• Journal of Korean Tunnelling and Underground Space Association
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• v.13 no.3
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• pp.243-260
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• 2011

To predict TBM performance in design stage is indispensable for its successful application. The NTNU model, one of the representative TBM performance prediction models uses two distinct parameters such as DRI and CLI obtained from three different tests on bored rock cores. Based on DRI and CLI, it is possible to predict TBM advance rate and cutter life in the NTNU model. In this study, NTNU testing methods and their related testing equipments were introduced to measure DRl and CLI for the NTNU model. Then, in order to derive their relationships, the two key parameters measured for 39 domestic rocks were compared with physico-mechanical properties of rock such as uniaxial compressive strength and quartz content. Lastly, the experimental results were also compared with NTNU database to verify their reliability.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.2
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• pp.162-172
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• 2011

In this paper, simulation was used to determine accuracies of genomic breeding values for polygenic traits associated with many thousands of markers obtained from high density genome scans. The statistical approach was based upon stochastically simulating a pedigree with a specified base population and a specified set of population parameters including the effective and noneffective marker distances and generation time. For this population, marker and quantitative trait locus (QTL) genotypes were generated using either a single linkage group or multiple linkage group model. Single nucleotide polymorphism (SNP) was simulated for an entire bovine genome (except for the sex chromosome, n = 29) including linkage and recombination. Individuals drawn from the simulated population with specified marker and QTL genotypes were randomly mated to establish appropriate levels of linkage disequilibrium for ten generations. Phenotype and genomic SNP data sets were obtained from individuals starting after two generations. Genetic prediction was accomplished by statistically modeling the genomic relationship matrix and standard BLUP methods. The effect of the number of linkage groups was also investigated to determine its influence on the accuracy of breeding values for genomic selection. When using high density scan data (0.08 cM marker distance), accuracies of breeding values on juveniles were obtained of 0.60 and 0.82, for a low heritable trait (0.10) and high heritable trait (0.50), respectively, in the single linkage group model. Estimates of 0.38 and 0.60 were obtained for the same cases in the multiple linkage group models. Unexpectedly, use of BLUP regression methods across many chromosomes was found to give rise to reduced accuracy in breeding value determination. The reasons for this remain a target for further research, but the role of Mendelian sampling may play a fundamental role in producing this effect.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.5
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• pp.2369-2374
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• 2014

Background and Aim: Selumetinib is a promising and interesting targeted therapy agent as it may reverse radioiodine uptake in patients with radioiodine-refractory differentiated thyroid cancer. We conduct this metaanalysis to compare the efficacy and safety of selumetinib with current therapies in patients with advanced cancer. Methods: An electronic search was conducted using PubMed/ Medicine, EMBASE and Cochrane library databases. Statistical analyses were carried out using either random-effects or fixed-effects models according to the heterogeneity of eligible studies. Results: Six eligible trials involved 601 patients were identified. Compared with current therapies, treatment schedules with selumetinib did not improve progression free survival (hazard ratio, 0.91; 95%CI 0.70-1.17, P= 0.448), but did identify better clinical benefits (odds ratio, 1.24; 95%CI 0.69-2.24, P = 0.472) and less disease progression (hazard ratio, 0.72; 95%CI 0.51-1.00, P = 0.052) though its impact was not statistically significant. Sub-group analysis resulted in significantly improved progression free survival (hazard ratio, 0.61; 95%CI 0.49-0.57, P = 0.00), clinical benefits (odds ratio, 3.04; 95%CI 1.60-5.77, P = 0.001) and reduced disease progression (hazard ratio, 0.35; 95%CI 0.18-0.67, P = 0.001) in patients administrated selumetinib. Dermatitis acneiform (risk ratio, 9.775; 95%CI 3.143-30.395, P = 0.00) and peripheral edema (risk ratio, 2.371; 95%CI 1.690-3.327, P = 0.00) are the most frequently observed adverse effects associated with selumetinib. Conclusions: Compared with current chemotherapy, selumetinib has modest clinical activity as monotherapy in patients with advanced cancer, but combinations of selumetinib with cytotoxic agents in patients with BRAF or KRAS mutations hold great promise for cancer treatment. Dermatitis acneiform and peripheral edema are the most frequently observed adverse effects in patients with selumetinib.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.569-575
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• 2020

The serial arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet, and statistical features have been used, additional steps such as transformation and feature extraction are required. On the contrary, deep learning models directly use the raw data without any feature extraction processes. Therefore, the usage of time-domain data is preferred, but the performance is not satisfactory. To solve this problem, subsequent 1-D signals are transformed into 2-D data that can feed into a convolutional neural network (CNN). Experiments validated that CNN model outperforms deep neural network (DNN) by the classification accuracy of 8.6%. In addition, data augmentation is utilized, resulting in the accuracy improvement by 14%.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.2179-2184
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• 2012

Introduction and aim: To compare reproductive factor influence on patients with pathological diagnosed malignant and benign tumor in the Breast Department, The First Peoples' Hospital of Kunming in Yunnan province, China. Methods: A hospital-based case-control study was conducted on 263 breast cancer (BC) cases and 457 non-breast cancer controls from 2009 to 2011. The cases and controls information on demographics, medical history, and reproductive characteristics variables were collected using a self-administered questionnaire and routine medical records. Histology of breast cancer tissue and benign breast lesion were documented by pathology reports. Since some variables in data analysis had zero count in at least one category, binomial-response GLM using the bias-reduction method was applied to estimate OR's and their 95% confidence intervals (95% CI). To adjust for age and menopause status, a compound variable comprising age and menopausal status was retained in the statistical models. Results: multivariate model analysis revealed significant independent positive associations of BC with short menstrual cycle, old age at first live birth, never breastfeeding, history of oral contraception experience, increased number of abortion, postmenopausal status, and nulliparity. Categorised by age and menopausal status, perimenopausal women had about 3-fold and postmenopausal women had more than 5-fold increased risk of BC compared to premenopausal women. Discussion and Conclusion: This study has confirmed the significant association of BC and estrogen related risk factors of breast cancer including longer menstrual cycle, older age of first live birth, never breastfeeding, nulliparity, and number of abortions more than one. The findings suggest that female hormonal factors, especially the trend of menopause status play a significant role in the development of BC in Yunnan women.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.477-481
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• 2008

