• Journal of the korean academy of Pediatric Dentistry
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• v.33 no.2
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• pp.336-347
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• 2006

Pit and fissure sealants has been proven as safe and effective method of caries prevention. But improper application of pit and fissure sealant may masking the caries process in occlusal fissure. Dentists have to understand the correct and exact application method of pit and fissure sealant for he good result of caries prevention. A key factor to enhanced the effectiveness of caries prevention is retention of pit and fissure sealant. Deep penetration of material into fissure and least marginal leakage around the fissure orifice are the major concerns for dentists to achieve the successive application of pit and fissure sealants. This paper reviewed the literature on the pit and fissure sealants under the following subtitles for enhanced retention : (1) application timing, (2) Indication, (3) Occlusal prophylaxis, (4) Materials, (5) Penetration, (5) Recall check Dental profession must perform the exact application of pit and fissure sealant because this procedure is one of the most technique-sensitive one in dental field.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.27-34
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• 2011

In this paper, the novel approach for image contrast enhancement is introduced. The method is based on the unsharp mask and directional information of images. Since the unsharp mask techniques give better visual quality than the conventional sharpening mask, there are much works on image enhancement using unsharp masks. The proposed algorithm decomposes the image to several blocks and extracts directional information using DCT. From the geometric properties of the block, each block is labeled as appropriate type and processed by adaptive unsharp mask. The masking process is skipped at the flat area to reduce the noise artifact, but at the texture and edge area, the adaptive unsharp mask is applied to enhance the image contrast based on the edge direction. Experiments show that the proposed algorithm produces the contrast enhanced images with superior visual quality, suppressing the noise effects and enhancing edge at the same time.

• Journal of Sensor Science and Technology
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• v.30 no.4
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• pp.267-272
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• 2021

In this study, Ag was deposited to investigate its applicability as a surface-enhanced Raman scattering substrate after forming a grass-type black silicon structure through maskless reactive ion etching. Grass-structured black silicon with heights of 2 - 7 ㎛ was formed at radio-frequency (RF) power of 150 - 170 W. The process pressure was 250 mTorr, the O₂/SF₆ gas ratio was 15/37.5, and the processing time was 10 - 20 min. When the processing time was increased by more than 20 min, the self-masking of Si_xO_yF_z did not occur, and the black silicon structure was therefore not formed. Raman response characteristics were measured based on the Ag thickness deposited on a black silicon substrate. As the Ag thickness increased, the characteristic peak intensity increased. When the Ag thickness deposited on the black silicon substrate increased from 40 to 80 nm, the Raman response intensity at a Raman wavelength of 1507 / cm increased from 8.2 × 10³ to 25 × 10³ cps. When the Ag thickness was 150 nm, the increase declined to 30 × 10³ cps and showed a saturation tendency. When the RF power increased from 150 to 170 W, the response intensity at a 1507/cm Raman wavelength slightly increased from 30 × 10³ to 33 × 10³ cps. However, when the RF power was 200 W, the Raman response intensity decreased significantly to 6.2 × 10³ cps.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.49-59
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• 2023

Recently, attention to the pandemic situation represented by COVID-19 emerged problems caused by unexpected shortage of medical personnel. In this paper, we present a method for diagnosing the presence or absence of lesional sign on PA chest X-ray images as computer vision solution to support diagnosis tasks. Method for visual anomaly detection based on feature modeling can be also applied to X-ray images. With extracting feature vectors from PA chest X-ray images and divide to patch unit, region-specific abnormality can be detected. As preliminary experiment, we created simulation data set containing multiple objects and present results of the comparative experiments in this paper. We present method to improve both efficiency and performance of the process through hard masking of patch features to aligned images. By summing up regional specificity and global anomaly detection results, it shows improved performance by 0.069 AUROC compared to previous studies. By aggregating region-specific and global anomaly detection results, it shows improved performance by 0.069 AUROC compared to our last study.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.643-646
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• 2005

