• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.5
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• pp.27-43
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• 2015

Ever more so than any other times, today's corporations today face an ultimate issue of acquiring highest work expertise for their employees. However, most of current academic researches try to focus on what factors comprise an expertise while they fail to tackle the very issue of detailed numerical measurement of the expertise factors recommended improvement paths, and goals for each measured expertise level. Hence, this study suggests more objective and highly reliable identification of work competence measurement factors and the correlation among the identified factors. For details, it tries to propose a methodology of expertise measurement by developing into the definition of experts and expertise, reestablishment of expertise factors, determination of reference points of the expertise factors, and weighting of the factors. This measurement methodology finds that it itself has significant correlation with existing work competency level measurement and test tools. Therefore it is identified to justify its effectiveness. Finally, this study proposes an action point of establishing a national expertise architecture and its frameworks for various societies in general.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.611-618
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• 2003

In this paper, we describe a fuzzy inference approach for detecting and classifying shot transitions in video sequences. Our approach basically extends FAM (Fuzzy Associative Memory) to detect and classify shot transitions, including cuts, fades and dissolves. We consider a set of feature values that characterize differences between two consecutive frames as input fuzzy sets, and the types of shot transitions as output fuzzy sets. The inference system proposed in this paper is mainly composed of a learning phase and an inferring phase. In the learning phase, the system initializes its basic structure by determining fuzzy membership functions and constructs fuzzy rules. In the inferring phase, the system conducts actual inference using the constructed fuzzy rules. In order to verify the performance of the proposed shot transition detection method experiments have been carried out with a video database that includes news, movies, advertisements, documentaries and music videos.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.231-236
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• 2014

The transit time of contrast agents and the parameters of time-intensity curves in ultrasonography are important factors to diagnose various diseases of a digestive organ. We have implemented an automatic parametric imaging method to overcome the difficulty of the diagnosis by naked eyes. However, the micro-bubble noise and the respiratory motions may degrade the reliability of the parameter images. In this paper, we introduce an optimization technique based on MRF(Markov Random Field) model to enhance the quality of the parameter images, and present an image tracking algorithm to compensate the image distortion by respiratory motions. A method to extract the respiration periods from the ultrasound image sequence has been developed. We have implemented the ROI(Region of Interest) tracking algorithm using the dynamic weights and a momentum factor based on these periods. An energy function is defined for the Gibbs sampler of the image enhancement method. Through the experiments using the data to diagnose liver lesions, we have shown that the proposed method improves the quality of the parametric images.

• Smart Media Journal
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• v.9 no.3
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• pp.25-30
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• 2020

The purpose of this paper is to implement a deep learning-based real-time video analysis algorithm that monitors safety of workers in industrial facilities. The worker's clothes were divided into six classes according to whether workers are wearing a helmet, safety vest, and safety belt, and a total of 5,307 images were used as learning data. The experiment was performed by comparing the mAP when weight was applied according to the number of learning iterations for 645 images, using YOLO v4. It was confirmed that the mAP was the highest with 60.13% when the number of learning iterations was 6,000, and the AP with the most test sets was the highest. In the future, we plan to improve accuracy and speed by optimizing datasets and object detection model.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.11
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• pp.1021-1032
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• 2011

This paper presents the results of a parametric study for the design of optimal Earth-Moon transfer trajectory using mixed impulsive and continuous thrust. Various types of the optimal Earth-Moon transfer trajectories were designed by adjusting the relative weight between the impulsive and the continuous thrust, and flight time. Two very different transfer trajectories can be obtained by different combination of design parameters. Furthermore, it was found that all thus designed trajectories permit the ballistic capture by the Moon gravity. Finally, the required thrust profiles are presented and analyzed in detail.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.1
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• pp.20-30
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• 2010

In this paper, a new tomographic scan method with fixed installed detectors and rotating source from gamma projector was presented to diagnose the industrial plants which were impossible to be examined by conventional tomographic systems. Weight matrix calculation method which was suitable for volumetric detector and statistical iterative reconstruction method were applied for reconstructing the simulation and experimental data. Monte Carlo simulations had been performed for two kinds of phantoms. Lab scale experiment with a same condition as one of phantoms, had been carried out. Simulation results showed that reconstruction from photopeak counting measurement gave the better results than from the gross counting measurement although photopeak counting measurement had large statistical errors. Experimental data showed the similar result as Monte Carlo simulation. Those results appeared to be promising for industrial tomographic applications, especially for petrochemical industries.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.301-309
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• 2005

Learning program's behavior using machine learning techniques based on system call audit data is an effective intrusion detection method. Rule teaming, neural network, statistical technique, and hidden Markov model are representative methods for intrusion detection. Among them neural networks are known for its good performance in teaming system call sequences. In order to apply it to real world problems successfully, it is important to determine their structure. However, finding appropriate structure requires very long time because there are no formal solutions for determining the structure of networks. In this paper, a novel intrusion detection technique using evolutionary neural networks is proposed. Evolutionary neural networks have the advantage that superior neural networks can be obtained in shorter time than the conventional neural networks because it leams the structure and weights of neural network simultaneously Experimental results against 1999 DARPA IDEVAL data confirm that evolutionary neural networks are effective for intrusion detection.

• Convergence Security Journal
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• v.20 no.3
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• pp.79-88
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• 2020

Business consignment using personal information is increasing for the operating profit and work efficiency of Internet companies. If the personal information leakage accident occurs at the consignee, the consigner who provided personal information will be damaged greatly. The purpose of this study is to analyze the business attributes of consignee using consigned personal information and present a model that can be used to select companies with high risk of personal information leakage by considering the importance of the involved personal information. For this, personal information consignment relations, consignment services, and personal information items used were analyzed. Social network analysis and cluster analysis were applied to select companies with high network centrality that are advisable to obtain information security certification. The results of this study could be used to establish information protection strategies for private or public enterprises that manage companies using personal information.

• Korean Journal of Construction Engineering and Management
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• v.9 no.5
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• pp.95-103
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• 2008

In recent years, there has been more reconstruction and redevelopment of apartments rather than efforts to consider alternative to extend the life time oh the apartments. It is essential to try to develop ways to adequately maintain and to use the apartment facilities efficiently in order to preserve earth environment and the limited resource. However, lacking research on the effects obtained through remodelling and maintenance have interfered with the vitalizing of the market. The objective of this study is to propose criterions and methods with which to evaluate adequacy of developing method. A survey was performed to investigate important evaluating methods in order to obtain advices that can smoothly progress improve apartment developing method. This study applied AHP(Analytical Hierarchy Process) methods for reasonable dependancy of developing in apartment. Through this study, the flow of apartment market is elevated to reaching the level in advanced nation.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.59-68
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• 2015

In this paper, we proposed a methodology of vulnerability analysis for armored fighting vehicle based on modeling and simulation. The SES/MB framework serves hierarchical representation of the structure for a complex systems and is easy to conduct modeling for the armored fighting vehicle which consists of various components. When the armored fighting vehicle is hit by the shots from threat, the vulnerability of the armored fighting vehicle is decreased by damaged or penetrated level of armors and components. The penetration is determined by the result of comparing a penetration energy through penetration analysis equation and defence ability of armor and components. And the defence ability is determined in accordance with type and defined property of normal component and armor component, all components have a weighted values for the degree of importance. We developed a simulation program for verification proposed methodology. Thus, the program analyzes vulnerability for armored fighting vehicle SES/MB framework using importance.