• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.157-163
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• 2023

The attack technique targeting end-users through phishing URLs is very dangerous nowadays. With this technique, attackers could steal user data or take control of the system, etc. Therefore, early detecting phishing URLs is essential. In this paper, we propose a method to detect phishing URLs based on supervised learning algorithms and abnormal behaviors from URLs. Finally, based on the research results, we build a framework for detecting phishing URLs through end-users. The novelty and advantage of our proposed method are that abnormal behaviors are extracted based on URLs which are monitored and collected directly from attack campaigns instead of using inefficient old datasets.

• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.371-375
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.315-316
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• 2011

• Imaging Science in Dentistry
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• v.47 no.2
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• pp.99-107
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• 2017

Purpose: Erosions and osteophytes are radiographic characteristics that are found in different stages of temporomandibular joint (TMJ) osteoarthritis. This study assessed the effectiveness of digital subtraction radiography (DSR) in diagnosing simulated osteophytes and erosions in the TMJ. Materials and Methods: Five intact, dry human skulls were used to assess the effectiveness of DSR in detecting osteophytes. Four cortical bone chips of varying thicknesses (0.5 mm, 1.0 mm, 1.5 mm, and 2.0 mm) were placed at the medial, central, and lateral aspects of the condyle anterior surface. Two defects of varying depth (1.0 mm and 1.5 mm) were created on the lateral, central, and medial poles of the condyles of 2 skulls to simulate erosions. Panoramic images of the condyles were acquired before and after artificially creating the changes. Digital subtraction was performed with Emago dental image archiving software. Five observers familiar with the interpretation of TMJ radiographs evaluated the images. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of the imaging methods. Results: The area under the ROC curve (Az) value for the overall diagnostic accuracy of DSR in detecting osteophytic changes was 0.931. The Az value for the overall diagnostic accuracy of panoramic imaging was 0.695. The accuracy of DSR in detecting erosive changes was 0.854 and 0.696 for panoramic imaging. DSR was remarkably more accurate than panoramic imaging in detecting simulated osteophytic and erosive changes. Conclusion: The accuracy of panoramic imaging in detecting degenerative changes was significantly lower than the accuracy of DSR (P<.05). DSR improved the accuracy of detection using panoramic images.

• Journal of Cadastre & Land InformatiX
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• v.45 no.2
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• pp.131-147
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• 2015

In modern society, as to the underground urban infrastructure facilities(communication electricity water and sewage gas etc.) were contained many risks because of excavating. The exact position of underground facilities and the attribute information should be built in order to prevent accidents. As the result of analyzing the public surveying results from 2004 to 2009, it shows that low detecting rate of water pipeline which is only 52.4%, because the exploration of electromagnetic induction only detect metal pipeline and positioning survey only detect new pipeline before burying. Therefore development and verification of the correct and efficient exploration techniques are needed to improve the detecting rate. In this study, determined based on the location measurement results for the non-metal pipes and metal pipes before burial. It was compared with values that obtained through the ground penetrating radar and electromagnetic induction detecting. As a result, detecting rate of the concrete section showed a 100%, unpaved section showed a 94.7%, asphalt section showed 60%. So it confirmed the applicability of the ground penetrating radar at underground facilities detecting.

• Journal of Microbiology and Biotechnology
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• v.18 no.9
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• pp.1550-1554
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• 2008

A hydrogen sulfide $(H_2S)$ detecting tube was developed for the quantitative determination of $H_2S$ produced by yeast during laboratory scale wine fermentations. The detecting tube consisted of a small transparent plastic tube packed with an $H_2S$-sensitive color-indicating medium. The packed medium changed color, with the color change progressing upward from the bottom of the tube, upon exposure to $H_2S$ produced by yeast during fermentation. A calibration study using a standard $H_2S$ gas showed that the length of the portion that darkened was directly related to the quantity of $H_2S$ (${\mu}g$) with a high correlation coefficient ($r^2$=0.9997). The reproducibility of the $H_2S$ detecting tubes was determined with five repetitive measurements using a standard $H_2S$ solution [5.6${\mu}g$/200 ml (28 ppb)], which resulted in a coefficient of variation of 3.6% at this level of $H_2S$. With the sulfide detecting tubes, the production of $H_2S$ was continuously monitored and quantified from laboratory scale wine fermentations with different yeast strains and with the addition of different levels of elemental sulfur to the grape juice. This sulfide detecting tube technology may allow winemakers to quantitatively measure $H_2S$ produced under different fermentation conditions, which will eventually lead winemakers to better understand the specific factors and conditions for the excessive production of $H_2S$ during wine fermentation in a large production scale.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.345-350
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• 2016

This research suggests the keyword filtering about disaster and the method of detecting area in real-time event detecting system by analyzing contents of twitter. The diffusion of smart-mobile has lead to a fast spread of SNS and nowadays, various researches based on studying SNS are being processed. Among SNS, the twitter has a characteristic of fast diffusion since it is written in 140 words of short paragraph. Therefore, the tweets that are written by twitter users are able to perform a role of sensor. By using these features the research has been constructed which detects the events that have been occurred. However, people became reluctant to open their information of location because it is reported that private information leakage are increasing. Also, problems associated with accuracy are occurred in process of analyzing the tweet contents that do not follow the spelling rule. Therefore, additional designing keyword filtering and the method of area detection on detecting real-time event process were required in order to develop the accuracy. This research suggests the method of keyword filtering about disaster and two methods of detecting area. One is the method of removing area noise which removes the noise that occurred in the local name words. And the other one is the method of determinating the area which confirms local name words by using landmarks. By applying the method of keyword filtering about disaster and two methods of detecting area, the accuracy has improved. It has improved 49% to 78% by using the method of removing area noise and the other accuracy has improved 49% to 89% by using the method of determinating the area.

• Journal of Biomedical Engineering Research
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• v.2 no.2
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• pp.83-88
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• 1981

A method of detecting abnormal spikes occuring in the EEG of subjects suffering from epilepsy is studied. The detection scheme is to take the first derivative of EEG and to determine if it exceed some threshold value. This study is focused on the digital signal processing for detecting abnormal spikes using microcomputer.

• 한국ITS학회:학술대회논문집
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• v.2006 no.10
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• pp.37-44
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• 2006

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.520-521
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• 2005