• Journal of Dental Anesthesia and Pain Medicine
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• v.18 no.5
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• pp.287-294
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• 2018

Mandibular third molar extraction is commonly performed in dental clinics. However, the optimal method of anesthesia has not been established for this procedure. The conventional inferior alveolar nerve block is the most widely used method. However, its success rate is not high and it may lead to complications, such as aspiration and nerve injury. Therefore, various anesthesia methods are being investigated. Articaine has been proven to be efficacious in a number of studies and is being used with increasing frequency in clinical practice. In this review article, we will briefly review various local anesthesia techniques, anesthetics, and a computer-controlled local anesthetic delivery (CCLAD) system, which reduces pain by controlling the speed of drug injection, for mandibular third molar extraction.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.41 no.5
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• pp.281-283
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• 2015

Extraction of an impacted third molar is one of the most frequently performed techniques in oral and maxillofacial surgery. Surgeons can suffer numerous external injuries while extracting a tooth, with percutaneous injuries to the hand being the most commonly reported. In this article, we present a case involving a percutaneous injury of the surgeon's femoral region caused by breakage of the fissure bur connected to the handpiece during extraction of the third molar. We also propose precautions to prevent such injuries and steps to be undertaken when they occur.

• Korean Journal of Remote Sensing
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• v.7 no.1
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• pp.29-43
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• 1991

The study was performed to extraction the ground water potential area using LANDSAT TM data. The image processing techniques developed for the study are contrast transformation, differential filtering and pseudo stereoscopic image methods. These were examined for lineament extraction, lineament interpretation and the integration of vertor data with LANDSAT data. The differential filtering method is much usefull for lineament extraction, and all direction lineaments are clearly shown on the band 5 image of LANDSAT TM. The pseudo stereoscopic image are made in which color differential method is adopted, the pair images are usefull for the lineament interpretation. The results of the analysis are as follows. 1) there is a close correlation between lineament and cased well in the study area, because 33 wells of the developed 45 cased wells coincide with the lineaments. 2) 21 sites in the study area were selected for pumping test, and as a result 11 sites of them produces over than 200 ton/day.

• Journal of the Korean institute of surface engineering
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• v.57 no.1
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• pp.31-37
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• 2024

The surge in demand for lithium is primarily fueled by the expanding electric vehicle market, the necessity for renewable energy storage, and governmental initiatives aimed at achieving carbon neutrality. This study proposes a straightforward method for lithium extraction utilizing cellulose nanofiber (CNF) via a vacuum filtration process. This approach yields a porous CNF film, showcasing its potential utility as a lithium extractor and indicator. Given its abundance and eco-friendly characteristics, cellulose nanofiber (CNF) emerges as a material offering both economic and environmental advantages over traditional lithium extraction techniques. Hence, this research not only contributes to lithium recovery but also presents a sustainable solution to meet the growing demand for lithium in energy storage technologies.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.42-47
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• 2024

The electrochemical extraction of uranium in ternary low melting LiCl-KCl-CsCl eutectic on inert and reactive electrodes via different electrochemical techniques was investigated. It was established that the electrochemical reduction process of U(III) ions on the inert W electrode was irreversible and proceeded in one stage. On reactive liquid Ga and liquid Cd electrodes the reduction of uranium ions took place with the considerable depolarization with the formation of UGa₂, UGa₃ and UCd₁₁ intermetallic compounds. Thermodynamic characteristics of uranium compounds and alloys were calculated. The conditions for the extraction of uranium from the electrolyte in the form of alloys on both liquid reactive electrodes via potentiostatic electrolysis were found.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.27 no.3
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• pp.238-247
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• 2005

