• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.171-176
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• 2022

A dramatic rise in the number of people dying from heart disease has prompted efforts to find a way to identify it sooner using efficient approaches. A variety of variables contribute to the condition and even hereditary factors. The current estimate approaches use an automated diagnostic system that fails to attain a high level of accuracy because it includes irrelevant dataset information. This paper presents an effective neural network with convolutional layers for classifying clinical data that is highly class-imbalanced. Traditional approaches rely on massive amounts of data rather than precise predictions. Data must be picked carefully in order to achieve an earlier prediction process. It's a setback for analysis if the data obtained is just partially complete. However, feature extraction is a major challenge in classification and prediction since increased data increases the training time of traditional machine learning classifiers. The work integrates the CNN-MDRP classifier (convolutional neural network (CNN)-based efficient multimodal disease risk prediction with TANFIS (tuned adaptive neuro-fuzzy inference system) for earlier accurate prediction. Perform data cleaning by transforming partial data to informative data from the dataset in this project. The recommended TANFIS tuning parameters are then improved using a Laplace Gaussian mutation-based grasshopper and moth flame optimization approach (LGM²G). The proposed approach yields a prediction accuracy of 98.40 percent when compared to current algorithms.

• Proceedings of KOSOMES biannual meeting
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• 2003.05a
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• pp.59-67
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• 2003

The prevention of marine accidents has been a major topic in marine society for long time and various safety policies and Countermeasures have been developed and applied to prevent those accidents. In spite of these efforts, however significant marine accidents have taken place intermittently. Ship is being operated under a highly dynamic environments and many factors are related with ship's collision and those factors are interacting. So, the analysis on ship's collision causes are very important to prepare countermeasures which will ensure the safe navigation. This study analysed the ship's collision data over the past 10 years(1991-2000), which is compiled by Korea Marine Accidents Inquiry Agency. The analysis confirmed that ‘ship's collision’ is occurred most frequently and the cause is closely related with human factor. The main purpose of this study is to propose risk control countermeasures of ship's collision. For this, the structure of human factor is analysed by the questionnaire methodology. Marine experts were surveyed based on major elements that were extracted from the human factor affecting to ship's collision. FSM has been widely adopted in modeling a dynamic system which is composed of human factors. Then, the structure analysis on the causes of ship's collision using FSM are performed. This structure model could be used in understanding and verifying the procedure of real ship's collision. Furthermore it could be used as the model to prevent ship's collision and reduce marine accidents.

• Journal of the Korean Society of Marine Environment & Safety
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• v.9 no.1
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• pp.51-56
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• 2003

The prevention of marine accidents has been a major topic in marine society for long time and various safety policies and Countermeasures have been developed and applied to prevent those accidents. In spite of these efforts, however significant marine accidents have taken place intermittently. Ship is being operated under a highly dynamic environments and many factors are related with ship's collision and those factors are interacting. So, the analysis on ship's collision rouses are very important to prepare countermeasures which will ensure the safe navigation. This study analysed the ship's collision data over the past 10 years(1991-2000), which is compiled by Korea Marine Accidents Inquiry Agency. The analysis confirmed that ‘ship's collision’ is occurred most frequently and the cause is closely related with human factor. The main purpose if this study is to propose risk control countermeasures of ship's collision. For this, the structure of human factor is analysed by the questionnaire methodology. Marine experts were surveyed based on major elements that were extracted from the human factor affecting to ship's collision FSM has been widely adopted in modeling a dynamic system which is composed of human factors. Then, the structure analysis on the rouses of ship's collision using FSM are performed. This structure model could be used in understanding and verifying the procedure of real ship's collision. Furthermore it could be used as the model to prevent ship's collision and to reduce marine accidents.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.83-89
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• 2021

The RMF (Cyber Security Risk Management Framework) is a more strengthened U.S. defense cybersecurity framework that is currently used throughout the U.S. federal government beyond the defense sector. In the past decade, the proportion of cyber warfare in non-regular warfare encountered by the United States, especially cyberattacks caused by China and North Korea, has been increasing. In the end, the U.S. is newly establishing an RMF system to prepare a more strengthened cybersecurity policy at the pan-government level, and the U.S. Department of Defense aims to expand the U.S. defense RMF evaluation policy beyond the federal government level. The South Korean military has already applied RMF at the request of the U.S. that notified the policy to apply RMF when obtaining F-35A. The application of RMF by the Korean military is no longer inevitable. Now is the time for the Korean military to seriously think about what to prepare for the early establishment of a successful Korean RMF system.

• Journal of Navigation and Port Research
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• v.27 no.2
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• pp.137-143
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• 2003

The prevention of marine accidents has been a important topic in marine society for long time, and various safety policies and countermeasures have been developed and applied to prevent those accidents. In spite of these efforts, however, significant marine accidents have taken place intermittently. Ship is being operated under a highly dynamic environments, and many factors are related with ship's collision, whose factors are interacting. So, the analysis on ship's collision causes are very important to prepare countermeasures which will ensure the safe navigation. This study analysed the ship's collision data over the past 10 years(1991-2000), which is compiled by Korea Marine Accidents Inquiry Agency. The analysis confirmed that‘ship's collision’is occurred most frequently and the cause is closely related with human factor. The main purpose of this study is to analyse human factor. For this, the structure of human factor is analysed by the questionnaire methodology. Marine experts were surveyed based on major elements that were extracted from the human factor affecting to ship's collision. FSM has been widely adopted in modeling a dynamic system which is composed of human factors. Then, the structure analysis on the causes of ship's collision using FSM are performed. This structure model could be used in understanding and verifying the procedure of real ship's collision. Furthermore it could be used as the model to prevent ship's collision and reduce marine accidents.

