• Journal of Families and Better Life
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• v.28 no.2
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• pp.27-37
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• 2010

The purpose of the study was to analyze the constraints that are normally experienced before moving in the context of the household characteristics of households that had recently moved to newly-built apartments. The data for the analysis was collected through a self-administered questionnaire from July 1, 2008 to August 10, 2008. The sample consisted of 251 households in Ulsan living in an apartment complex who had moved within a year. The data from the sample was analyzed by descriptive statistics, factor analysis, and analysis of variance with Duncan's multiple range tests. The results are as follows. The constraints were categorized into information gathering, attractive housing characteristics, expectations of residential mobility, housing development and policies, and resources. Overall, the constraints did not have a huge impact on the performance of the residential mobility of the sample households. Resources, however, were the most influential factors among the five constraints followed by attractive housing characteristics, information gathering, etc. The constraints varied based on the demographic characteristics, such as the household size, duration of marriage, age of the household head, and the socio-economic characteristics, such as the education level of the household head, household income, and the number of mobility. As the number of family members increased, the age of the household head went up, or the level of education went down, the constraints on information gathering were affected in terms of performing residential mobility. Households with a middle aged head with a professional occupation were more constrained by the attractive characteristics of the housing. The impact of the resources related constraints was significantly different based on the number of family members, marriage duration, and the household head's age and occupation, and the number of mobility.

• The Journal of Korean Academic Society of Nursing Education
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• v.18 no.3
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• pp.499-509
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• 2012

Purpose: The purpose of this study was to develop a Simulation-based Integrated Clinical Practice Program (SICPP) for nursing students and to identify the effect of this program. Methods: A non-equivalent pre-post test of quasi-experimental design was used. One hundred thirty-one nursing students participated in the study with 69 in the experimental group and 62 in the control group. We developed a SICPP taking 3 hours per session, once per week for 10 weeks. Data were analyzed using the SPSS 19.0 program with descriptive statistics, ${\chi}^2$-test, independent t-test. Results: There were significant increases in nursing clinical competence (t=2.72, p=.008) and critical thinking(t=2.18, p=.031) in the experimental group compared to the control group. However, there was no difference in the problem solving process (t=0.36, p=.720) between the experimental and control groups. Conclusion: These results indicate that a SICPP can be used as an integrative program for enhancing the core performance of nursing students. However, a SICPP to promote the problem solving process needs to be more developed and research related with SICPP is further needed.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7583-7588
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• 2014

Background: Colorectal cancer (CRC) is a major cause of cancer-related death and cancer-related incidence worldwide. The potential of microRNA-21 (miR-21) as a biomarker for CRC detection has been studied in several studies. However, the results were inconsistent. Therefore, we conducted the present meta-analysis to systematically assess the diagnostic value of miR-21 for CRC. Materials and Methods: Using a random-effect model, the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated to evaluate the diagnostic performance of miR-21 for CRC. A summary receiver operating characteristic (SROC) curve and an area under the curve (AUC) were also generated to assess the diagnosis accuracy of miR-21 for CRC. Q test and I2 statistics were used to assess between-study heterogeneity. Publication bias was evaluated by the Deeks' funnel plot asymmetry test. Results: A total of 986 CRC patients and 702 matched healthy controls from 8 studies were involved in the meta-analysis. The pooled results for SEN, SPE, PLR, NLR, DOR, and AUC were 57% (95%CI: 39%-74%), 87% (95%CI: 78%-93%), 4.4 (95%CI: 2.4-8.0), 0.49 (95%CI: 0.32-0.74), 9 (95%CI: 4-22), and 0.83 (95%CI: 0.79-0.86), respectively. Subgroup analyses further suggested that blood-based studies showed a better diagnostic accuracy compared with feces-based studies, indicating that blood may be a better matrix for miR-21 assay and CRC detection. Conclusions: Our findings suggest that miR-21 has a potential diagnostic value for CRC with a moderate level of overall diagnostic accuracy. Hence, it could be used as auxiliary means for the initial screening of CRC and avoid unnecessary colonoscopy, which is an invasive and expensive procedure.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.47-61
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• 2012

parallel transmitting system with channel bonding method have been proposed to transmit mass content such as UHD(Ultra High Definition) in HFC(Hybrid Fiber Coaxial) networks. However, this system may lead to channel resource problem because the system needs many channels to transmit mass content. In this paper, we analyze three effective bandwidth approximation algorithms to use the bonding channel efficiently. These algorithms are the effective bandwidth of Gaussian approximation method algorithm proposed by Guerin, the effective bandwidth based on statistics of video frames proposed by Lee and the effective bandwidth based on Gaussian traffic proposed by Nagarajan. We also evaluate compatibility of algorithms to the mass broadcasting service. OPNET simulator is used to evaluate the performance of the algorithms. For accuracy of simulation, we make mass source from real HD broadcasting stream.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.295-304
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• 2010