Place recognition is necessary for a mobile user to be provided with place-dependent information. This paper proposes real-time video based place recognition system that identifies users' current place while moving in the building. As for the feature extraction of a scene, there have been existing methods based on global feature analysis that has drawback of sensitive-ness for the case of partial occlusion and noises. There have also been local feature based methods that usually attempted object recognition which seemed hard to be applied in real-time system because of high computational cost. On the other hand, researches using statistical methods such as HMM(hidden Markov models) or bayesian networks have been used to derive place recognition result from the feature data. The former is, however, not practical because it requires huge amounts of efforts to gather the training data while the latter usually depends on object recognition only. This paper proposes a combined approach of global and local feature analysis for feature extraction to complement both approaches' drawbacks. The proposed method is applied to a mobile information system and shows real-time performance with competitive recognition result.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.306-312
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• 2008

In a goal-oriented dialogue, speaker's intention can be approximated by a semantic structure that consists of a pair of a speech act and a concept sequence. Therefore, it is very important to correctly identify the semantic structure of an utterance for implementing an intelligent dialogue system. In this paper, we propose a model to efficiently analyze the semantic structures based on an active teaming method. To reduce the burdens of high-level linguistic analysis, the proposed model only uses morphological features and previous semantic structures as input features. To improve the precisions of semantic structure analysis, the proposed model adopts CRFs(Conditional Random Fields), which show high performances in natural language processing, as an underlying statistical model. In the experiments in a schedule arrangement domain, we found that the proposed model shows similar performances(92.4% in speech act analysis and 89.8% in concept sequence analysis) to the previous models although it uses about a third of training data.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.453-463
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• 2013

In this paper, we present an effective method and a system for the music summarization which automatically extract the chorus portion of a piece of music. A music summary technology is very useful for browsing a song or generating a sample music for an online music service. To develop the solution, conventional automatic music summarization methods use a 2-dimensional similarity matrix, statistical models, or clustering techniques. But our proposed method extracts the music summary by calculating BER(Bit Error Rate) between audio fingerprint blocks which are extracted from a song. But we could directly use an enormous audio fingerprint database which was already saved for a music retrieval solution. This shows the possibility of developing a various of new algorithms and solutions using the audio fingerprint database. In addition, experiments show that the proposed method captures the chorus of a song more effectively than a conventional method.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.11
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• pp.1700-1713
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• 2018

Objective: The aim of this study was to verify the usefulness of artificial neural networks (ANN), multivariate adaptive regression splines (MARS), naïve Bayes classifier (NBC), general discriminant analysis (GDA), and logistic regression (LR) for dystocia detection in Polish Holstein-Friesian Black-and-White heifers and cows and to indicate the most influential predictors of calving difficulty. Methods: A total of 1,342 and 1,699 calving records including six categorical and four continuous predictors were used. Calving category (difficult vs easy or difficult, moderate and easy) was the dependent variable. Results: The maximum sensitivity, specificity and accuracy achieved for heifers on the independent test set were 0.855 (for ANN), 0.969 (for NBC), and 0.813 (for GDA), respectively, whereas the values for cows were 0.600 (for ANN), 1.000 and 0.965 (for NBC, GDA, and LR), respectively. With the three categories of calving difficulty, the maximum overall accuracy for heifers and cows was 0.589 (for MARS) and 0.649 (for ANN), respectively. The most influential predictors for heifers were an average calving difficulty score for the dam's sire, calving age and the mean yield of the farm, where the heifer was kept, whereas for cows, these additionally included: calf sex, the difficulty of the preceding calving, and the mean daily milk yield for the preceding lactation. Conclusion: The potential application of the investigated models in dairy cattle farming requires, however, their further improvement in order to reduce the rate of dystocia misdiagnosis and to increase detection reliability.

• The korean journal of orthodontics
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• v.50 no.2
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• pp.120-128
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• 2020

Objective: The aims of the present study were to evaluate the changes in the maximum lip-closing force (MLF) after orthodontic treatment with or without premolar extractions and verify the correlation of these changes with dentoskeletal changes. Methods: In total, 17 women who underwent nonextraction orthodontic treatment and 15 women who underwent orthodontic treatment with extraction of all four first premolars were included in this retrospective study. For all patients, lateral cephalograms and dental models were measured before (T0) and after (T1) treatment. In addition, MLF was measured at both time points using the Lip De Cum LDC-110R^® device. Statistical analyses were performed to evaluate changes in clinical variables and MLF and their correlations. Results: Both groups showed similar skeletal patterns, although the extraction group showed greater proclination of the maxillary and mandibular incisors and lip protrusion compared to the nonextraction group at T0. MLF at T0 was comparable between the two groups. The reduction in the arch width and depth and incisor retroclination from T0 to T1 were more pronounced in the extraction group than in the nonextraction group. MLF in the extraction group significantly increased during the treatment period, and this increase was significantly greater than that in the nonextraction group. The increase in MLF was found to be correlated with the increase in the interincisal angle and decrease in the intermolar width, arch depth, and incisor-mandibular plane angle. Conclusions: This study suggests that MLF increases to a greater extent during extraction orthodontic treatment than during nonextraction orthodontic treatment.