• Asian Pacific Journal of Cancer Prevention
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• 제13권1호
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• pp.329-337
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• 2012

Considerable attention has been given to the accuracy of HER-2 testing and the correlation between the results of different testing methods. This interest reflects the growing importance of HER-2 status in the management of patients with breast cancer. In this study the detection of HER-2 gene and centromere 17 status was evaluated using dual-colour primed in situ labelling (PRINS) in comparison with fluorescence in situ hybridization (FISH). These two methods were evaluated on a series of 27 formalin fixed paraffin embedded breast carcinoma tumours, previously tested for protein overexpression by HercepTest (grouped into Hercep 1+/0, 2+ and 3+). HER-2 gene amplification (ratio${\geq}2.2$) by PRINS was found in 3:3, 6:21 and 0:3 in IHC 3+, 2+ and 1+/0 cases, respectively. Comparing FISH and IHC (immunohistochemistry), showed the same results as for PRINS and IHC. Chromosome 17 aneusomy was found in 10 of 21 IHC 2+ cases (47.6%), of which 1 (10%) showed hypodisomy (chromosome 17 copy number per cell${\leq}1.75$), 7 (70%) showed low polysomy (chromosome 17 copy number per cell=2.26 - 3.75) and 2 (20%) showed high polysomy (chromosome 17 copy number per cell ${\geq}3.76$). The overall concordance of detection of HER-2 gene amplification by FISH and PRINS was 100% (27:27). Furthermore, both the level of HER-2 amplification and copy number of CEN17 analysis results correlated well between the two methods. In conclusion, PRINS is a reliable, reproducible technique and in our opinion can be used as an additional test to determine HER-2 status in breast tumours.

• Journal of Genetic Medicine
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• 제12권2호
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• pp.100-108
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• 2015

Purpose: Conventional methods for the prenatal detection of fetal RhD status involve invasive procedures such as fetal blood sampling and amniocentesis. The identification of cell-free fetal DNA (cffDNA) in maternal plasma creates the possibility of determining fetal RhD status by analyzing maternal plasma DNA. However, some technical problems still exist, especially the lack of a positive control marker for the presence of fetal DNA. Therefore, we assessed the feasibility and accuracy of fetal RHD genotyping incorporating the RASSF1A epigenetic fetal DNA marker from cffDNA in the maternal plasma of RhD-negative pregnant women in Korea. Materials and Methods: We analyzed maternal plasma from 41 pregnant women identified as RhD-negative by serological testing. Multiplex real-time PCR was performed by amplifying RHD exons 5 and 7 and the SRY gene, with RASSF1A being used as a gender-independent fetal epigenetic marker. The results were compared with those obtained by postnatal serological analysis of cord blood and gender identification. Results: Among the 41 fetuses, 37 were RhD-positive and 4 were RhD-negative according to the serological analysis of cord blood. There was 100% concordance between fetal RHD genotyping and serological cord blood results. Detection of the RASSF1A gene verified the presence of cffDNA, and the fetal SRY status was correctly detected in all 41 cases. Conclusion: Noninvasive fetal RHD genotyping with cffDNA incorporating RASSF1A is a feasible, reliable, and accurate method of determining fetal RhD status. It is an alternative to amniocentesis for the management of RhD-negative women and reduces the need for unnecessary RhIG prophylaxis.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.65-67
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• 2018

본 논문에서는 특정 공간의 흡연 여부를 감지하는 시스템을 소개한다. 제안하는 시스템은 라즈베리 파이로 이루어진 무선 애드혹 네트워크 기반 위에 구현되었다. 이는 상용 흡연 모니터링 시스템에 비하여 저가의 장치를 이용하여 경제적이며, 하나의 라즈베리파이를 이용한 또 다른 기존의 시스템에 비하여 확장성이 뛰어나다. 본 논문에서는 센서로부터 장시간 측정한 데이터를 이용하여 흡연 시와 비흡연 시 일산화탄소 농도의 확률밀도함수를 가우시안 함수로 근사화하였다. 이를 바탕으로 최대 우도 검파 (maximum likelihood detection) 기법을 이용하여, 일산탄소농도 값으로 흡연 상태를 추정하는 기법을 제안한다. 또한 애드혹 네트워크로 연결된 복수의 센서들로부터 수집한 값으로 흡연 상태를 추정하여 신뢰도를 높이고자 하였다.

• The Plant Pathology Journal
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• 제15권6호
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• pp.335-339
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• 1999

Citrus tristeza virus(CTV), an aphid-borne closterovirus, is one of the most destructive pathogens of citrus. It has caused rapid decline in growth, stem pitting and death in citrus trees. A reverse transcriptase polymerase chain reaction (RT-PCR) assay was developed for detection of CTV and investigation of the CTV infection status of citrus and its related cultivars in Cheju island. For RT-PCR based CTV detection, primers were designed to amplify 670bp of coat protein gene. A screening test for CTV in citrus cultivars was conducted from March to July in 1999. Seventy individual citrus trees representing 9 species of 3 genera were tested. The infection rates of CTV for leaves from the years or older trees of late maturing citrus varieties such as Yuzu (C. junos Sieb. ex Tanaka), Navel orange (C.sinensis Osbeck), Kiyomitanger (C. unshiu x C. sinensis), and Shiranuhi ((C. unshiu x C. sinensis) x C. reticulata) were 100%, 80%, 60%, and 60% respectively. The CTV infection rates in Early satsuma mandarins such as 'Miyagawa Early' Satsuma mandarins (C. unshiu Marc. var. Miyagawa) and 'Okitsu Early' Satsuma mandarins (C. unshiu Marc. var. Okitsu) were 100%, and 60%, respectively. CTV was not detected in Cheju native Dangyooja (C. unshiu Marc. var. Osbeck), Trifoliate orange (Poncirus trifoliata) and Kumquat (Fortunella margarita Swingle). In conclusion, RT-PCR assay can be successfully applied to the detection of CTV in citrus trees.

