• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.822-831
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• 2021

Although programs have been developed to evaluate the risk of dragging anchors, it is practically difficult for VTS(vessel traffic service) operators to calculate and evaluate these risks by obtaining input factors from anchored ships. Therefore, in this study, the gross tonnage (GT) that could be easily obtained from the ship by the VTS operators was set as an independent variable, and linear and nonlinear regression analyses were performed using the input factors as the dependent variables. From comparing the fit of the polynomial model (linear) and power series model (nonlinear), the power series model was evaluated to be more suitable for all input factors in the case of container ships and bulk carriers. However, in the case of tanker ships, the power supply model was suitable for the LBP(length between perpendiculars), width, and draft, and the polynomial model was evaluated to be more suitable for the front wind pressure area, weight of the anchor, equipment number, and height of the hawse pipe from the bottom of the ship. In addition, all other dependent variables, except for the front wind pressure area factor of the tanker ship, showed high degrees of fit with a coefficient of determination (R-squared value) of 0.7 or more. Therefore, among the input factors of the dragging anchor risk assessment program, all factors except the external force, seabed quality, water depth, and amount of anchor chain let out are automatically applied by the regression analysis model formula when only the GT of the ship is provided.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.459-467
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• 2018

This study aim to analyze the factors affecting technical support input and performance of companies benefiting from ICT SME technology support operated by ETRI. In order to analyze the data, we surveyed 181 companies who received technical support between 2015 and 2017, and analyzed the relationship between input factors and performance factors through path analysis. As a result of the study, it was found that the service quality was directly influenced on the improvement of technology level, and the cost reduction effect was influenced by the amount of support, the year of support, and the service quality. Also, input factors affecting contribution sales are the amount of support, and the support year and quality of support services are not effective. Finally, as a result of examining the effect of technological and economic performance on job creation, it is found that the effect of job creation increases as the contribution sales increase.

• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.51-68
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• 2020

Purpose: The primary objective of this research is to develop the optimal operating conditions as well as their associated design spaces for a Cryogenic Submerged Arc Welding(SAW) process by improving its quality and productivity simultaneously. Methods: In order to investigate functional relationships among quality characteristics and their associated control factors of an SAW process, a stepwise design of experiment(DoE) method is proposed in this paper. Based on the DoE results, not only a multi-dimensional design space but also a safe operating space and normal acceptable range(NAR) by integrating statistical confidence intervals were demonstrated. In addition, the optimal operating conditions within the proposed NAR can be obtained by a robust optimal design method. Results: This study provides a customized stepwise DoE method (i.e., a sequential set of DoE such as a factorial design and a central composite design) for Cryogenic SAW process and its statistical analysis results. DoE results can then provide both the main and interaction effects of input control factors and the functional relationships between the input factors and their associated output responses. Maximizing both the product quality with high impact strength and the productivity with minimum processing times simultaneously in a case study, we proposed a design space which can provide both acceptable productivity and quality levels and NARs of input control factors. In order to confirm the optimal factor settings and the proposed NARs, validation experiments were performed. Conclusion: This research may provide significant contributions and applications to many SAW problems by preparing a standardization of the functional relationship between the input factors and their associated output response. Moreover, the proposed design space based on DoE and NAR methods can simultaneously consider a number of quality characteristics including tradeoff between productivity and quality levels.

• Journal of Digital Contents Society
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• v.6 no.4
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• pp.235-242
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• 2005

This Study examines influencing factors such as input, process, and output variables on1 student's satisfaction in cyber-education. That is to study on the effectiveness of input, process, and output variables for cyber-education and how does student's interaction moderate influencing factors and student satisfaction. The study was carried out through literature and empirical study. Questionnaire was used to varify the hypothesis based on which the input-process-output with system models were established. The result of hypothesis verification in this study is as follows : First, learning hour and grade showed a positive influence on the students' satisfaction in learning factors. Second reliant of professor, recognized teaming participate, and contents showed a positive influence on the students' satisfaction in system factors. Third, an interesting findings emerged throughout the analysis, showed that process variables were rather meaning factor than input variables.

