• Journal of Korean Society of societal Security
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• v.1 no.1
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• pp.69-79
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• 2008

Operational continuity is not a simple issue that can be solved by a Back-Up center or an alternate site. Strategic issues including law, standards, etc demand a new approach in terms of the operational continuity management (OCM). Also, it is necessary to develop a new framework of OCM governance as a part of the corporate governance. Experts from corporate governance insist that OCM can be included in the corporate operational control and so it is important to set up a strategy for OCM in the organization. This paper describes how OCM governance suggests two aspects of effectively controlling corporate risks in the viewpoint of corporate governance. First of all, the top corporate management develops the strategy of operational continuity with regard to the corporate governance. Secondly, there is the aspect of how to build up and manage the strategy of operational continuity in the corporations.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.753-757
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• 2015

This paper introduces an experimental rescue robot, HUBO T-100 and presents the optimal motion control method. The objective of the rescue robot is to extract patients or wounded soldiers in the battlefield and hazardous environments. Another mission is to dispose and transport an explosive ordnance to safe places. To execute these missions, the upper body of the rescue robot is humanoid in form to execute various kinds of tasks. The lower body features a hybrid tracked/legged design, which allows for a variety of mode of locomotion, depending on terrain conditions in order to increase traversability. The weight lifting motion is one of the most important task for performing rescue related missions because the robot must lift an object or impaired person lying on the ground for transferring. Here, dynamics based motion optimization is employed to minimize joint torques while maintaining stability simultaneously. Physical experiments with a real humanoid robot, HUBO T-100, are presented to verify the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1155-1168
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• 2016

This paper considers a probability density estimation problem of climate values. In particular, we focus on estimating probability densities of summer extreme temperature over South Korea. It is known that the probability density of climate values at one location is similar to those at near by locations and one doesn't follow well known parametric distributions. To accommodate these properties, we use a mixture of conditional autoregressive species sampling model, which is a nonparametric Bayesian model with a spatial dependency. We apply the model to a dataset consisting of summer maximum temperature and minimum temperature over South Korea. The dataset is obtained from University of East Anglia.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.759-767
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• 2006

Firstly, this study aimed to identify differential characteristics of alternative tourists by comparing socioeconomic and travel characteristics, ecotourism cognition level and intention to participate in ecotourism, and eco-friendly travel attitudes between alternative tourists and mass tourists visiting Jeju Island. Secondly, it aimed to evaluate the possibility of the Jeju experimental forests managed by Warm Temperate Forest Center as an alternative tourism destination. The results shown that alternative tourists had more positive travel attitude and higher level of cognition of ecotourism and intention of participate in ecotourism than mass tourist. The cognition level and the intention of visit the experimental forests were also higher in alternative tourists group. In addition, alternative tourists were more active and participatory in nature-oriented activities, and evaluated themselves culture and nature oriented tourists. Thus, it is required to keep monitoring the alternative tourists' distinctive characteristics and to reflect those in developing and managing alternative tourism destinations.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.246-254
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• 2020

In this paper, we propose a learning based compressive sensing algorithm for the purpose of side scan sonar image denoising. The proposed method is based on Iterative Shrinkage and Thresholding Algorithm (ISTA) framework and incorporates a powerful strategy that reinforces the non-linearity of deep learning network for improved performance. The proposed method consists of three essential modules. The first module consists of a non-linear transform for input and initialization while the second module contains the ISTA block that maps the input features to sparse space and performs inverse transform. The third module is to transform from non-linear feature space to pixel space. Superiority in noise removal and memory efficiency of the proposed method is verified through various experiments.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.543-548
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• 2019