• 한국임상수의학회지
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• 제14권2호
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• pp.177-184
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• 1997

Canine parvovirus(CPV) is a very highly contagious virus causing hemorrhagic enteritis and myocarditis mainly in young dogs. The diseases were first recognized in 1978, and then spread throughout the world by 1980. The main source of the infection seems to be the feces of infected dogs, at the same time feces are suitable materials for detection of virus in the enteric form exactly for the same reasons. Recently, a new technique of in vitro DNA amplification, Known as the polymerase chain reaction (PCR), has been widely applied to clinical viral diagnosis because of its sensitivity, specificity and rapidity. In this research, we attemped to set up the PCR for the detection of CPV in fecal samples and conformed the canine parvpviral enteritis by PCR. To increase the sensitivity and specificity of a PCR, the nested PCR (two-step PCR) was performed. We also surveyed the contamination status of CPV in the research using fecal specimen was highly sensitive and specific. Of the 100 fecal specimens suspected canine parvoviral enteritis, 45 fecal specimens were positive in HA test, 64 fecal specimens were positive in the first PCR, and 87 fecal specimens were positive in the second PCR. CPV contamination status of animal clinics and breeding centers was serious, wo hygienic management of environment in which dogs are reared is required. The nested PCR described here seems to be a rapid, sensitive and specific for the detection of canine parvovirus.

• BMB Reports
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• 제44권12호
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• pp.765-771
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• 2011

Cancer treatment has been stratified by companion biomarker tests that serve to provide information on the genetic status of cancer patients and to identify patients who can be expected to respond to a given treatment. This stratification guarantees better efficiency and safety during treatment. Cancer patients, however, marginally benefit from the current companion biomarker-aided treatment regimens, presumably because companion biomarker tests are dependent solely on the mutation status of several genes status quo. In the true sense of the term, "personalized medicine", cancer patients are deemed to be identified individually by their molecular signatures, which are not necessarily confined to genetic mutations. Glycosylation is tremendously dynamic and shows alterations in cancer. Evidence is accumulating that aberrant glycosylation contributes to the development and progression of cancer, holding the promise for use of glycosylation status as a companion biomarker in cancer treatment. There are, however, several challenges derived from the lack of a reliable detection system for aberrant glycosylation, and a limited library of aberrant glycosylation. The challenges should be addressed if glycosylation status is to be used as a companion biomarker in cancer treatment and contribute to the fulfillment of personalized medicine.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2804-2823
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• 2013

Wireless sensor network (WSN) is a promising technology for monitoring physical phenomena at fine-grained spatial and temporal resolution. However, the typical approach of sending each sensed measurement out of the network for detailed spatial analysis of transient physical phenomena may not be an efficient or scalable solution. This paper focuses on in-network physical phenomena detection schemes, particularly the distributed computation of the boundary of physical phenomena (i.e. event), to support energy efficient spatial analysis in wireless sensor networks. In-network processing approach reduces the amount of network traffic and thus achieves network scalability and lifetime longevity. This study investigates the recent advances in distributed event detection based on in-network processing and includes a concise comparison of various existing schemes. These boundary detection schemes identify not only those sensor nodes that lie on the boundary of the physical phenomena but also the interior nodes. This constitutes an event geometry which is a basic building block of many spatial queries. In this paper, we introduce the challenges and opportunities for research in the field of in-network distributed event geometry boundary detection as well as illustrate the current status of research in this field. We also present new areas where the event geometry boundary detection can be of significant importance.

• 로봇학회논문지
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• 제13권1호
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• pp.31-37
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• 2018

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

• 대한의용생체공학회:의공학회지
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• 제18권3호
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• pp.315-323
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• 1997

Driving is a complex vigilance task that includes improper lookout, excessive speed and inattention. The primary objective of this research is to detect driver drowsiness so that the driver can be alerted to an impending traffic accident in performance. We developed the automatic detection and warning system during drowsy driving. A drowsiness detection system must be able to monitor driver status and detect the detrimental changes of a driver performance. Eyeblink has been found to be a reliable factor of drowsiness detection in earlier studies. As an additional parameter, we also considered the yawning which often occurs in a low vigilance state and predicts the drowsy state. We used a computer vision method to extract the eyeblink and yawning in the face image sequences. When the drowsy state was detected, the driver was refreshed by alarming device and menthol scent generator after deciding the warning level by fuzzy logic. For the evaluation of our system, we measured the physiological parameters such as EOG and EEG. The results indicated that it is possible to detect and alert the driver drowsiness temporarily or continuously by using our system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3608-3626
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• 2021

The detection of bolts is an important task in high-speed train inspection systems, and it is frequently performed to ensure the safety of trains. The difficulty of the vision-based bolt inspection system lies in small sample defect detection, which makes the end-to-end network ineffective. In this paper, the problem is resolved in two stages, which includes the detection network and cascaded classification networks. For small bolt detection, all bolts including defective bolts and normal bolts are put together for conducting annotation training, a new loss function and a new boundingbox selection based on the smallest axis-aligned convex set are proposed. These allow YOLOv3 network to obtain the accurate position and bounding box of the various bolts. The average precision has been greatly improved on PASCAL VOC, MS COCO and actual data set. After that, the Siamese network is employed for estimating the status of the bolts. Using the convolutional Siamese network, we are able to get strong results on few-shot classification. Extensive experiments and comparisons on actual data set show that the system outperforms state-of-the-art algorithms in bolt inspection.