• Food Science and Biotechnology
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• v.15 no.5
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• pp.786-791
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• 2006

Three solvent extraction techniques were used to recover waxy tractions from grain sorghum kernels. Yield and chemical composition of the waxy tractions obtained by reflux, bench scale (recirculated solvent), and countercurrent extraction methods were compared. Waxy traction yield from countercurrent extraction (0.200%) was significantly greater (p<0.05) than the yields of wax from both reflux (0.184%) and bench-scale (0.179%) methods. The waxy traction extracted using the bench-scale method showed the greatest relative amount of long-chained (primarily C:28 and C:30) alcohols while the countercurrent-extracted wax showed the greatest relative amount of long-chained fatty acids and fatty aldehydes. Countercurrent extraction removed a higher additive percentage of fatty aldehydes, acids, and alcohols than reflux or bench-scale extraction method.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.44 no.2
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• pp.52-58
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• 2018

Dry socket, also termed fibrinolytic osteitis or alveolar osteitis, is a complication of tooth exodontia. A dry socket lesion is a post-extraction socket that exhibits exposed bone that is not covered by a blood clot or healing epithelium and exists inside or around the perimeter of the socket or alveolus for days after the extraction procedure. This article describes dry socket lesions; reviews the basic clinical techniques of treating different manifestations of dry socket lesions; and shows how microscope level loupe magnification of $6{\times}$ to $8{\times}$ or greater, combined with co-axial illumination or a dental operating microscope, facilitate more precise treatment of dry socket lesions. The author examines the scientific validity of the proposed causes of dry socket lesions (such as bacteria, inflammation, fibrinolysis, or traumatic extractions) and the scientific validity of different terminologies used to describe dry socket lesions. This article also presents an alternative model of what causes dry socket lesions, based on evidence from dental literature. Although the clinical techniques for treating dry socket lesions seem empirically correct, more evidence is required to determine the causes of dry socket lesions.

• Journal of Information Science Theory and Practice
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• v.2 no.1
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• pp.6-21
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• 2014

This paper proposes a novel knowledge extraction system, TAKES (Two-step Approach for Knowledge Extraction System), which integrates advanced techniques from Information Retrieval (IR), Information Extraction (IE), and Natural Language Processing (NLP). In particular, TAKES adopts a novel keyphrase extraction-based query expansion technique to collect promising documents. It also uses a Conditional Random Field-based machine learning technique to extract important biological entities and relations. TAKES is applied to biological knowledge extraction, particularly retrieving promising documents that contain Protein-Protein Interaction (PPI) and extracting PPI pairs. TAKES consists of two major components: DocSpotter, which is used to query and retrieve promising documents for extraction, and a Conditional Random Field (CRF)-based entity extraction component known as FCRF. The present paper investigated research problems addressing the issues with a knowledge extraction system and conducted a series of experiments to test our hypotheses. The findings from the experiments are as follows: First, the author verified, using three different test collections to measure the performance of our query expansion technique, that DocSpotter is robust and highly accurate when compared to Okapi BM25 and SLIPPER. Second, the author verified that our relation extraction algorithm, FCRF, is highly accurate in terms of F-Measure compared to four other competitive extraction algorithms: Support Vector Machine, Maximum Entropy, Single POS HMM, and Rapier.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.157-165
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• 2021

Recently, as the spatial resolution of satellite and aerial images has improved, various studies using remotely sensed data with high spatial resolution have been conducted. In particular, since the building extraction is essential for creating digital thematic maps, high accuracy of building extraction result is required. In this manuscript, building extraction models were generated using SegNet, U-Net, FC-DenseNet, and HRNetV2, which are representative semantic segmentation models in deep learning techniques, and then the evaluation of building extraction results was performed. Training dataset for building extraction were generated by using aerial orthophotos including various buildings, and evaluation was conducted in three areas. First, the model performance was evaluated through the region adjacent to the training dataset. In addition, the applicability of the model was evaluated through the region different from the training dataset. As a result, the f1-score of HRNetV2 represented the best values in terms of model performance and applicability. Through this study, the possibility of creating and modifying the building layer in the digital map was confirmed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.984-996
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• 2007