• Korean Management Science Review
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• v.33 no.3
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• pp.105-117
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• 2016

In this paper, we present empirical testing result to examine the validity of inbound supply and outbound demand risk factors in the sense of early predicting the firm's bankruptcy risk level. The risk factors are drawn from industry uncertainty attributes categorized as uncertainties of input market (inbound supply), and product market (outbound demand). On the basis of input-output table, industry level inbound and outbound sectors are identified to formalize supply chain structures, relevant inbound and outbound uncertainty attributes and corresponding risk factors. Subsequently, publicly available macro-economic indicators are used to appropriately quantify these risk factors. Total 68 industry level bankruptcy risk forecasting results are presented with the average R-square scores of between 53.4% and 37.1% with varying time lag. The findings offers useful insights to incorporate supply chain risk to the body of firm's bankruptcy risk level prediction literature.

• Architectural research
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• v.24 no.1
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• pp.1-11
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• 2022

As the occurrence of a crime is dependent on different factors, their correlations are beyond the ordinary cognitive range. Owing to this limitation, systems face difficulty in correlating various factors, thereby requiring the assistance of artificial intelligence (AI) to overcome such limitations. Therefore, AI has become indispensable for crime prediction. Crimes can cause severe and irrevocable damage to a society. Recently, big data has been introduced for developing highly accurate models for crime prediction. Prediction of night crimes should be given significant consideration, because crimes primarily occur during nights, when the spatiotemporal characteristics become vulnerable to crimes. Many environmental factors that influence crime rate are applied for crime prediction, and their influence on crime rate may differ based on temporal characteristics and the nature of crime. This study aims to identify the environmental factors that influence sex and theft crimes occurring at night and proposes an artificial neural network (ANN) model to predict sex and theft crimes at night in random areas. The crime data of A district in Seoul for 12 years (2004-2015) was used, and environmental factors that influence sex and theft crimes were derived through multiple regression analysis. Two types of crime prediction models were developed: Type A using all environmental factors as input data; Type B with only the significant factors (obtained from regression analysis) as input data. The Type B model exhibited a greater accuracy than Type A, by 3.26 and 9.47 % higher for theft and sex crimes, respectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.601-604
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• 2000

In this paper, we compare the classification performance of both data fusion and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. Since the relationship between input & output is not typically known, we use Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: Clustering based logistic regression turns out to provide the highest classification accuracy when input variables are weakly correlated and the variance of data is high. When there is high correlation among input variables, variable bagging performs better than logistic regression. When there is strong correlation among input variables and high variance between observations, bagging appears to be marginally better than logistic regression but was not significant.

• Journal of the military operations research society of Korea
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• v.34 no.1
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• pp.61-77
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• 2008

Data Envelopment Analysis(DEA) is a promising methodology to evaluate the relative efficiency of the decision-making units. We have compared the efficiency of six electric power generation companies in Korea using DEA. The analysis results by input-oriented CCR and BCC models are summarized as follows: first, different results were acquired between using input factors as total capacity of generators and as sub-totals of generator capacity based on primary energy sources. It is the result influenced by input factors which are characterized by the proportion of fixed costs(generating facilities) and variable costs(generation costs for primary energy), Second, the efficiency will be increased if the input factors selected, according to primary energy sources discussed in this research, are used during long-term expansion of electric power capacity plans. It is expected that this approach can give a feedback for management of electric power generation companies.

• Structural Engineering and Mechanics
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• v.37 no.4
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• pp.351-365
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• 2011

This study proposes an inverse estimation method for the input forces of a fixed beam structural system. The estimator includes the fuzzy Kalman Filter (FKF) technology and the fuzzy weighted recursive least square method (FWRLSM). In the estimation method, the effective estimator are accelerated and weighted by the fuzzy accelerating and weighting factors proposed based on the fuzzy logic inference system. By directly synthesizing the robust filter technology with the estimator, this study presents an efficient robust forgetting zone, which is capable of providing a reasonable trade-off between the tracking capability and the flexibility against noises. The period input of the fixed beam structure system can be effectively estimated by using this method to promote the reliability of the dynamic performance analysis. The simulation results are compared by alternating between the constant and adaptive and fuzzy weighting factors. The results demonstrate that the application of the presented method to the fixed beam structure system is successful.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.337-344
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• 2017

In the offshore crane system, the requirements on the operating safety are extremely high due to many external factors. Rope extension is one of the factors producing vertical vibration of load. In this study, the load is carried by the motor-winch actuator control and the rope is modeled as a mass-damper-spring system. To control the load position and suppress the vertical vibration of the load, a control system based on input-output linearization method is proposed. By the simulation and experiment results with pilot crane model, the effectiveness of proposed control method is evaluated and verified.