• International journal of advanced smart convergence
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• v.11 no.4
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.1129-1143
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• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.1-8
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• 2003

The operation and management of a plant require proper accounting for the constraints coming from reliability requirements as well as from budget and resource considerations. Most of the mathematical methods to decide the inspection time interval for plant maintenance by reliability theory are too complicated to be solved. Moreover, the mathematical and theoretical models are not usually cases in the practical applications. In order to overcome these problems, we propose a new the decision-making method of optimal inspection interval to minimize the maintenance cost by reliability theory and genetic algorithm (GA). The most merit of the proposed method is to decide the inspection interval for a plant machine of which failure rate $\lambda$(t) conforms to any probability distribution. Therefore, this method is more practical. The efficiency of the proposed method is verified by comparing the results obtained by GA-based method with the inspection model haying regular time interval.

• Journal of Korean Academy of Nursing
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• v.42 no.4
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• pp.453-465
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• 2012

Purpose: The study was done to develop a shared decision-making scale for end-of-life patients in Korea. Methods: The process included construction of a conceptual framework, generation of initial items, verification of content validity, selection of secondary items, preliminary study, and extraction of final items. The participants were 388 adults who lived in one of 3 Korean metropolitan cities: Seoul, Daegu, or Busan. Item analysis, factor analysis, criterion related validity, and internal consistency were used to analyze the data. Data collection was done from July to October 2011. Results: Thirty-four items were selected for the final scale, and categorized into 7 factors explaining 61.9% of the total variance. The factors were labeled as sharing information (9 items), constructing system (7 items), explanation as a duty (5 items), autonomy (4 items), capturing time (3 items), participation of family (3 items), and human respect (3 items). The scores for the scale were significantly correlated among shared decision-making scale, terminating life support scale, and dignified dying scale. Cronbach's alpha coefficient for the 34 items was .94. Conclusion: The above findings indicate that the shared decision-making scale has a good validity and reliability when used for end-of-life patients in Korea.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.91-105
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• 2008

Nowadays, circulation industry is taking charge of important role in improvement of competitive power on the manufacturing industry and public welfare increase of consumer, price stabilization, employment creation and so on. A lot of research have been progressing for formation of total circulation complex, but decision making for selection of location on some facility is only calculated the optimum value when correct data values are inserted. However, a lot of decision making is accomplished in situation that have little knowledge of objective and constraints and as real world is also evaluated inclusive of analyst's subjectivity about variable, indefinite and fuzzy part, so it is decreasing a reliability on evaluation result and complicating objective evaluation on various effect and negative impact. Accordingly, from under like this situation, this study is to develop location decision model of circulation complex using fuzzy theory from the intention for the most reasonable decision making in fuzzy situation based on decision making problem on conventional location and size decision that did to be satisfactory constraints necessarily.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.172-180
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• 2021

The purpose of this study is to analyze the structural relationship among perfectionism and dance achievement of middle and high school students majoring in dance. Specifically, this study aims to investigate the effects of perfectionism on dance achievement through the medium of dance commitment and career decision-making self-efficacy. For this purpose, a structural equation model based on the previous studies was constructed with perfectionism as an exogenous variable and dance commitment, career decision-making self-efficacy, and dance achievement as endogenous variables. The final subjects of this study were 279 middle and high school students majoring in dance. The data were processed by frequency analysis to find out personal characteristics using SPSS 23 and exploratory factor analysis and reliability analysis were conducted on the research tools. In addition, AMOS 21 was used for confirmatory factor analysis, correlation analysis and structural equation model analysis. As a result of data processing on the research model. First, the sub-dimensions of perfectionism tendency 'worry about mistakes', 'personal standard', and 'doubt about behavior' had a statistically significant effect on dance commitment. Second, the sub-dimensions of perfectionism 'worry about mistakes', 'personal standard', and 'doubt about behavior' had statistically significant effects on career decision-making self-efficacy. Third, dance commitment did not have a statistically significant effect on dance achievement, but career decision-making self-efficacy had a statistically significant effect on dance achievement. These results provide implications.

• Journal of the Korea Safety Management & Science
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• v.6 no.4
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• pp.107-122
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• 2004

This study aims to examine the usefulness on the Evaluation Process for the Feasibility & Priority of A Certain Public Projects. and the Methodology used AHP(Analytic Hierarchy Process) which used pairwise comparisons of the alternatives and criteria for solving discrete alternative multicriteria decision problems. In this paper, we present a similar phenomenon, rank reversal problem, when we apply the AHP to group decision making process. The problem is identified by an example problem in that the previous rank order of Public Projects choices. we also present three different methods to prevent the undesirable characteristic of the original AHP in appling to Decision Making Process.

• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.545-552
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• 2006

The purpose of this study is to develop an optimal, long-term planning model for improvement of water distribution networks. The water distribution system is divided into sub-zones and the decision of improvement plan is made for each sub-zone. Costs for replacement, rehabilitation and repair, benefits including reduced pumping and leakage costs, and hydraulic reliability are considered to make optimal decision for improvement planning of water network. Harmony search algorithm is applied to optimize the system and hydraulic analysis model EPANET is interfaced with the optimal decision model to check the hydraulic reliability, The developed model is applied to actual water distribution system in Daegu-city, South Korea. The new model which use durability, conveyance and cost as a decision variable is different from existing methods which use only burying period and pipe type and can be used as optimal decision making system for water distribution network.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.221-230
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• 2022

The purpose of this study is to identify career decision-making types of college students majoring in beauty, and to improve career preparation behaviors by analyzing their effects on career preparation behaviors and major satisfaction. It was conducted from November 1 to 30, 2021, and a total of 485 questionnaires were used as analysis data. Frequency analysis, factor analysis, reliability analysis, correlation analysis, and multiple regression analysis were performed as research methods. As a result of the study, first, the type of career decision-making showed a positive (+) correlation between career preparation behavior and major satisfaction, indicating that it was statistically significant. Second, rational career decision-making style was correlated with dependence and intuitive style. As the career preparation behavior, the career preparation behavior of time effort, ability activity, and information collection, and the satisfaction of the major showed a statistically significant positive (+) correlation in class satisfaction and subject satisfaction. Third, among career decision-making types, rational and dependent types were found to have a statistically significant effect on ability activity, which is a sub-factor of career preparation behavior.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.1
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• pp.25-33
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• 2020

Multipath routing protocols with unmanned aerial vehicles have been proposed to improve reliability in tactical ad hoc networks. Most of existing studies tend to establish the paths with multiple metrics. However, these approaches suffer from link loss and congestion problems according to the network condition because they apply same metric for both ground and air path or employ the simple weight value to combine multiple metrics. To overcome this limitation, in this study, we propose new routing metrics for path over unmanned aerial vehicles and use the multi-criteria decision making (MCDM) method to determine the weight factors between multiple metrics. For the case studies, we extend the ad-hoc on-demand distance vector protocol and propose a strategy for modifying the route discovery and route recovery procedure. The simulation results show that the proposed mechanism is able to achieve high end-to-end reliability and low end-to-end delay in tactical ad hoc networks.