This paper presents techniques of 2-D scattering center extraction and 2-B ISAR(Inverse SAR) image formation for scattering wave which is scattered by a target. In general, 2-D IFFT is widely used to obtain 2-D scattering center and ISAR image of targets. But, this method has drawbacks, that is poor in a resolution aspect. To overcome these shortcomings with the FT(Fourier Transform)-based method, various techniques of high resolution signal processing were developed. In this paper, algorithms of 2-D scattering center extraction and ISAR image formation such as 2-D MEMP(Matrix Enhancement and Matrix Pencil), 2-D ESPRIT(Estimation of Signal Parameter via Rotational Invariance Techniques) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and F-18 aircraft to estimate 2-D scattering center and abtain 2-D ISAR image.

• Journal of Periodontal and Implant Science
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• v.46 no.6
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• pp.415-425
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• 2016

Purpose: The present study investigated the impact of 2 different suture techniques, the conventional crossed mattress suture (X suture) and the novel hidden X suture, for alveolar ridge preservation (ARP) with an open healing approach. Methods: This study was a prospective randomized controlled clinical trial. Fourteen patients requiring extraction of the maxillary or mandibular posterior teeth were enrolled and allocated into 2 groups. After extraction, demineralized bovine bone matrix mixed with 10% collagen (DBBM-C) was grafted and the socket was covered by porcine collagen membrane in a double-layer fashion. No attempt to obtain primary closure was made. The hidden X suture and conventional X suture techniques were performed in the test and control groups, respectively. Cone-beam computed tomographic (CBCT) images were taken immediately after the graft procedure and before implant surgery 4 months later. Additionally, the change in the mucogingival junction (MGJ) position was measured and was compared after extraction, after suturing, and 4 months after the operation. Results: All sites healed without any complications. Clinical evaluations showed that the MGJ line shifted to the lingual side immediately after the application of the X suture by $1.56{\pm}0.90mm$ in the control group, while the application of the hidden X suture rather pushed the MGJ line slightly to the buccal side by $0.25{\pm}0.66mm$. It was demonstrated that the amount of keratinized tissue (KT) preserved on the buccal side was significantly greater in the hidden X suture group 4 months after the procedure (P<0.05). Radiographic analysis showed that the hidden X suture had a significant effect in preserving horizontal width and minimizing vertical reduction in comparison to X suture (P<0.05). Conclusions: Our study provided clinical and radiographic verification of the efficacy of the hidden X suture in preserving the width of KT and the dimensions of the alveolar ridge after ARP.

• Membrane and Water Treatment
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• v.7 no.6
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• pp.521-537
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• 2016

Laboratory-scale experiments were carried out to investigate the adsorption equilibrium, the adsorption kinetics and facilitated transport of two cationic dyes (Methylene Blue (MB) and Rhodamine B (RB)) on Polymer Inclusion Membrane (D2EHPA-PIM). Different adsorption isotherms (Freundlich, Langmuir and Temkin models) as well as kinetics models indicated that the adsorption process is spontaneous and exothermic. Under the optimal conditions, the adsorption removal efficiencies reach about 93% and 97% for MB and RB respectively. Different extraction values by D2EHPA-PIM were obtained for the two cationic dyes: MB is weakly extracted at pH 2.0 (E% = 18.7%) whilst E% = 82.4% was observed for RB at the same pH. This difference was exploited in a mixture containg both the 2 cationic dyes for the selective extraction of RB at pH 2. Desorption of both dyes was achieved from the membrane by using acidic aqueous solutions and desorption ratio up to 90% was obtained. The formulas of the extracted complexes by the PIMs were, determined by the method of slopes. The dyes transport was elucidated using mass transfer analysis where in it found relatively high values of the initial flux ($J_0$) as 41.57 and $18.74{\mu}mol.m^2.s^{-1}$ for MB and RB respectively.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.1-10
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• 2020

