• v.10B no.1
• /
• pp.81-86
• /
• 2003

In this paper, we propose the tracking method of moving object which use extracted object by difference between background image and target image in fixed domain. As a extraction method of object, calculate not pixel of full image but predefined some edge pixel of image to get a position of new object. Since the center area Is excluded from calculation, the extraction time is efficiently reduced. To extract object in the predefined area, get a starting point in advance and then extract size of width and height of object. Central coordinate is used to track moved object.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.8
• /
• pp.2787-2800
• /
• 2022

The aging society increases emergency situations of the elderly living alone and a variety of social crimes. In order to prevent them, techniques to detect emergency situations through voice are actively researched. This study proposes CutPaste-based anomaly detection model using multi-scale feature extraction in time series streaming data. In the proposed method, an audio file is converted into a spectrogram. In this way, it is possible to use an algorithm for image data, such as CNN. After that, mutli-scale feature extraction is applied. Three images drawn from Adaptive Pooling layer that has different-sized kernels are merged. In consideration of various types of anomaly, including point anomaly, contextual anomaly, and collective anomaly, the limitations of a conventional anomaly model are improved. Finally, CutPaste-based anomaly detection is conducted. Since the model is trained through self-supervised learning, it is possible to detect a diversity of emergency situations as anomaly without labeling. Therefore, the proposed model overcomes the limitations of a conventional model that classifies only labelled emergency situations. Also, the proposed model is evaluated to have better performance than a conventional anomaly detection model.