• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1401-1409
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• 1999

In this paper, a conceptual framework of a new concept of protectability is proposed, which indicates the protection level of the system. Evaluation attributes have been identified and a hierarchical evaluation model has been established. Dempster-Shafer Theory of Evidence is applied in combining multiple uncertain judgements to produce an aggregated evaluation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.3-8
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• 2006

This paper discusses current challenges, as a result of the rapid increase in air travel, and future navigation needs of Civil Aviation. The objectives pursued by ANASTASIA, a sixth framework European Commission project, are presented. The methods used in the derivation of the navigation performance requirements are introduced and discussed in the context of precision approaches. High-level impacts on the avionics receiver of integrating additional multi-frequency ranging signals from a modernized GPS and Galileo into the current navigation architecture are investigated. Expected performance achievements are presented.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.171-174
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• 2022

Weakly-supervised learning is a widely adopted approach in video anomaly detection whereby only video labels are utilized instead of expensive frame-level annotations. Since the success of multi-instance learning (MIL), almost all recent approaches are based on maximizing the margin between the set of abnormal video snippets and those of normal video snippets. In this work, we present a simple contrastive approach for weakly supervised video anomaly detection (WS-VAD) with aims to enhance the performance of existing models. The method is generic in nature and introduces a loss function to encourage attraction of output features from the same video class and repel those from different video classes. Experimental results demonstrate our method can be applied to existing algorithms to improve detection accuracy in public video anomaly dataset.

• Journal of the Korean Mathematical Society
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• v.59 no.2
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• pp.217-233
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• 2022

Although machine learning shows state-of-the-art performance in a variety of fields, it is short a theoretical understanding of how machine learning works. Recently, theoretical approaches are actively being studied, and there are results for one of them, margin and its distribution. In this paper, especially we focused on the role of margin in the perturbations of inputs and parameters. We show a generalization bound for two cases, a linear model for binary classification and neural networks for multi-classification, when the inputs have normal distributed random noises. The additional generalization term caused by random noises is related to margin and exponentially inversely proportional to the noise level for binary classification. And in neural networks, the additional generalization term depends on (input dimension) × (norms of input and weights). For these results, we used the PAC-Bayesian framework. This paper is considering random noises and margin together, and it will be helpful to a better understanding of model sensitivity and the construction of robust generalization.

• Journal of KIISE:Software and Applications
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• v.37 no.7
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• pp.503-517
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• 2010

Service-oriented computing, the effective paradigm for developing service applications by using reusable services, becomes popular. In service-oriented computing, service consumer has no responsibility for managing services, just invokes services what service providers are producing. On the other hand, service providers should manage any resources and data for service consumers can use the service anytime and anywhere. However, it is hard service providers manage the quality of the services because an unspecified number of service consumers. Therefore, service scalability for providing services with higher quality of services specified in a service level agreement becomes a potential problem in service-oriented computing. There have been many researches for scalability in network, database, and distributed computing area. But a research about a definition of service scalability and metrics of measuring service scalability is still not mature in service engineering area. In this paper, we construct a service network which connects multiple service nodes, and integrate all the resources to manage it. And we also present a service scalability framework for managing service scalability by using a mechanism of service migration or replication. In section 3, we, firstly, present the structure of the scalability management framework and basic functionalities. In section 4, we propose scalability enhancement mechanism which is needed to release functionality of the framework. In section 5, we design and implement the framework by using proposed mechanism. In section 6, we demonstrate the result of our case study which dynamically manages services in multi-nodes environment by applying our framework. Through the case study, we show the applicability of our scalability management framework and mechanism.