The image analysis is an important and predominant task for classifying the different parts of the image. The analysis of complex image analysis like histopathological define a crucial factor in oncology due to its ability to help pathologists for interpretation of images and therefore various feature extraction techniques have been evolved from time to time for such analysis. Although deep reinforcement learning is a new and emerging technique but very less effort has been made to compare the deep learning and deep reinforcement learning for image analysis. The paper highlights how both techniques differ in feature extraction from complex images and discusses the potential pros and cons. The use of Convolution Neural Network (CNN) in image segmentation, detection and diagnosis of tumour, feature extraction is important but there are several challenges that need to be overcome before Deep Learning can be applied to digital pathology. The one being is the availability of sufficient training examples for medical image datasets, feature extraction from whole area of the image, ground truth localized annotations, adversarial effects of input representations and extremely large size of the digital pathological slides (in gigabytes).Even though formulating Histopathological Image Analysis (HIA) as Multi Instance Learning (MIL) problem is a remarkable step where histopathological image is divided into high resolution patches to make predictions for the patch and then combining them for overall slide predictions but it suffers from loss of contextual and spatial information. In such cases the deep reinforcement learning techniques can be used to learn feature from the limited data without losing contextual and spatial information.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.493-498
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• 2004

The objective of the present study is to compare various conventional and recently evolved satellite image-processing techniques and to ascertain the best possible technique that can identify and position of aquaculture farms accurately in and around the Younggwang coastal area. Several conventional techniques performed to extract such information fiom the Landsat-TM imagery do not seem to yield better information about the aquaculture farms, and lead to misclassification. The large errors between the actual and extracted aquaculture farm information are due to existence of spectral confusion and inadequate spatial resolution of the sensor. This leads to possible occurrence of mixture pixels or 'mixels' of the source of errors in the classification techniques. Understanding the confusing and mixture pixel problems requires the development of efficient methods that can enable more reliable extraction of aquaculture farm information. Thus, the more recently evolved methods such as the step-by-step partial spectral end-member extraction and linear spectral unmixing methods are introduced. The farmer one assumes that an end-member, which is often referred to as 'spectrally pure signature' of a target feature, does not appear to be a spectrally pure form, but always mix with the other features at certain proportions. The assumption of the linear spectral unmxing is that the measured reflectance of a pixel is the linear sum of the reflectance of the mixture components that make up that pixel. The classification accuracy of the step-by-step partial end-member extraction improved significantly compared to that obtained from the traditional supervised classifiers. However, this method did not distinguish the aquaculture ponds and non-aquaculture ponds within the region of the aquaculture farming areas. In contrast, the linear spectral unmixing model produced a set of fraction images for the aquaculture, water and soil. Of these, the aquaculture fraction yields good estimates about the proportion of the aquaculture farm in each pixel. The acquired proportion was compared with the values of NDVI and both are positively correlated (R$^2$ =0.91), indicating the reliability of the sub-pixel classification.ixel classification.

• Journal of Soil and Groundwater Environment
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• v.18 no.1
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• pp.112-122
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• 2013

Current status of soil contamination with fluorine and its source were investigated. The basic principles and procedures of various techniques for the analysis of fluorine contents in soil and solid phase samples were summarized in this review. Analysis of fluorine in solid matrices can be achieved by two types of techniques: (i) UV/Vis spectrophotometer or ion selective electrode (ISE) analysis after performing appropriate extraction steps and (ii) direct solid analysis. As the former cases, the standard method of Korean ministry of environment, alkali fusion-ISE method, pyrohydrolysis, oxygen bomb combustion, aqua regia digestion-automatic analysis, and sequential extraction-ISE method were introduced. In addition, direct analysis methods (i.e., X-ray fluorescence spectrometry and proton induced gamma-ray emission spectrometry) and atomic spectrometry combining with the equipment for introducing solid phase sample were also reviewed. Fluorine analysis techniques can be reasonably selected through site-specific information such as matrix condition, contamination level, the amount of samples and the principles of various methods for the analysis of fluorine presented in this review.