• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.233-242
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• 2016

Startup must be agile and be able to handle extreme changes, survive unpredicted threats, and capitalize on emerging business opportunities. Agile teams continually sense changes for competitive action and marshal the necessary knowledge. While team members share their knowledge, there must be emerging various type of conflicts in teams. This study examines the relationship among the conflict, knowledge sharing and agility in startup context. At the same time, we tested the roles of shard vision both moderating variable between conflict and knowledge sharing, and antecedent for knowledge sharing. Different two types of conflict, task conflict and relationship conflict, knowledge sharing, agility, and different impact of shared vision are identified from literatures and tested. 182 data points were collected from under 5-year old startup's representatives to test these hypotheses. PLS data analysis indicated that the task conflict and shard vision positively effect on knowledge sharing, and then knowledge sharing has statistically significant effect on agility. And the impact of conlict has been weakened by shared vision's moderating effect. Based on the results, we proposed practically several team management skills for startup managers, leaders and stakeholder, and explained theoretical contributions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1797-1807
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• 2013

Dams always have the possibility of failure due to unexpected natural phenomena. In particular, dam failure can cause huge damage including damage for humans and properties when dam downstream regions are densely populated or have important national facilities. Although many studies have been conducted on the analysis of flood waves about single dam failure thus far, studies on the analysis of flood waves about the sequential failure of dams are lacking. Therefore, the purpose of this study was to calculate the peak discharge of sequential failure of dams through flood wave analysis of sequential failure of dams and this analysis techniques to predict flood wave propagation situation in downstream regions. To this end, failure flood wave analysis were conducted for Lawn Lake Dam which is a case of sequential failure of dams among actual failure cases using DAMBRK to test the suitability of the dam failure flood wave analysis model. Based on the results, flood wave analysis of sequential failure of dams were conducted for A dam in Korea assuming a virtual extreme flood to predict flood wave propagation situations and 2-dimensional flood wave analysis were conducted for major flooding points. Then, the 1, 2-dimensional flood wave analysis were compared and analyzed. The results showed goodness-of-fit values exceeding 90% and thus the accuracy of the 1-dimensional sequential failure of dams simulation could be identified. The results of this study are considered to be able to contribute to the provision of basic data for the establishment of disaster prevention measures for rivers related to sequential failure of dams.

• Journal of Korean Academy of Nursing
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• v.14 no.2
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• pp.93-111
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• 1984

The main purpose of this study is to develop a ratio scale measuring level of pain using Korean pain terms. The specific purposes of this study are to identify the degree of pain of each pain term in each subclass: to classify each subclass in terms of dimensions of pain; and to analyze factors of the Korean pain ratio scale clustering together. One hundred an4 fifty eight pain terms which were originally identified as representative terms and their synonyms were used for data collection. Fifty eight nursing professors ana sixty one medical doctors who have contacted with patients having pain were asked to rate the weight of each pain term on a visual analogue scale. Subclasses in which ranks of pain terms were same f s findings in two previous studies were 1) thermal 3 am 2) cavity pressure, 3) single stimulating pain, 4) radiation pain. and 5) chemical pain. Subclasses in which ranks of pain terms were confused were 1) incisive pressure, and 2) cold pain. Subclasses in which one new pain term was added were 1) inflammatory-repeated pain, 2) punctuate pressure, 3) constrictive pressure, 4) fatigue-related pressure, and 5) suffering-relate4 pain. Subclasses in which two new pain terms were added were 1) traction pressure, 2) peripheral nerve pain, 3) dull pain, 4) pulsation-related pain, 5) digestion-related pain, 6) tract pain, and 7) punishment-related pain. Subclass in which 3 new pain terms were included was fear-related pain. Rating scores of 5 words in 4 subclasses were significantly different between the normal group and the extreme group of subjects in terms of subjective rating. Only one word among 6 words was that newly added to the scale. Rating scores of 12 words in 9 subclasses were significantly different between doctor group and nursing professor group. Among these 12 words, only 3 were those newly added to the scale. In comparison of these 12 words, mean scores of the nursing professors were always 7 to 16 points higher than those of the medical doctors. In the analysis of judgement of subjects in terms of dimensions of pain terms, subclasses of dull pain, cavity pressure, tract pain and cold pain were suggested to be included in the miscellaneous dimension. As a result of factor analysis of the ratings given to 96 pain words using principal components analysis without iteration and with varimax rotation limiting the number of factors to 4, factors of severe pain (factor I) mild-moderate pain (factor II) , causative pain (factor III) and temperature-related pain(factor IV) were extracted with the factor loading above 0.388. When the pain words were re-arranged on the bases of factor loading above 0.368, number of factors decreased to only first two factors. Maximum score of pain word in factor II was 46.17 and the minimum score of the factor I was 45.36. Further studies are needed to identify the validity, reliability, sensitivity and practicability of this ratio scale using patients having various sources of pain.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.273-280
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• 2005