The placement of different graft materials and/or the use of occlusive membranes to cover the extraction socket entrance are techniques aimed at reducing alveolar ridge resorption and enhancing bone formation. However, in spite of its clinical advantage, the use of graft materials in fresh extraction socket has been questioned because particles of the grafted material have been found in alveolar sockets with fibrous union. The purposes of this study were to evaluate whether alveolar ridge resorption following tooth extraction could be reduced and bone formation could be enhanced by the application of absorbable gelatin spongy or gelatin spongy soaked with platelet rich plasma(PRP) used as a space filler in clinical and radiographic aspects. Eighty patients who were scheduled for extraction of both third molars were participated and carried out by one experienced surgeon. Following extraction of teeth, one extracted socket were treated with gelatin spongy as an experimental group A and the other were treated with gelatin spongy and PRP as an experimental group B. The routine extracted socket were healed without any treatment as a control group. From the period of extraction to 12 weeks postoperatively, we examined the clinical course and radiographic evaluation on socket at regular interval. Both experimental groups showed faster wound healing process than control clinically. Vertical gingival height of the extraction socket were less changed statistically in both experimental groups than control. The horizontal width change of the extraction socket were not significant statistically in any group. Radiographic changes of the alveolar bone height were less changed in both experimental groups and bone density were showed higher than control. There were a little difference between experimental group A and B. In conclusion, absorbable gelatin sponge and with PRP were considered as having preservation effects of extraction socket and stimulation of bone formation process after extraction.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.35-36
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• 2008

• Journal of Computing Science and Engineering
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• v.2 no.2
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• pp.109-136
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• 2008

In this survey paper, we discuss biomedical ontologies and major text mining techniques applied to biomedicine and healthcare. Biomedical ontologies such as UMLS are currently being adopted in text mining approaches because they provide domain knowledge for text mining approaches. In addition, biomedical ontologies enable us to resolve many linguistic problems when text mining approaches handle biomedical literature. As the first example of text mining, document clustering is surveyed. Because a document set is normally multiple topic, text mining approaches use document clustering as a preprocessing step to group similar documents. Additionally, document clustering is able to inform the biomedical literature searches required for the practice of evidence-based medicine. We introduce Swanson's UnDiscovered Public Knowledge (UDPK) model to generate biomedical hypotheses from biomedical literature such as MEDLINE by discovering novel connections among logically-related biomedical concepts. Another important area of text mining is document classification. Document classification is a valuable tool for biomedical tasks that involve large amounts of text. We survey well-known classification techniques in biomedicine. As the last example of text mining in biomedicine and healthcare, we survey information extraction. Information extraction is the process of scanning text for information relevant to some interest, including extracting entities, relations, and events. We also address techniques and issues of evaluating text mining applications in biomedicine and healthcare.

• Journal of the Semiconductor & Display Technology
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• v.15 no.4
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• pp.97-102
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• 2016

Image stitching is a process of combining two or more images with overlapping area to create a panorama of input images, which is considered as an active research area in computer vision, especially in the field of augmented reality with 360 degree images. Image stitching techniques can be categorized into two general approaches: direct and feature based techniques. Direct techniques compare all the pixel intensities of the images with each other, while feature based approaches aim to determine a relationship between the images through distinct features extracted from the images. This paper proposes a novel image stitching method based on feature pixels with approximated clustering filter. When the features are extracted from input images, we calculate a meaning of the minutiae, and apply an effective feature extraction algorithm to improve the processing time. With the evaluation of the results, the proposed method is corresponding accurate and effective, compared to the previous approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2788-2808
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• 2023

Brain tumors are one of the most threatening malignancies for humans. Misdiagnosis of brain tumors can result in false medical intervention, which ultimately reduces a patient's chance of survival. Manual identification and segmentation of brain tumors from Magnetic Resonance Imaging (MRI) scans can be difficult and error-prone because of the great range of tumor tissues that exist in various individuals and the similarity of normal tissues. To overcome this limitation, the Amended Convolutional Neural Network (ACNN) model has been introduced, a unique combination of three techniques that have not been previously explored for brain tumor detection. The three techniques integrated into the ACNN model are image tissue preprocessing using the Kalman Bucy Smoothing Filter to remove noisy pixels from the input, image tissue segmentation using the Isotonic Regressive Image Tissue Segmentation Process, and feature extraction using the Marr Wavelet Transformation. The extracted features are compared with the testing features using a sigmoid activation function in the output layer. The experimental findings show that the suggested model outperforms existing techniques concerning accuracy, precision, sensitivity, dice score, Jaccard index, specificity, Positive Predictive Value, Hausdorff distance, recall, and F1 score. The proposed ACNN model achieved a maximum accuracy of 98.8%, which is higher than other existing models, according to the experimental results.