• Journal of the Korea Convergence Society
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• v.8 no.3
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• pp.265-273
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• 2017

The purpose of this study was to investigate the relationship among social support, career decision-making self-efficacy, and career decision level in golf majors. For this purpose, a survey was given to a convenience sample of 215 students in universities in Seoul and its metropolitan areas. The data were then analyzed using descriptive statistics, correlations, and multiple regression analysis. The major findings of this study were as follows. First, social support had a significant effect on the career decision-making self-efficacy of golf majors. Second, social support had a significant effect on the career decision level of golf majors. Third, career decision-making self-efficacy had a significant effect on the career decision level of golf majors. The results of this study may be helpful to provide empirical evidence on the roles of social supports and career decision-making self-efficacy needed to decide golf majors' career path.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.275-280
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• 2018

Companies are now rapidly entering the realm of the realtime economy named 'Now Economy'. 'Now Economy' features the measurement and assessment, accelerating speed of decision making about business. According to this, companies intend to change their disposition to be able to make quick and accurate decision by gathering informations rapidly and correctly, and then by processing that. Applications of ICT can be possible to change the new decision system of companies. In this thesis, the new decision system through amalgamations of BPMS, Mobile, Cloud Service, Hadoop, BI and AI is presented. It will be able to make decision quickly and accurately by collecting all information between the most efficiently managed process and formal and informal data inside company through this, and then by combining changes with situations outside company.

• ETRI Journal
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• v.37 no.5
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• pp.1032-1043
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• 2015

ETRI's Co-Pilot project is aimed at the development of an automated vehicle that cooperates with a driver and interacts with other vehicles on the road while obeying traffic rules without collisions. This paper presents a core block within the Co-Pilot system; the block is named "Co-Pilot agent" and consists of several main modules, such as road map generation, decision-making, and trajectory generation. The road map generation builds road map data to provide enhanced and detailed map data. The decision-making, designed to serve situation assessment and behavior planning, evaluates a collision risk of traffic situations and determines maneuvers to follow a global path as well as to avoid collisions. The trajectory generation generates a trajectory to achieve the given maneuver by the decision-making module. The system is implemented in an open-source robot operating system to provide a reusable, hardware-independent software platform; it is then tested on a closed road with other vehicles in several scenarios similar to real road environments to verify that it works properly for cooperative driving with a driver and automated driving.

• Journal of Digital Convergence
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• v.18 no.9
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• pp.159-167
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• 2020

This study was intended to examine how the job stress of enterpriser affects decision quality when they make rational decision making, and to empirical analysis on whether decision quality can be enhanced through corporate network and absorption capacity. For this purpose, 356 survey data were collected from small business enterpriser and analyzed using SPSS v.25 and AMOS v.24. Studies have shown that among job stress, challenging stress has positive(+) influence on decision quality, disturbing stress has negative(-) influence on decision quality, and both corporate network and absorption capacity have positive(+) influence on decision quality. In addition, challenge stress and hindrance stress have been shown to have a positive(+) influence on decision quality through corporate network and absorption capacity. These findings confirmed that the challenge factors of job stress had a positive effect on decision quality, and confirmed that the corporate network and absorption capacity were important factors in enhancing decision-making products. As such, conclusions were discussed and implications and directions for follow-up studies were presented.

• Journal of Korean Association for Spatial Structures
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• v.3 no.3 s.9
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• pp.67-74
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• 2003

The purpose of this study is to improve convergence speed of topology optimization procedure using the existing ESO method and to deal with topology decision of the truss structures according to a boundary condition, such as cantilever type. At the existing ESO topology optimization procedure for the truss structures, the adjustment of member sizes according to target stress has been executed by increasing or reducing a very small value from each member size. In this case, it takes too much iteration till convergence. Accordingly, it is practically hard to obtain optimum topology for a large scale structures. For that reason, it is necessary to improve convergence speed of ESO method more effectively. During the topology decision procedure, member sizes are adjusted by calculating approximate solution for member sizes corresponding to the target stress at every step, the new member sizes are adjusted by such method are applied in FEA procedure of next step.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.97-104
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• 2024

Leukemia induced death has been listed in the top ten most dangerous mortality basis for human being. Some of the reason is due to slow decision-making process which caused suitable medical treatment cannot be applied on time. Therefore, good clinical decision support for acute leukemia type classification has become a necessity. In this paper, the author proposed a novel approach to perform acute leukemia type classification using sequential neural network classifier. Our experimental result only covers the first classification process which shows an excellent performance in differentiating normal and abnormal cells. Further development is needed to prove the effectiveness of second neural network classifier.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2451-2458
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• 1997

Adaptive channel equalization complished without resorting to a training sequence is known as blind equalization. In this paper, in order to increase the speed of the convergence and to reduce the steady-state mean squared error simulatneously, we propose the multi-stage DD(decision-direct) algorithm derived from the combination of the Sato algorithm and the decision-directed algorithm. In the starting stage, the multi-stage DD algorithm is identical to the Sato algorithm which guarantees the convergence of the equalizer. As the blind equalizer converges, the number of the level of the quantizers is increased gradally, so that the proposed algorithm operates identical to the decision-directed algorithm which leads to the low error power after the convergence. Therefore, the multi-stage DD algorithm obtains fast convergence rate and low steady state mean squared error.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.365-372
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• 2018

This study was conducted to investigate the influence of nursing professional value and career decision self efficacy on senior nursing students' job seeking stress. Subjects were 225 senior nursing students. Data were analyzed using descriptive statistics, Pearson's Correlation Coefficient, multiple regression with SPSS/WIN 22.0. As a result, There was significant positive correlation between nursing professional value and career decision self efficacy and negative correlation between and job seeking stress. Career decision self efficacy was significant factor predicting job seeking stress and accounted for 18% of the variance. Therefore, it is necessary to develop strategies for enhancing career decision self efficacy in order to reduce job seeking stress in senior nursing students.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1083-1090
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• 2022

Since renal cell carcinoma(RCC) has various examination and treatment methods according to clinical stage and histopathological characteristics, it is required to determine accurate and efficient treatment methods in the clinical field. However, the process of collecting and processing RCC medical data is difficult and complex, so there is currently no AI-based clinical decision support system for RCC treatments worldwide. In this study, we propose a clinical decision support system that helps clinicians decide on a precision treatment to each patient. RCC standard big database is built by collecting structured and unstructured data from the standard common data model and electronic medical information system. Based on this, various machine learning classification algorithms are applied to support a better clinical decision making.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.276-281
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• 2011

This paper presents a method of constructing the switching function using edge-valued decision diagrams. The proposed method is as following. The edge-valued decision diagram is a new data structure type of decision diagram which is recently used in constructing the digital logic systems based on the graph theory. Next, we apply edge-valued decision diagram to function minimization of digital logic systems. The proposed method has the visible, schematic and regular properties.