Robust magneto-telluric (MT) response function estimators are now in standard use in electromagnetic induction research. Properly devised and applied, these methods can reduce the influence of unusual data (outlier) in the response (electric field) variable, but often not sensitive to exceptional predictor (magnetic field) data, which are termed leverage points. A bounded influence estimator is described which simultaneously limits the influence of both outlier and leverage point, and has proven to consistently yield more reliable MT response function estimates than conventional robust approach. The bounded influence estimator combines a standard robust M-estimator with leverage weighting based on the statistics of the hat matrix diagonal, which is a standard statistical measure of unusual predictors. Further extensions to MT data analysis are proposed, including a establishment of data rejection criterion which minimize the influence of both electric and magnetic outlier in frequency domain based on statistical distribution of electromagnetic field. The rejection scheme made in this study seems to have an effective performance on eliminating extreme data, which is even not removed by BI estimator, in frequency domain. The effectiveness and advantage of these developments are illustrated using real MT data.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.6
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• pp.283-293
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• 2019

As applications in extreme environments such as aerospace, high-energy plasma and radio-active circumstances increases, the demand for materials that require higher melting points, higher mechanical strength and improved thermal conductivity continues to increase. Accordingly, in order to improve the oxidation/abrasion resistance of the carbon-carbon composite, which is a typical heat-resistant material, a method of using ultra high temperature ceramics was reviewed. The advantages and disadvantages of CVD coating, pack cementation and thermal plasma spraying, the simplest methods for synthesizing ultra-high temperature ceramics, were compared. As a method for applying the CVD coating method to C/C composites with complex shapes, the possibility of using thermodynamic calculation and CFD simulation was proposed. In addition, as a result of comparing the oxidation resistance of the TaC/SiC bi-layer coating and TaC/SiC multilayer coating produced by this method, the more excellent oxidation resistance of the multilayer coating on C/C was confirmed.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.113-117
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• 2016

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

• Journal of Korean Philosophical Society
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• v.145
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• pp.245-270
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• 2018

This article aims to examine the possibility of 'philosophy for old age' when humanity begins to reflect on old age in earnest as our country shifts to the aged society. In particular, this article aims to reframe $Ved{\bar{a}}ntic$ philosophy, i.e. a beacon of Hindu philosophy as a model of philosophy for old age, on the assumption that liberation-oriented Hindu philosophies in India can be the most suitable model to frame and apply philosophy for old age mainly at the individual level. First of all, this article identifies that liberation-oriented Hindu philosophies are nothing but a philosophy for the later part of one's life, that is, a philosophy for old age, showing that their common thoughts are very similar to the characteristics of old age. Then, it proves that three points of $Ved{\bar{a}}ntic$ philosophy, i.e. spirit supremacy, the world as an illusion, and freedom from all relations, are fully compatible with philosophy for old age. Finally, it argues that the tradition of Hindu saṃnyāsin (wonderer) embodied to the extreme in $Ved{\bar{a}}ntic$ philosophy is to establish 'old age for philosophy' beyond 'philosophy for old age.' Because $Ved{\bar{a}}ntic$ philosophy establishes saṃnyāsin of old age, which is optimized to strive for the truth as the confident subject of philosophical inquiry, so much that it exists more 'by old age' than 'for old age.' After all, according to $Ved{\bar{a}}ntic$ philosophy, as ontological and practical positivity is maximized in old age, so old age itself can be the best position to overcome not 'negativity of old age', but 'negativity of human condition' or 'negativity of life.'

• Journal of Korean Philosophical Society
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• v.146
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• pp.115-135
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• 2018

This article attempts to deal with the problem that science and technology function as a mechanism to oppress and exploit humans rather than to release humans from labor. To explore this subject, it is necessary to consider the difference between the theory of labor value and the theory of 'technology value'. In addition, it is also important to refer to Marx's critical view of the 'capitalist' use of technology. Above all, Marx' concepts of relative surplus value and special surplus value, and his analysis of organic composition of capital are still valid in explaining that development of technology tightens control over workers and intensity of labor, and worsens instability of employment. Reflection of the limitations of capitalist development of technology is also important for realization of its usefulness. Industry 4.0 in Germany therefore deserves to be noticed as a good example because it shows a different way from extreme capitalist exploitation. The model suggests also some points that shouldn't be overlooked, when we try to actualize the tremendous slogan of the current fourth industrial revolution as real innovation and progress in human life. In this matter, the most important point is the possibility of technological development that doesn't oppose workers' interests.

• Journal of the Korean Geotechnical Society
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• v.37 no.7
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• pp.13-23
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• 2021

If roads, bridges, buildings, etc. are built on the ground with soft clay or organic soil, there may be a lot of problems in geotechnical engineering such as settlement and stability due to the large settlement and lack of bearing capacity. In extreme cases, it may appear due to shear failure or collapse of the constructed structure, so a ground improvement method is indispensable to increase the strength of the ground and to suppress settlement. In this study, the settlement according to each groundwater level condition was analyzed using the measurement results for the groundwater level conditions, one of the important factors in predicting the settlement in dredged and reclaimed ground, and the groundwater level conditions applied to the settlement analysis were proposed by comparing it with settlement generated 5 years after construction. As a result of the analysis, it is judged that it is reasonable to apply the measured groundwater level during construction and the low water ordinary neap tide (L.W.O.N.T) during load application for the groundwater level in the settlement analysis. In addition, in the case of the dredged and reclaimed ground, it is estimated that the water pressure acting on the clay layer is nonlinear, as the result of the observations of the head of water at the observation points above and below the in-situ clay layer were different.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.