Coating thickness is one of target variables in quality control process in steel industry. To predict coating thickness and to control quality of anti-fingerprint steel coils, ultraviolet-visible spectra are measured. We propose a variable-interval selection procedure based on the variable importance in projection in partial least square model. Using the proposed variable interval selection method, prediction performance gets better in the reduced model than the full model with full spectra absorbance. It is also shown that the first differencing as a data preprocessing technique does work well for the prediction of coating thickness.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.5
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• pp.19-25
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• 2004

In this paper, we propose optimal and suboptimal serial code acquisition schemes for chip-asynchronous direct-sequence spread-spectrum systems. The conventional serial code acquisition scheme is to compare each value of correlator outputs with a threshold individually. However, such a scheme is optimum only under the chip-synchronous assumption which is actually very difficult to be held prior to acquisition at the receiver because the signal-to-noise ratios before despreading are very low. In this paper, an optimal serial code acquisition scheme is derived based on the maximum-likelihood criterion under the more realistic and general chip-asynchronous environments. A suboptimal scheme, which is simpler but yields comparable performance to the optimal one, is also derived based on the criterion of local detection power Numerical results show that, under the chip-asynchronous environments, both the optimal and suboptimal serial code acquisition schemes outperform the conventional serial code acquisition scheme.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.7
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• pp.63-70
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• 2006

This paper describes research of using area of artificial mark on vision based head tracker system. A head tracker system consists of the translational and rotational motions which are detected by web camera. Results of the motion are taken from image processing and neural network. Because of the characteristics of cockpit, the specific color on the helmet is tracked for translational motion. And rotational motion is tracked via neural network. Ratio of two different colored area on the helmet is used as input of network. Neural network algorithms used, such as back-propagation and RBFN (Radial Basis Function Network). Both back-propagation using a characteristic of feedback and RBFN using a characteristic of statistics have a good performances for the tracking of nonlinear system such as a head motion. Finally, this paper analyzes and compares with tracking performance.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.33-42
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• 2007

Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. From the analysis of mission time, the result of this comparative study shows the excellent performance of Burr coverage model rather than exponential coverage and S-shaped model using NTDS data. This analysis of failure data compared with the Kappa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.3
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• pp.163-170
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• 2000

Accident statistics shows that the portion of fatal occupant injuries due to side impacts is considerably high. The side impact usually leads to a severe intrusion of side structure into the passenger compartment. Furthermore, the safety zone for the side impact is relatively small compared to the front impact. Those kinds of physics for side impact frequently result in a fatal injury for the occupant. Therefore, NHTSA and EEVC are trying to intensify the regulation for the occupant protection against side impact. Both the regulation and recent market trends are asking for an installation of side airbag. There are several types of system configuration for side impact sensing. In this paper, we adopt the acceleration-based remote sensing method for the side airbag control system. We mainly focus on the development of hardware and crash discrimination algorithm of remote sensing unit. The crash discrimination algorithm needs fast decision of airbag firing especially for high-speed side impact such as FMVSS 214 and EEVC tests. It is also required to distinguish between low-speed fire and no-fire events. The algorithm should have a sufficient safety margin against any misuse situation such as hammer blow, door slam, etc. This paper introduces several firing criteria such as acceleration. velocity and energy criteria that use physical value proportional to crash severity. We have made a simulation program by using Matlab/Simulink to implement the proposed algorithm. We have conducted an algorithm calibration by using real crash data for 2,500cc vehicle. The crash performance obtained by the simulation was verified through a pulse injection method. It turned out that the results satisfied the system requirements well.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.341-347
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• 2017

As the amount of document data increases, the user needs summarized information to understand the document. However, existing document summary research methods rely on overly simple statistics, so there is insufficient research on multiple document summaries for ambiguity of sentences and meaningful sentence generation. In this paper, we investigate semantic connection and preprocessing process to process unnecessary information. Based on the vocabulary semantic pattern information, we propose a multi-document summarization method that enhances semantic connectivity between sentences using VAE. Using sentence word vectors, we reconstruct sentences after learning from compressed information and attribute discriminators generated as latent variables, and semantic connection processing generates a natural summary sentence. Comparing the proposed method with other document summarization methods showed a fine but improved performance, which proved that semantic sentence generation and connectivity can be increased. In the future, we will study how to extend semantic connections by experimenting with various attribute settings.