• International Journal of Contents
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• v.13 no.3
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• pp.25-31
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• 2017

With tremendous advancement of information and communication technologies, mobile learning systems have been widely adopted in language learning contexts, and several frameworks have been developed for identifying and categorizing different factors of mobile-assisted language learning (MALL). However, pre-existing frameworks have limitations when evaluating the importance level of criteria. The purpose of this study is to develop a comprehensive hierarchical framework for identifying and categorizing success factors of MALL and prioritizing them according to the importance level. To do that, AHP method is used to quantitatively estimate weight values of MALL criteria. Results reveal that the priority of MALL criteria is ordered as follows: content, system, learner, language learning. Local weights of each criterion are also analyzed; for example, usefulness, accuracy, and authenticity are critical factors for improving MALL contents. Ease of use and mobility of MALL systems are also considered more critical than other systematic factors. In addition, availability of immediate feedback and self-directness has the highest weight values of importance. The findings of the study are discussed regarding hierarchical orders of MALL criteria and conclude that successful MALL implementation may be achieved if related elements are diversely measured and evaluated. Pedagogical implications and suggestions for further research are also presented.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.5
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• pp.735-747
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we propose to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collect a new video dataset and propose a procedure to calculate refined rainfall depth from the original meteorological data. We also propose to utilize the differential frame as well as the optical flow image for better recognition of rainfall depth. Under the Temporal Segment Networks framework, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. The final model is able to achieve high performance in the single-location low sensitivity classification task and reasonable accuracy in the higher sensitivity classification task for both the single-location and the multi-location case.

• Earthquakes and Structures
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• v.11 no.5
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• pp.905-924
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• 2016

Several two-dimensional analytical beam column joint models with varying complexities have been proposed in quantifying joint flexibility during seismic vulnerability assessment of non-ductile reinforced concrete (RC) frames. Notable models are the single component rotational spring element and the super element joint model that can effectively capture the governing inelastic mechanisms under severe ground motions. Even though both models have been extensively calibrated and verified using quasi-static test of joint sub-assemblages, a comparative study of the inelastic seismic responses under nonlinear time history analysis (NTHA) of RC frames has not been thoroughly evaluated. This study employs three hypothetical case study RC frames subjected to increasing ground motion intensities to study their inherent variations. Results indicate that the super element joint model overestimates the transient drift ratio at the first story and becomes highly un-conservative by under-predicting the drift ratios at the roof level when compared to the single-component model and the conventional rigid joint assumption. In addition, between these story levels, a decline in the drift ratios is observed as the story level increased. However, from this limited study, there is no consistent evidence to suggest that care should be taken in selecting either a single or multi component joint model for seismic risk assessment of buildings when a global demand measure such as maximum inter-storey drift is employed in the seismic assessment framework.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.192-196
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• 2018

The mobile agent paradigm can be exploited in a variety of ways, ranging from low-level system administration tasks to middle ware to user-level applications. Mobile agents can be useful in building middle-ware services such as active mail systems, distributed collaboration systems, etc. An active mail message is a program that interacts with its recipient using a multimedia interface, and adapts the interaction session based on the recipient's responses. The mobile agent paradigm is well suitable to this type of application, since it can carry a sender-defined session protocol along with the multimedia message. Mobile agent communication is possible via method invocation on virtual references. Agents can make synchronous, one-way, or future-reply type invocations. Multicasting is possible, since agents can be aggregated hierarchically into groups. A simple check-pointing facility has also been implemented. Another proposed solution is to use multi agent computer systems to access, filter, evaluate, and integrate this information. We will present the overall architectural framework, our agent design commitments, and agent architecture to enable the above characteristics. Besides, the each information needed a mobile agent system such as text, graphic, image, audio and video etc, constructed a great capacity multimedia database system. However, they have problems in establishing connections over multiple subnetworks, such as no end-to-end connections, transmission delay due to ATM address resolution, no QoS protocols. We propose a new connection management scheme in the thesis to improve the connection management involved of mobile agent systems.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.253-261
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• 2013

This study analyzed the preparation characteristics for old age of the baby boomers by the framework of the multi-pillar pension system. Analysis results are as follows. First, multi-pillar pension system's subscription rates of baby boomers was public pension 59%, private pension 11.5% and retirement pension 1.5%. The baby boomers isn't ready for old age life. Second, women and people with the low level of education are less prepared for old age. Third, people in a bad health state are less prepared for old age. Forth, low-income people are less prepared for old age. We must support baby boomers' preparations for old age by establishing income security system for old age. We must establish public pension support policy for the people of the low level of education and economic hierarchy, women, bad health status people, and must introduce universal old-age allowance policy for guaranteeing the minimum income of baby boomers.