The gas hydrate exploration using seismic reflection data, the detection of BSR(Bottom Simulating Reflector) on the seismic section is the most important work flow because the BSR have been interpreted as being formed at the base of a gas hydrate zone. Usually, BSR has some dominant qualitative characteristics on seismic section i.e. Wavelet phase reversal compare to sea bottom signal, Parallel layer with sea bottom, Strong amplitude, Masking phenomenon above the BSR, Cross bedding with other geological layer. Even though a BSR can be selected on seismic section with these guidance, it is not enough to conform as being true BSR. Some other available methods for verifying the BSR with reliable analysis quantitatively i.e. Interval velocity analysis, AVO(Amplitude Variation with Offset)analysis etc. Usually, AVO analysis can be divided by three main parts. The first part is AVO analysis, the second is AVO modeling and the last is AVO inversion. AVO analysis is unique method for detecting the free gas zone on seismic section directly. Therefore it can be a kind of useful analysis method for discriminating true BSR, which might arise from an Possion ratio contrast between high velocity layer, partially hydrated sediment and low velocity layer, water saturated gas sediment. During the AVO interpretation, as the AVO response can be changed depend upon the water saturation ratio, it is confused to discriminate the AVO response of gas layer from dry layer. In that case, the AVO modeling is necessary to generate synthetic seismogram comparing with real data. It can be available to make conclusions from correspondence or lack of correspondence between the two seismograms. AVO inversion process is the method for driving a geological model by iterative operation that the result ing synthetic seismogram matches to real data seismogram wi thin some tolerance level. AVO inversion is a topic of current research and for now there is no general consensus on how the process should be done or even whether is valid for standard seismic data. Unfortunately, there are no well log data acquired from gas hydrate exploration area in Korea. Instead of that data, well log data and seismic data acquired from gas sand area located nearby the gas hydrate exploration area is used to AVO analysis, As the results of AVO modeling, type III AVO anomaly confirmed on the gas sand layer. The Castagna's equation constant value for estimating the S-wave velocity are evaluated as A=0.86190, B=-3845.14431 respectively and water saturation ratio is $50\%$. To calculate the reflection coefficient of synthetic seismogram, the Zoeppritz equation is used. For AVO inversion process, the dataset provided by Hampson-Rushell CO. is used.

• The Journal of Bigdata
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• v.5 no.1
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• pp.11-27
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• 2020

In this paper, we developed a big data platform to store, process, and analyze effectively on such education longitudinal study data. And it was applied to the Seoul Education Longitudinal Study(SELS) to confirm its usefulness. The developed platform consists of data preprocessing unit and data analysis unit. The data preprocessing unit 1) masking, 2) converts each item into a factor 3) normalizes / creates dummy variables 4) data derivation, and 5) data warehousing. The data analysis unit consists of OLAP and data mining(DM). In the multidimensional analysis, OLAP is performed after selecting a measure and designing a schema. The DM process involves variable selection, research model selection, data modification, parameter tuning, model training, model evaluation, and interpretation of the results. The data warehouse created through the preprocessing process on this platform can be shared by various researchers, and the continuous accumulation of data sets makes further analysis easier for subsequent researchers. In addition, policy-makers can access the SELS data warehouse directly and analyze it online through multi-dimensional analysis, enabling scientific decision making. To prove the usefulness of the developed platform, SELS data was built on the platform and OLAP and DM were performed by selecting the mathematics academic achievement as a measure, and various factors affecting the measurements were analyzed using DM techniques. This enabled us to quickly and effectively derive implications for data-based education policies.

• Korean Journal of Biological Psychiatry
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• v.6 no.1
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• pp.111-118
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• 1999

Objectives : There have been several evidences that the central nervous system defect is one of the etiologic factors in schizophrenia and high nailfold plexus visibility can reflect these defects indirectly. These are particularly related to the negative symptoms of schizophrenia. In this study, we examined the relationship between nailfold plexus visibility and various clinical variables in schizophrenia. Methods : Forty patients(20 males, 20 females) satisfying the DSM-lV criteria for schizophrenia and forty normal controls(20 males, 20 females) were measured for Plexus Visualization Score (PVS) by using capillary microscopic examination. We used Positive and Negative Syndrome Scale(PANSS), Ulmann-Giovannoni Process-Reactive Questi-onnaire(PRQ), Phillips Premorbid Adjustment Scale(PAS), Continuous Performance Test, and Backward Masking for psychopathology and clinical variables. Results : There was no significant relationship between schizophrenic subjects and normal controls in PVS. PVS was correlated with PANSS positively except negative symptom subscore. PVS was correlated with PRQ score negatively, and with PAS score positively. Conclusions : This study shows high PVS are associated with more severe psychotic symptoms and with clinical variables, such as disease process and premorbid adjustment, in some schizophrenics.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Journal of the Korean association of regional geographers
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• v.9 no.2
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• pp.203-216
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• 2003

The process of constructing coastal digital elevation model(DEM), for the 3 dimensional analysis, is composed by abstracting land layers for land elevation and water depth, reprojecting UTM, relocating geographical grid, and interpolating works. The geomorphic set of shallow sea, including tidal current, tidal zone deposition, and water depth distribution, was analyzed by eye search of Landsat TM image, masking of land zone, band combination and regression analysis. Some horizontal differences, between combined DEM and surveyed data of shallow sea, was corrected for analysis. Analyzed geomorphic elements are stream channel, alluvial fan, coastal terrace, tidal current. and shallow sea bank. Results of analysis present that transported fluvial materials influence tidal sedimentation, especially from Gahwacheon river, for the role of artificial draining flooding waters from Jinyang Reservoir, almost in the summer season. In the coastal area with less tidal current, more fine materials are deposited. The influence of currental deposition are higher on small pockets with west coast of well developed terraces. The lower skirt of alluvial fans developed into the tidal zone of shallow sea. Small pocket type bays are closed by coastal current, and less influenced from tidal deposition. The bank of Jinju Bay are developed originally from submerging of remnant erosional mountain ranges, and play on the role of trapping fine materials.