• Advanced Composite Materials
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• v.18 no.3
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• pp.265-285
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• 2009

Off-axis compressive deformation behavior of a unidirectional CFRP laminate at high temperature and its strain-rate dependence in a quasi-static range are examined for various fiber orientations. By comparing the off-axis compressive and tensile behaviors at an equal strain rate, the effect of different loading modes on the flow stress level, rate-dependence and nonlinearity of the off-axis inelastic deformation is elucidated. The experimental results indicate that the compressive flow stress levels for relatively larger off-axis angles of $30^{\circ}$, $45^{\circ}$ and $90^{\circ}$ are about 50 percent larger than in tension for the same fiber orientations, respectively. The nonlinear deformations under off-axis tensile and compressive loading conditions exhibit significant strain-rate dependence. Similar features are observed in the fiber-orientation dependence of the off-axis flow stress levels under tension and compression and in the off-axis flow stress differential in tension and compression, regardless of the strain rate. A phenomenological theory of viscoplasticity is then developed which can describe the tension-compression asymmetry as well as the rate dependence, nonlinearity and fiber orientation dependence of the off-axis tensile and compressive behaviors of unidirectional composites in a unified manner. It is demonstrated by comparing with experimental results that the proposed viscoplastic constitutive model can be applied with reasonable accuracy to predict the different, nonlinear and rate-dependent behaviors of the unidirectional composite under off-axis tensile and compressive loading conditions.

• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.959-968
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• 1999

In this paper we are obtained new results for bivariate pro-cesses which help us to tell the dependent structure among hitting times of the processes. We are proposed both dependence properties and the-oretical results among the processes and certain kinds of dependence properties when we are imposed on processes are reflected as analo-gous properties of corresponding hitting times. Finlly we are given some examples to illustrate these concepts.

• Human Ecology Research
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• v.52 no.5
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• pp.519-528
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• 2014

This study explores how the main variables of youth going through a transition period (parents' nurturing behavior, the youth's self-esteem and ego resilience, the peer group relationships) affect the youth's school adjustment. It also analyzes the effects of theses variables on the youth's dependence on cell phones, which are considered a necessity in modern society. This research is verified by using a structure model verification method based on data from the Korean Children Youth Panel Study. According to the research, first, 1st-year students in middle school show better adjustment to their school life and less dependence on cell phones when they have a stronger sense of self-esteem and ego resilience; further, it is revealed that cell phone dependence has an indirect influence on the school life of these children. Second, they tend to show better adjustment to their school life and less dependence on cell phones when their parents' nurturing behaviors are more positive. Third, these children tend to depend more on cell phones when they have a positive peer group relationship, Moreover, cell phone dependence has an indirect influence on their school life. When considering the impact of cell phone to youth in modern society, need to prepare proper training program for correct uses and preventing from addiction.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1119-1122
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• 2000

This paper describes on RF circuit simulation technique, especially on a RF modeling and a model extraction of a LDMOS(Lateral Diffused MOS) that has gate-width (Wg) dependence. Small-signal model parameters of the LDMOSs with various gate-widths extracted from S-parameter data are applied to make the relation between the RF performances and gate-width. It is proved that a source inductance (Ls) was not applicable to scaling rules. These extracted small-signal model parameters are also utilized to remove extrinsic elements in an extraction of a large-signal model (using HP Root MOSFET Model). Therefore, we can omit an additional measurement to extract extrinsic elements. When the large-signal model with Ls having the above gate-width dependence is applied to a high-power LDMOS module, the simulated performances (Output power, etc.) are in a good agreement with experimental results. It is proved that our extracted model and RF circuit simulation have a good accuracy.

• 한국초전도학회:학술대회논문집
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• 2009.07a
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• pp.91-91
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• 2009

• Journal of Microbiology
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• v.43 no.5
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• pp.411-416
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• 2005

The high-throughput sequencing of microbial genomes has resulted in the relatively rapid accumulation of an enormous amount of genomic sequence data. In this context, the problem posed by the detection of promoters in genomic DNA sequences via computational methods has attracted considerable research attention in recent years. This paper addresses the development of a predictive model, known as the dependence decomposition weight matrix model (DDWMM), which was designed to detect the core promoter region, including the -10 region and the transcription start sites (TSSs), in prokaryotic genomic DNA sequences. This is an issue of some importance with regard to genome annotation efforts. Our predictive model captures the most significant dependencies between positions (allowing for non­adjacent as well as adjacent dependencies) via the maximal dependence decomposition (MDD) procedure, which iteratively decomposes data sets into subsets, based on the significant dependence between positions in the promoter region to be modeled. Such dependencies may be intimately related to biological and structural concerns, since promoter elements are present in a variety of combinations, which are separated by various distances. In this respect, the DDWMM may prove to be appropriate with regard to the detection of core promoter regions and TSSs in long microbial genomic contigs. In order to demonstrate the effectiveness of our predictive model, we applied 10-fold cross-validation experiments on the 607 experimentally-verified promoter sequences, which evidenced good performance in terms of sensitivity.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.5
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• pp.206-214
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• 1996

Because of the wide variety of the composite materials, inherent variability in properties, and complex temperature and strain rate dependence, large strain behavior of these materials has not been well characterized. Large strain behavior under uniaxial tension is characterized over a range of temperatures and strain rates, and a modified simple linear viscoelastic model is fit to the observed data. Of particular importance is the strain rate and temperature dependence of these composites, and it is the primary focus of this study. The strain rate and temperature dependence is then used to predict limiting tensile strains, based on Marciniak imperfection theory. Excellent correlation was obtained between model and experiment and the results are summarized in maps of forming limit as a function of strain rate and temperature.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.101-112
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• 1998

Recently, researchers show growing interest on product quality characteristic dependence and designing acceptance sampling plans under the quality dependence. This research intends to resolve a few theoretical and practical questions for better application of acceptance sampling when the quality characteristic of product items exhibits a statistical dependence and samples are inspected according to the production order. In this research, a mathematical programming model is developed for the economic modeling of sampling plans based on two evaluation criteria : the average outgoing quality(AOQ) and the average total inspection cost. An efficient solution procedure is then proposed using the functional structure of the two evaluation criteria and the procedure is numerically illustrated.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.180-180
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• 2015

Weather radar has been widely used in measuring precipitation and discharge and predicting flood risks. The radar rainfall estimate has one of the essential problems in terms of uncertainty and accuracy. Previous study analyzed radar errors to reduce its uncertainty or to improve its accuracy. Furthermore, a recent analyzed the effect of radar error on rainfall-runoff using spatial error model (SEM). SEM appropriately reproduced radar error including spatial correlation. Since the SEM does not take the time dependence into account, its time variability was not properly investigated. Therefore, in the current study, we extend the SEM including time dependence as well as spatial dependence, named after Spatial-Temporal Error Model (STEM). Radar rainfall events generated with STEM were tested so that the peak runoff from the response of a basin could be investigated according to dependent error. The Nam River basin, South Korea, was employed to illustrate the effects of STEM on runoff peak flow.