• Molecular & Cellular Toxicology
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• v.4 no.3
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• pp.246-252
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• 2008

Tumor tissue is usually contaminated by normal tissue components, which reduces the sensitivity of analysis for exploring genetic alterations. Although microdissection has been adopted to minimize the contamination of tumor DNA with normal cell components, there is a concern over the amount of microdissected DNA not enough to be applied to array-CGH reaction. To amplify the extracted DNA, several whole genome amplification (WGA) methods have been developed, but objective comparison of the array-CGH outputs using different types of WGA methods is still scarce. In this study, we compared the performance of non-amplified microdissected DNA and DNA amplified in 2 WGA methods such as degenerative oligonucleotide primed (DOP)-PCR, and multiple strand displacement amplification (MDA) using Phi 29 DNA polymerase. Genomic DNA was also used to make a comparison. We applied those 4 DNAs to whole genome BAC array to compare the false positive detection rate (FPDR) and sensitivity in detecting copy number alterations under the same hybridization condition. As a result microdissected DNA method showed the lowest FPDR and the highest sensitivity. Among WGA methods, DOP-PCR amplified DNA showed better sensitivity but similar FPDR to MDA-amplified method. These results demonstrate the advantage and applicability of microdissection for array-CGH analysis, and provide useful information for choosing amplification methods to study copy number alterations, especially based on precancerous and microscopically invaded lesions.

• Journal of KSNVE
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• v.8 no.6
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• pp.1181-1192
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• 1998

This paper describes the performance of a full-authority neural network-based fault tolerant system within a flight control system. This fault tolerant flight control system integrates sensor and actuator failure detection, identification, and accommodation (SFDIA and AFDIA), The first task is achieved by incorporating a main neural network (MNN) and a set of n decentralized neural networks (DNNs) to create a system for achieving fault tolerant capabilities for a system with n sensors assumed to be without physical redundancy The second scheme implements the same main neural network integrated with three neural network controllers (NNCs). The function of NNCs is to regain equilibrium and to compensate for the pitching, rolling. and yawing moments induced by the failure. Particular emphasis is placed in this study toward achieving an efficient integration between SFDIA and AFDIA without degradation of performance in terms of false alarm rates and incorrect failure identification. The results of the simulation with different actuator and sensor failures are presented and discussed.

• Journal of Biomedical Engineering Research
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• v.37 no.5
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• pp.161-167
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• 2016

Recent technological advances in sensor fabrication and bio-signal processing enabled non-constraint and non-intrusive measurement of human bio-signals. Especially, non-constraint measurement of ECG makes it available to estimate various human health parameters such as heart rate. Additionally, non-constraint ECG measurement of wheelchair user provides real-time health parameter information for emergency response. For accurate emergency response with low false alarm rate, it is necessary to discriminate quality levels of ECG measured using non-constraint approach. Health parameters acquired from low quality ECG results in inaccurate information. Thus, in this study, a machine learning based approach for three-class classification of ECG quality level is suggested. Three sensors are embedded in the back seat, chest belt, and handle of automatic wheelchair. For the two sensors embedded in back seat and chest belt, capacitively coupled electrodes were used. The accuracy of quality level classification was estimated using Monte Carlo cross validation. The proposed approach demonstrated accuracy of 94.01%, 95.57%, and 96.94% for each channel of three sensors. Furthermore, the implemented algorithm enables classification of user posture by detection of contacted electrodes. The accuracy for posture estimation was 94.57%. The proposed algorithm will contribute to non-constraint and robust estimation of health parameter of wheelchair users.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.926-935
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• 2015

The efficiency of genome-wide association analysis (GWAS) depends on power of detection for quantitative trait loci (QTL) and precision for QTL mapping. In this study, three different strategies for GWAS were applied to detect QTL for carcass quality traits in the Korean cattle, Hanwoo; a linkage disequilibrium single locus regression method (LDRM), a combined linkage and linkage disequilibrium analysis (LDLA) and a $BayesC{\pi}$ approach. The phenotypes of 486 steers were collected for weaning weight (WWT), yearling weight (YWT), carcass weight (CWT), backfat thickness (BFT), longissimus dorsi muscle area, and marbling score (Marb). Also the genotype data for the steers and their sires were scored with the Illumina bovine 50K single nucleotide polymorphism (SNP) chips. For the two former GWAS methods, threshold values were set at false discovery rate <0.01 on a chromosome-wide level, while a cut-off threshold value was set in the latter model, such that the top five windows, each of which comprised 10 adjacent SNPs, were chosen with significant variation for the phenotype. Four major additive QTL from these three methods had high concordance found in 64.1 to 64.9Mb for Bos taurus autosome (BTA) 7 for WWT, 24.3 to 25.4Mb for BTA14 for CWT, 0.5 to 1.5Mb for BTA6 for BFT and 26.3 to 33.4Mb for BTA29 for BFT. Several candidate genes (i.e. glutamate receptor, ionotropic, ampa 1 [GRIA1], family with sequence similarity 110, member B [FAM110B], and thymocyte selection-associated high mobility group box [TOX]) may be identified close to these QTL. Our result suggests that the use of different linkage disequilibrium mapping approaches can provide more reliable chromosome regions to further pinpoint DNA makers or causative genes in these regions.