• Journal of Distribution Science
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• v.13 no.4
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• pp.9-19
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• 2015

Purpose - This study focuses on the use of evaluative criteria software for imprecise market information, and product mapping relationships between design parameters and customer requirements. Research design, data, and methodology - This study involved using the product predicted value method, synthesizing design alternatives through a morphological analysis and plan, realizing the synthesis in multi-criteria decision-making (MCDM), and using its searching software capacity to obtain optimal solutions. Results - The establishment of product designs conforms to the customer demand, and promotes the optimization of several designs. In this study, the construction level analytic method and the simple multi attribute comment, or the quantity analytic method are used. Conclusions - This study provides a solution for enterprise products' multi-goals decision-making, because the product design lacks determinism, complexity, risk, conflict, and so on. In addition, the changeable factor renders the entire decision-making process more difficult. It uses Fuzzy deduction and the correlation technology for appraising the feasible method and multi-goals decision-making, to solve situations of the products' multi-goals and limited resources, and assigns resources for the best product design.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.285-289
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• 2012

In a coastal area, all of the vessels are always exposed to the potential risk, taking into the maritime accident statistics account over the last decades. To manage vessels underway safety, the characteristics of ship movements in a fairway should be recognized by VTS system or VTS operators. The IMO has already mandated the shipboard carriage of AIS since 2004, as stated in SOLAS Chapter V Regulation 19. As a result, the static and dynamic information of AIS data has been collected for vessel traffic management in the coastal areas and used for VTS. This research proposes a simple algorithm of recognizing potentially risky ships by observing their trajectories on the fairway. The static and dynamic information of AIS data are collected and the curvature for the ship trajectory is surveyed. The proposed algorithm finds out the irregularity of ship movement. The algorithm effectively monitors the change of navigation pattern from the curvature analysis of ship trajectory. Our method improves VTS functions in an intelligent way by analyzing the navigation pattern of vessels underway.

• Journal of Navigation and Port Research
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• v.27 no.5
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• pp.493-498
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• 2003

Ship is being operated under a highly dynamic environments and many factors are related with ship's collision and those factors are interacting. So, An analysis on the ship's collision muses is very important to prepare countermeasures which will ensure the safe navigation. And the analysis confirmed that ship's collision is occurred most frequently and the muse is closely related with human factor. The main purpose of this study is to build a model of human factors in ship's collision muse using SD(System Dynamics} approach and to measure a effect which is risk control countermeasures of ship's collision. To achieve this aim, the structure analysis on the muses of ship's collision using FSM are performed, and the structure was changed by quantitative, qualitative factors and their feedback loops in casual map. This model was performed over 20 years(1993-2012) in a standard simulation model and 8 policy simulation models.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.107-117
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• 2015

As the demand for urban business hotel has increased in the recent years due to the sharp rise in overseas tourists, the potential of business hotel development has gained in financial attention for the real estate investment. However, its concept and business domain has not been defined, and none of investment guidance for the development has not been clarified. Accordingly, this report intends to define the concept of urban business hotel in perspective of real estate investment through prior case studies and literature review, and provide the structure of determinants which control its investment decisions. Furthermore, this study develops the weight of determinants depending on the type of investment, and evaluate the two actual projects in urban area of Seoul, differed from investment type: direct and indirect, based on AHP and Fuzzy methodologies. Research finding indicate that the financial factors affecting the sales and tour business condition factors are critical determinants regardless of investment type. And it is notable that the direct investment perspective pays more attention on the finance and investment associated determinants while the indirect one more focuses on the regional and environmental ones. From the analysis of case evaluation, it is also noteworthy that the direct investors turn out to be more conservative than indirect investors due to the risk of equity capital investment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.268-276
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• 2015

A ship's sailing route or plan is determined by the master as the decision maker of the vessel, and depends on the characteristics of the navigational environment and the conditions of the ship. The trajectory, which appears as a result of the ship's navigation, is monitored and stored by a Vessel Traffic Service center, and is used for an analysis of the ship's navigational pattern and risk assessment within a particular area. However, such an analysis is performed in the same manner, despite the different navigational environments between coastal areas and the harbor limits. The navigational environment within the harbor limits changes rapidly owing to construction of the port facilities, dredging operations, and so on. In this study, a support vector machine was used for processing and modeling the trajectory data. A K-fold cross-validation and a grid search were used for selecting the optimal parameters. A complicated traffic route similar to the circumstances of the harbor limits was constructed for a validation of the model. A group of vessels was composed, each vessel of which was given various speed and course changes along a specified route. As a result of the machine learning, the optimal route and voyage data model were obtained. Finally, the model was presented to Vessel Traffic Service operators to detect any anomalous vessel behaviors. Using the proposed data modeling method, we intend to support the decision-making of Vessel Traffic Service operators in terms of navigational patterns and their characteristics.