• Journal of radiological science and technology
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• v.36 no.2
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• pp.141-148
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• 2013

The CT examination sometimes fail to localize the cerebral hemorrhage part depending on the seriousness and may embarrass the pathologist if he/she is not trained enough for emergencies. Therefore, an assisting role is necessary for examination, automatic and quick detection of the cerebral hemorrhage part, and supply of the quantitative information in emergencies. the computer based automatic detection and recognition system may be of a great service to the bleeding part detection. As a result of this research, we succeeded not only in automatic detection of the cerebral hemorrhage part by grafting threshold value handling, morphological operation, and roundness calculation onto the bleeding part but also in development of the PCA based classifier to screen any wrong choice in the detection candidate group. We think if we apply the new developed system to the cerebral hemorrhage patient in his critical condition, it will be very valuable data to the medical team for operation planning.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.545-552
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• 2012

The rapid development of information technology is making large changes in our lives today. Also the infrastructure and services are combinding with information technology which predicts another huge change in our environment. However, the development of information technology brings various types of side effects and these side effects not only cause financial loss but also can develop into a nationwide crisis. Therefore, the detection and quick reaction towards these side effects is critical and much research is being done. Intrusion detection systems can be an example of such research. However, intrusion detection systems mostly tend to focus on judging whether particular traffic or files are malicious or not. Also it is difficult for intrusion detection systems to detect newly developed malicious codes. Therefore, this paper proposes a method which determines whether the present network model is normal or abnormal by comparing it with past network situations.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.186-192
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• 2023

Malwares are becoming a major problem nowadays all around the world in android operating systems. The malware is a piece of software developed for harming or exploiting certain other hardware as well as software. The term Malware is also known as malicious software which is utilized to define Trojans, viruses, as well as other kinds of spyware. There have been developed many kinds of techniques for protecting the android operating systems from malware during the last decade. However, the existing techniques have numerous drawbacks such as accuracy to detect the type of malware in real-time in a quick manner for protecting the android operating systems. In this article, the authors developed a hybrid model for android malware detection using a decision tree and KNN (k-nearest neighbours) technique. First, Dalvik opcode, as well as real opcode, was pulled out by using the reverse procedure of the android software. Secondly, eigenvectors of sampling were produced by utilizing the n-gram model. Our suggested hybrid model efficiently combines KNN along with the decision tree for effective detection of the android malware in real-time. The outcome of the proposed scheme illustrates that the proposed hybrid model is better in terms of the accurate detection of any kind of malware from the Android operating system in a fast and accurate manner. In this experiment, 815 sample size was selected for the normal samples and the 3268-sample size was selected for the malicious samples. Our proposed hybrid model provides pragmatic values of the parameters namely precision, ACC along with the Recall, and F1 such as 0.93, 0.98, 0.96, and 0.99 along with 0.94, 0.99, 0.93, and 0.99 respectively. In the future, there are vital possibilities to carry out more research in this field to develop new methods for Android malware detection.

• Clinical and Experimental Pediatrics
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• v.48 no.9
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• pp.976-985
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• 2005

Purpose : Although influenza is one of the most important causes of acute respiratory tract infections in children, effective antiviral therapies are not common and there are only a few clinical studies on treatment of influenza in children. We evaluated the efficacy of oseltamivir in the treatment of naturally aquired influenza in children during the first half of 2004 in Busan. Methods : From January 2004 to June 2004, throat swabs and nasal washes were performed and cultured for the isolation of influenza virus and tested by rapid antigen detection test(QuickVue influenza test) in children with suspected influenza infections. The children who responded positively to the QuickVue influenza test, we divided into two groups : an oseltamivir treatment group and a control group. We compared their clinical symptoms(including fever duration) and diagnosis. The medical records of patients with influenza virus infection were reviewed retrospectively. Results : A total of 621 individuals were suspected of influenza infection. Influenza viruses were isolated in 79(17.2 percent) out of 621 patients examined. QuickVue influenza tests were positive in 181 cases. The treatment group(83 individuals) received oseltamivir twice daily for 5 days, and the control group(99 individuals) were administered only symptom relief medicine. There was no differences between the two groups in clinical diagnosis and symptoms. Oseltamivir treatment reduced the fever duration and other respiratory symptoms. There were no adverse events associated with oseltamivir treatment. Conclusion : Our data suggest that oral oseltamivir treatment reduces the fever duration and other respiratory symptoms of acute influenza without side effects in children.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.213-230
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• 2017