The tonal signal caused by the machinery component of a vessel such as an engine, gearbox, and support elements, can be modeled as a sparse signal in the frequency domain. Recently, compressive sensing based techniques that recover an original signal using a small number of measurements in a short period of time, have been applied for the tonal frequency detection. These techniques, however, cannot avoid a basis mismatch error caused by the discretization of the frequency domain. In this paper, we propose a method to detect the tonal frequency with a small number of measurements in the continuous domain by using the atomic norm minimization technique. From the simulation results, we demonstrate that the proposed technique outperforms conventional methods in terms of the exact recovery ratio and mean square error.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.1-11
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• 2021

In this paper, we explain the purpose of building a mobile app called "ARnetView" that can use the AR(augmented Reality)based calling function and AR based content creation function, and as well as an AR based data center that can share AR based video streaming and AR based contents on smartphones and tablet devices. For the AR(Augmented Reality) based data center implement, we have developed a mobile application and implemented a service system including an AR(augmented Reality) based calling function and AR based content production and AR based video streaming functions for real-time communication to connect a field technician and an expert so that the expert can see and discuss the situation in the field and technician and experts, they can draw digital annotation on mobile screen that accurately stick to 3D physical objects, allowing the expert to guide the technician step by step. In result, it provides a remote technical collaboration environment between field technician and expert. In addition, AR(Augmented Reality) collaboration service Platform was designed and implemented to increase work speed, efficiency, and utilization of advanced technicians, improve continuous productivity of equipment and facilities, maximize equipment and facility utilization, and strengthen industrial competitiveness. Therefore, through this, the AR collaboration service Platform can be applied to the industrial field, the medical field, and the entertainment/education field.

• Journal of Science Education
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• v.45 no.2
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• pp.201-218
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• 2021

The purpose of this study is to investigate qualitatively two cases of general citizens' scientific participation and activities responding to fine dust problem. The processes of their scientific actions were investigated and categorized inductively based on three stages: problem recognition stage, information collection and analysis stage, and sharing and spreading stage. As a result, in the 'problem recognition' stage, two participants recognized the seriousness of the fine dust problem as they felt a threat to their health and began to act practically by questioning the accuracy of public data. In the 'information collection and analysis' stage, a participant collected as much information as possible and compared them in order to obtain more accurate information for her situation. On the other hand, another participant conducted various experiments in person to get the information which is appropriate to his situation. Finally, in the 'Sharing and Spreading' stage, both participants created and shared various materials based on online environment, and continued their activities with a sense of contribution through others assistance. Educational implications are discussed in terms of civic science education and scientific literacy.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.460-465
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• 2021

In active sonar, time delay estimation is used to find the distance between the target and the sonar. Among the time delay estimation methods for active sonar, estimation in the frequency domain is widely used. When estimating in the frequency domain, the time delay can be thought of as a frequency estimator, so it can be used relatively easily. However, this method is prone to rapid increase in error due to noise. In this paper, we propose a new method which applies weighted dictionary and sparsity in order to reduce this error increase and we extend it to two receivers to propose an algorithm for estimating the time delay between two receivers. And the case of applying the proposed method and the case of not applying the proposed method including the conventional frequency domain algorithm and Generalized Cross Correlation-Phase transform (GCC-PHAT) in a white noise environment were compared with one another. And we show that the newly proposed method has a performance gain of about 15 dB to about 60 dB compared to other algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.49-63
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• 2019

Crowdedness management at subway platforms is essential to improve services, including the prevention of train delays and ensuring passenger safety. Establishing effective crowdedness mitigation measures for platforms requires accurate estimation of the congestion level. There are temporal and spatial constraints since crowdedness on subway platforms is assessed at certain locations every 1-2 years by hand counting. However, smart cards generate real-time big data 24 hours a day and could be used in estimating congestion. This study proposes a model based on data from transit cards to estimate crowdedness dynamically. Crowdedness was defined as demand, which can be translated into passengers dynamically moving along a subway network. The trajectory of an individual passenger can be identified through this model. Passenger flow that concentrates or disperses at a platform is also calculated every minute. Lastly, the platform congestion level is estimated based on effective waiting areas for each platform structure.