• The Korean Journal of Applied Statistics
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• v.24 no.3
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• pp.535-546
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• 2011

This study develops statistical models for the binary forecast of Asian dust days over South Korea in the winter season. For this study, we used three kinds of data; the rst one is the observed Asian dust days for a period of 31 years (1980 to 2010) as target values, the second one is four meteorological factors(near surface temperature, precipitation, snowfall, ground wind speed) in the source regions of Asian dust based on the NCEP reanalysis data and the third one is the large-scale climate indices. Four kinds of statistical models(multiple regression models, logistic regression models, decision trees, and support vector machines) are applied and compared based on skill scores(hit rate, probability of detection and false alarm rate).

• Journal of Veterinary Clinics
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• v.34 no.6
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• pp.420-424
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• 2017

Cystic endometrial hyperplasia (CEH) and uterine dilation (hydro-, muco-, hemato- and pyometra) are common uterine diseases in intact female dogs. The aim of the present study was to assess the usefulness of digital abdominal radiography in diagnosing uterine disease in intact female dogs. Two hundred and thirteen intact female dogs were included, and were classified into four groups on the basis of radiographic uterine visibility (visible/invisible) and ultrasonographic findings (normal uterus/abnormal uterine condition including CEH and uterine dilation). For each dog, the ratio of the maximum uterine diameter to the height of the fifth lumbar vertebral body (U/L5 ratio) was calculated on radiographs. There were 78 and 135 dogs in the normal and abnormal groups, respectively; 34.6% normal and 53.5% abnormal uteri were visible on abdominal radiographs. Our results suggested that a mean U/L5 ratio of $1.18{\pm}0.53$ ($mean{\pm}2SD$) indicated a normal radiographic uterus diameter, and that a value of > 1.60 should be used as an indicator of uterine disease in clinical practice. However, because false negative results were noted, radiography cannot replace ultrasonography for assessment of the uterus.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.89-95
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• 2020

Recently, studies are being conducted to recognize a sketch image of a GUI (Graphical User Interface) based on a deep learning and to make it into a code implemented in an application. UI / UX designers can communicate with developers through storyboards when developing mobile applications. However, UI / UX designers can create different widgets for ambiguous widgets. In this paper, we propose an automatic UI detection method using symbol markers to improve the accuracy of DNN (Deep Neural Network) based UI identification. In order to evaluate the performance with or without the symbol markers, their accuracy is compared. In order to improve the accuracy according to of the symbol marker, the results are analyzed when the shape is a circle or a parenthesis. The use of symbol markers will reduce feedback between developer and designer, time and cost, and reduce sketch image UI false positives and improve accuracy.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9471-9473
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• 2014

Background: Since 2002, from October till December of each year, the Lebanese Ministry of Public Health conducts a mammogram based breast cancer screening campaign in the whole country for women over 40 years of age. These mammograms are performed free of charge in governmental hospitals or for reduced fees in private hospitals. The aim of this study is to analyze the direct impact of this campaign on cancer detection and subsequent treatment. Materials and Methods: Radiologic records of women screened with a mammogram during the campaign period from October till December 2012 at Saint Joseph Hospital, Baouchrieh, Beirut, were reviewed. Results of mammograms were reported using the ACR score. Women with ACR score ${\geq}4$ were tracked and investigated. Results: 900 screening mammograms were performed; median age was 55.2 years (range:31-81 years). Some 826 (91.8%) had an ACR score of ${\leq}2$; 66 (7.3%) an ACR =3 and only 8 (0.89%) an ACR=4. Thus, less than 1% (8/900) of all screened women were considered at high risk and needed a close follow-up. Among these 8 women, 4 underwent surgery for an early breast cancer, one had synchronous metastatic breast cancer and two were lost to follow-up. Conclusions: To coclude, Among 900-screened women for BC, less than 1 % (8 out of 900) were at high risk of hiding a BC (ACR=4), half of them benefited from early therapy (4 women out of 900) and one was a false positive. Larger studies on national level should be accomplished to have a complete data on breast cancer screening in Lebanon. The results of these studies can affect the Lebanese health policy regarding BC.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.28-42
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• 2013

Personal Rapid Transit(PRT) is a new unmanned transportation system using electricity. The purpose of the PRT is relieving the congestion of city traffic and connecting between inner city and airport, high-speed railroad. PRT requires to develop devices for the guarantee of safety and reliability. PRT as the mean of rail transportation must be equipped with control system for front rail sensing. Ultra Wide Band(UWB) radar system is suitable for PRT's detection because it has the advantage of low power consumption, low interference and high resolution. In this paper, an improved adaptive Constant False Alarm Rate(CFAR) algorithm is proposed and studied in various noise environments. The proposed algorithm improves performance in various noise environments compared to the Mean Level CFAR algorithms and other adaptive CFAR algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1A
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• pp.37-52
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• 2004

In this paper, Multistage Adaptive Partial PIC eliminating effectively the multiple access and multipath interference for DS-CDMA based W-CDMA uplink system is designed and its performance is evaluated with computer simulation. By adaptively controlling the slope of the soft limiter with received signals, the efficiency of the soft limiter can be maximized and the better performance is obtained by solving error floor problem using further precise generation of interference signal. As a result, The proposed Multistage Adaptive Partial PIC with simple optimizing method for time-variant channel showed optimum performance at fewer stages. Besides fewer stages, the interference cancellation at the output of the rake receiver considerably reduced system complexity. The Multistage Adaptive Partial PIC with precise generation and efficient cancellation of interference signal can solve error eoor problem, resulted from initial false detection and improve system performance of high data rate system.