The satellite-based red tide detection algorithms have been developed for specific occurrence waters and red tide species. However, it is essential to study the whole occurrence waters and various red tide species for quick and accurate surveillance of red tide around the Korean coastal waters. In thisstudy, the comprehensive analysesinvolve the spectral features of red tide areas and the suitability of the satellite-based red tide detection algorithms used with GOCI in the Korean coastal waters. As a result, the spectral characteristics were changed according to the chlorophyll content of red tide species and the turbidity of the waters where the red tide appeared. In addition, the previous red tide detection algorithm is applied to GOCI, and it is found that there is a limitation to the red tide area extraction as the existing threshold value. To overcome these limitations, red tide species were divided into two groups according to the difference of chlorophyll content and a system for red tide surveillance wassuggested. It is possible to distinguish between red tide and non-red tide area through five steps. As a result of applying to GOCI, the red tide was appropriately extracted from the previous algorithm based on red tide breaking news. If such a red tide surveillance system is used, it will be possible to efficiently monitor red tide by quick and accurate surveillance of the whole occurrence waters around the Korean and various red tide species.

• Journal of Plant Biotechnology
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• v.5 no.2
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• pp.83-86
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• 2003

A reverse transcription polymerase chain reaction (RT-PCR) protocol was developed using two specific 22-mer primers located in coat protein gene of SPFMV. A 411 bp PCR-product was detected in virus infected plants as well as tissue culture raised sweet potato but not in healthy plants. For optimization of RT-PCR protocol, the optimum crude nucleic acid concentration, annealing temperature, primer concentration and numbers of PCR-cycle for maximum sensitivity and specificity were determined. The optimum condition for RT-PCR was as follows: RT-PCR reaction mixture was one-step mixture, containing 50 pmol of primer, 30 units of reverse transcriptase, 5 units of RNasin, and the crude nucleic acid extracts (200 ng). In RT-PCR, cDNA was synthesized at $42^{\circ}C$ for 45 min before a quick incubation on ice after pre-denaturation at $95^{\circ}C$ for 5 min. The PCR reaction was carried out for 40 cycles at $96^{\circ}C$ for 30 see, $63^{\circ}C$ for 30 sec, $72^{\circ}C$ for 1 min, and finally at $72^{\circ}C$ for 10 min. The viral origin of the amplified product was confirmed by sequencing, with the sequence obtained having $95-98\%$ homology with published sequence data for SPFMV. The benefits of this RT-PCR based detection of SPFMV would be simple, rapid and specific.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.409-420
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• 2007

Since 1988, pine wilt disease has spread over rapidly in Korea. It is not easy to detect the damaged pine trees by pine wilt disease from conventional remote sensing skills. Thus, many possibilities were investigated to detect the damaged pines using various kinds of remote sensing data including high spatial resolution satellite image of 2000/2003 IKONOS and 2005 QuickBird, aerial photos, and digital airborne data, too. Time series of B&W aerial photos at the scale of 1:6,000 were used to validate the results. A local maximum filtering was adapted to determine whether the damaged pines could be detected or not at the tree level from high resolution satellite images, and to locate the damaged trees. Several enhancement methods such as NDVI and image transformations were examined to find out the optimal detection method. Considering the mean crown radius of pine trees, local maximum filter with 3 pixels in radius was adapted to detect the damaged trees on IKONOS image. CIR images of 50 cm resolution were taken by PKNU-3(REDLAKE MS4000) sensor. The simulated CIR images with resolutions of 1 m, 2 m, and 4 m were generated to test the possibility of tree detection both in a stereo and a single mode. In conclusion, in order to detect the pine tree damaged by pine wilt disease at a tree level from satellite image, a spatial resolution might be less than 1 m in a single mode and/or 1 m in a stereo mode.

