• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.5
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• pp.496-510
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• 2016

Simulation technology is a type of shipbuilding product lifecycle management solution used to support production planning or decision-making. Normally, most shipbuilding processes are consisted of job shop production, and the modeling and simulation require professional skills and experience on shipbuilding. For these reasons, many shipbuilding companies have difficulties adapting simulation systems, regardless of the necessity for the technology. In this paper, the data model for shipyard production simulation model generation was defined by analyzing the iterative simulation modeling procedure. The shipyard production simulation data model defined in this study contains the information necessary for the conventional simulation modeling procedure and can serve as a basis for simulation model generation. The efficacy of the developed system was validated by applying it to the simulation model generation of the panel block production line. By implementing the initial simulation model generation process, which was performed in the past with a simulation modeler, the proposed system substantially reduced the modeling time. In addition, by reducing the difficulties posed by different modeler-dependent generation methods, the proposed system makes the standardization of the simulation model quality possible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1058-1076
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• 2013

The WBAN(Wireless Body Area Network) supplies mobile convenience to our medical services. But if we have few effective control variables across this service deployment, the hidden distortions or defects of the system might threaten the lives and rights of the stakeholders. Therefore we need to increase the service credibility, to get WBAN effective. This study proposes a governance mechanism using feasible variables that are currently in use in practices in WBAN environments against medical incidents. Control variables were tested in Seoul National University hospital and related medical industries of South Korea. We assume that WBAN systems would be open based on integrating patients, medical employees and law enforcements to get smart theater operations against medical incidents by implementing proposed MJA(Multilateral Joint Analysis) model. MJA model also contributes to the convergence of computer systems and medical services by demonstrating flexible SOA(Service Oriented Architecture) dashboard of healthcare services with credibility factors in medicine. The important components in MJA model across WBAN, were found to be "Safety, Accuracy and Reliability" in priority order. Factor analysis, correlations and ANOVA were used to evaluate this model and an IT dashboard with a realization of mobile application, was used to support participants' decision-making.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1097-1098
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• 2006

This study investigated the needs and effectiveness of the application of Computer-Aided Systems Engineering Tool in order to enhance the chance of success of the large and complex system development projects like City Train System. Furthermore, it was shown that the merits of Systems Engineering and Project Management must be complementary to each other in their interaction in a project. Especially, for the project plans must be executed based on the fully understood system being developed, the technical and management data of the system development need be integrated and be able to support exact and rapid decision making of project planning. As an alternative solution approach, a model for development knowledge capture integrating both technical and management data of system development was proposed using Computer Aided Systems Engineering tool-Cradle.

• Journal of Computing Science and Engineering
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• v.7 no.1
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• pp.1-20
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• 2013

Over the past generation, data warehousing and online analytical processing (OLAP) applications have become the cornerstone of contemporary decision support environments. Typically, OLAP servers are implemented on top of either proprietary array-based storage engines (MOLAP) or as extensions to conventional relational DBMSs (ROLAP). While MOLAP systems do indeed provide impressive performance on common analytics queries, they tend to have limited scalability. Conversely, ROLAP's table oriented model scales quite nicely, but offers mediocre performance at best relative to the MOLAP systems. In this paper, we describe a storage and indexing framework that aims to provide both MOLAP like performance and ROLAP like scalability by essentially combining some of the best features from both. Based upon a combination of R-trees and bitmap indexes, the storage engine has been integrated with a robust OLAP query engine prototype that is able to fully exploit the efficiency of the proposed storage model. Specifically, it utilizes an OLAP algebra coupled with a domain specific query optimizer, to map user queries directly to the storage and indexing framework. Experimental results demonstrate that not only does the design improve upon more naive approaches, but that it does indeed offer the potential to optimize both query performance and scalability.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.115-126
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• 2006

The purpose of this study is to develop an urban inundation model using GIS(geographic information system). The model is combining a storm sewer system model and a overland-flow model for the estimation inundation depth in urban area caused by the surcharge of storm sewers. SWMM(storm water management model) was employed to resolve the storm sewer flow and to provide the overflow hydrographs caused by the failure of a drainage system due to the shortage of drainage capacity. The level-pool overland-flow model and DEM based overland-flow model were used to calculate the detail inundation zones and depths due to the surcharge on overland surface. The simulation results can help the decision preventing flood damages by redesigning and enlarging the capacities of storm sewer systems in the inundation-prone areas. The model can also be applied to make the potential inundation area map and establish flood-mitigation measures as a part of the decision support system for flood control authority.

• Convergence Security Journal
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• v.13 no.3
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• pp.71-77
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• 2013

In our country security industry biz model analysis methodology fragmentary theory exists, but it is hard to find a comprehensive analysis methodology. Biz model analysis IT companies the external factors and internal factors to integrate the information gathered about the comprehensive analysis of the development of an information system are required. Information support system early in the software architecture of the system design decisions early decision as the design, development, testing, maintenance, has a lasting impact on the project as a guideline in the development of a framework of design abstraction. BMO evaluation support information systems architecture designs system purposes. The mission must support the execution. Information system stakeholders to determine the mission and the environment. All information systems architecture shall have architecture. Technology architecture should be documented with each other can be used. Determine the architecture based architecture descriptions are presented.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.111-118
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• 2024

In general network-based intrusion detection system is designed to detect malicious behavior directed at a network or its resources. The key goal of this paper is to look at network data and identify whether it is normal traffic data or anomaly traffic data specifically for accounting information systems. In today's world, there are a variety of principles for detecting various forms of network-based intrusion. In this paper, we are using supervised machine learning techniques. Classification models are used to train and validate data. Using these algorithms we are training the system using a training dataset then we use this trained system to detect intrusion from the testing dataset. In our proposed method, we will detect whether the network data is normal or an anomaly. Using this method we can avoid unauthorized activity on the network and systems under that network. The Decision Tree and K-Nearest Neighbor are applied to the proposed model to classify abnormal to normal behaviors of network traffic data. In addition to that, Logistic Regression Classifier and Support Vector Classification algorithms are used in our model to support proposed concepts. Furthermore, a feature selection method is used to collect valuable information from the dataset to enhance the efficiency of the proposed approach. Random Forest machine learning algorithm is used, which assists the system to identify crucial aspects and focus on them rather than all the features them. The experimental findings revealed that the suggested method for network intrusion detection has a neglected false alarm rate, with the accuracy of the result expected to be between 95% and 100%. As a result of the high precision rate, this concept can be used to detect network data intrusion and prevent vulnerabilities on the network.

• Korean Medical Education Review
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• v.24 no.3
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• pp.193-204
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• 2022

One of the important roles of medical schools is to support medical students in deciding upon their future career path or choosing their specialty. The purpose of this study is to suggest a career advising model and strategies for medical students through a systematic approach. This study consists of three parts. The first part introduces some main career theories: super's career development theory, career decision-making theory, social cognitive career theory, and ecosystem theory. The second part proposes a systematic career advising model using the results acquired from previous studies and theories. This model considers a medical school as a social system that consists of two domains (internal and external). This social system is considered as a complex where various factors interact with each other: students' individual characteristics, institutional policies and culture, curriculum and learning experience, students' perceived specialty characteristics, and aspects of the external environment such as healthcare systems. The third part suggests some career advising strategies based on a systematic approach that medical schools can apply. These research results can be used for designing career advising courses for medical students, integrating various career advising programs and resources of medical schools, and evaluating the outcomes of career advising programs at an institutional level.