• The Plant Pathology Journal
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• v.38 no.3
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• pp.229-238
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• 2022

Fusarium wilt caused by Fusarium oxysporum f. sp. niveum (Fon) is the most serious soil-borne disease in the world and has become the main limiting factor of watermelon production. Reliable and quick detection and quantification of Fon are essential in the early stages of infection for control of watermelon Fusarium wilt. Traditional detection and identification tests are laborious and cannot efficiently quantify Fon isolates. In this work, a real-time polymerase chain reaction (PCR) assay has been described to accurately identify and quantify Fon in watermelon plants and soil. The FONRT-18 specific primer set which was designed based on identified specific sequence amplified a specific 172 bp band from Fon and no amplification from the other formae speciales of Fusarium oxysporum tested. The detection limits with primers were 1.26 pg/µl genomic DNA of Fon, 0.2 pg/ng total plant DNA in inoculated plant, and 50 conidia/g soil. The PCR assay could also evaluate the relationships between the disease index and Fon DNA quantity in watermelon plants and soil. The assay was further used to estimate the Fon content in soil after disinfection with CaCN₂. The real-time PCR method is rapid, accurate and reliable for monitoring and quantification analysis of Fon in watermelon plants and soil. It can be applied to the study of disease diagnosis, plant-pathogen interactions, and effective management.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.125-134
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• 2024

The novel coronavirus 2019 is called COVID-19 has outspread swiftly worldwide. An early diagnosis is more important to control its quick spread. Medical imaging mechanics, chest calculated tomography or chest X-ray, are playing a vital character in the identification and testing of COVID-19 in this present epidemic. Chest X-ray is cost effective method for Covid-19 detection however the manual process of x-ray analysis is time consuming given that the number of infected individuals keep growing rapidly. For this reason, it is very important to develop an automated COVID-19 detection process to control this pandemic. In this study, we address the task of automatic detection of Covid-19 by using a popular deep learning model namely the VGG19 model. We used 1300 healthy and 1300 confirmed COVID-19 chest X-ray images in this experiment. We performed three experiments by freezing different blocks and layers of VGG19 and finally, we used a machine learning classifier SVM for detecting COVID-19. In every experiment, we used a five-fold cross-validation method to train and validated the model and finally achieved 98.1% overall classification accuracy. Experimental results show that our proposed method using the deep learning-based VGG19 model can be used as a tool to aid radiologists and play a crucial role in the timely diagnosis of Covid-19.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.5
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• pp.498-502
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• 1998

The present study was designed, fIrst to develop the new methodology to measure the bioluminescence activity easily in live developing bovine embryos by photoncounting, and secondly to compare the expression efficiency of four luciferase reporter genes in bovine embryos at four- to 16-cell stages. In experiment 1, equimolar pSVlacZ and pSVEluc were microinjected into the pronucleus of fertilized bovine oocytes. At 2 days after micro injection, bioluminescence activity of these embryos was measured by photoncounting with a luminometer for 1 min, and lacZ gene expression in the same embryos was assayed by X-gal staining. All the luciferase-positive oocytes showed some bacterial ${\beta}$-galactosidase activity irrespective of the intensity. In experiment 2, four firefly luciferase genes (pTKEluc, pTK6WEluc, pSVEluc and pMiwluc) were introduced by micro injection, and the injected embryos were cultured for the following 2 days. Detection of the luciferase gene expression was done by photoncounting at 5 to 55 min. Over the measurement period, the luciferase activity was almost constant irrespective of the transgenes microinjected. The luciferase activity and expression efficiency at 2 days after microinjection were not significantly affected by the difference in the microinjected transgenes. The present results demonstrated that the bioluminescence activity in live developing bovine embryos could be measured quickly by photoncounting.