• Ocean and Polar Research
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• v.40 no.1
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• pp.37-48
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• 2018

The purpose of this study is to assess the climate change vulnerability of coastal and offshore fisheries in the South Sea of Korea using the RCP scenarios. Based on the vulnerability defined by IPCC, the indicator-based method was applied. Exposure indicator was calculated through weighted sum of the sea temperature and salinity forecasted by National Institute of Fisheries Science, and the weights were obtained from the time-space distribution of each fisheries. Sensitivity indicator was determined by applying the catch proportion of fisheries to the sensitivity of fish species. The adaptive capacity was measured by survey of fisheries which represent the ability of the fishermen well. As a result of summarizing the above indicators, vulnerability of coastal fisheries is higher than offshore fisheries. This shows that measures against coastal fisheries are needed. In addition, the results of each scenario are somewhat different, so it is considered that accurate prediction of climate change is important for adaptation measures.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.131-133
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• 2014

본 논문에서는 서비스업의 매장에 설치된 POS(Point of sale) 또는 Smart device를 이용하여 빈 방 또는 빈 테이블 등의 서비스 가능 공간 수에 따라 실시간으로 가격이 변동되는 시스템을 제안한다. 고객 입장에서는 보다 싼 가격으로 서비스를 이용할 수 있으며, 매장주 입장에서는 한산한 시간에 경쟁력 있는 가격으로 고객을 유치할 수 있도록 도움을 준다. 고객은 애플리케이션에 접속하여 위치기반서비스를 통해 이용하고자하는 서비스 매장을 선택하여 실시간으로 변동되는 서비스 가격을 확인할 수 있으며, 예약 및 결제를 한 후, 일정 시간 내에 해당 매장에 가서 서비스를 이용할 수 있다. 매장주는 POS 또는 Smart device를 통해 자동 또는 수동으로 서비스 가격을 변동시킬 수 있다.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.5
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• pp.341-351
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• 2019

The purpose of this study was to evaluate vulnerability of drought in small island areas. Vulnerability assessment factors of drought were selected by applying the factor analysis. Ninety Eup/Myon areas in small island were evaluated to vulnerability of drought by entropy method adapting objective weights. Vulnerability consisted of climate exposure, sensitivity, and adaptive capacity. A total of 22 indicators were used to evaluate and analyze vulnerability of drought in small island areas. The results of entropy method showed that winter rainfall, no rainfall days, agricultural population rate, cultivation area rate, water supply rate and groundwater capacity have a significant impact on drought assessment. The overall assessment of vulnerability indicated that Seodo-myeon Ganghwa-gun, Seolcheon-myeon Namhae-gun and Samsan-myeon Ganghwa-gun were the most vulnerable to drought. Especially Ganghwa-gun should be considered policy priority to establish drought measures in the future, because it has a high vulnerability of drought.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• Journal of IKEEE
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• v.25 no.4
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• pp.598-606
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• 2021

In this paper, we presents a new service binding and resource management model for context based services in mobile edge computing (MEC) networks. The proposed control is composed of two layers: MEC service bindng control layer (MCL) and user context control layer (UCL). The MCL manages service binding construction, resource allocation, and service policy construction from a system point of view; and the UCL manages real-time service adaptation using meta-objects. Through simulations, we confirmed that the proposed control offers enhanced throughput and content transfer time when it is compared to the legacy computing and control models. The proposed control model can be employed as a key component for the context based various internet-of-things (IoT) services in MEC environments.

• Korean Journal of Social Welfare
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• v.64 no.2
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• pp.31-54
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• 2012

Along with increasing mothers' employment, work-family reconciliation has been recognised as a key policy agenda in contemporary welfare states. Although various policy instruments have been introduced and expanded in recent years, the problem of time allocation within couples still remains as a fundamental issue, which has been largely underresearched at a micro perspective. In this context, this study aims to identify dominant types of work-family time allocation within married couple, and to apply these types to the Korean case using the fuzzy-set ideal type analysis. Further, a series of multiple regression analyses will be implemented to find factors affecting each ideal type of work-family time allocation. The 1999 and 2009 Korea Time Use Survey datasets will be adopted for the analyses. Married couples are selected as samples only when men work 40 hours or more per week and they have at least one pre-school child. Empirical analyses cover three parts. First of all, four ideal types on work-family time allocation are classified by intersecting two core variables - the ratio of men's (paid) working and family (caring time plus domestic work) time to total working and family time. In this research, the four types will be labelled the traditional male breadwinner model (TM, high working and low family time), the dual burden model (DB, shared working but low family time), the family-friendly male breadwinner model (FM, high working but shared family time), and the adaptive partnership model (AP, shared working and shared family time). By comparing the composition of the four ideal types in 1999 and 2009, it will examine the trend of work-family time allocation in Korea. In addition, multiple regressions will be useful for investigating which characteristics contribute to the different degree of each fuzzy ideal score in the four models. Finally, policy implications and further research agenda will be discussed.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.672-680
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• 2003

A shopbot is a software agent whose goal is to maximize buyer´s satisfaction through automatically gathering the price and quality information of goods as well as the services from on-line sellers. In the response to shopbots´ activities, sellers on the Internet need the agents called pricebots that can help them maximize their own profits. In this paper we adopts Q-learning, one of the model-free reinforcement learning methods as a price-setting algorithm of pricebots. A Q-learned agent increases profitability and eliminates the cyclic price wars when compared with the agents using the myoptimal (myopically optimal) pricing strategy Q-teaming needs to select a sequence of state-action fairs for the convergence of Q-teaming. When the uniform random method in selecting state-action pairs is used, the number of accesses to the Q-tables to obtain the optimal Q-values is quite large. Therefore, it is not appropriate for universal on-line learning in a real world environment. This phenomenon occurs because the uniform random selection reflects the uncertainty of exploitation for the optimal policy. In this paper, we propose a Mixed Nonstationary Policy (MNP), which consists of both the auxiliary Markov process and the original Markov process. MNP tries to keep balance of exploration and exploitation in reinforcement learning. Our experiment results show that the Q-learning agent using MNP converges to the optimal Q-values about 2.6 time faster than the uniform random selection on the average.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.23-34
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• 2017

This study investigated relative explanation of social support, ego-resiliency and stress coping strategies to help adaptive coping style of school-dropout adolescents under stress situation. To this end, 101 school-dropout adolescents were surveyed by visiting and requesting the outofschool youth supporting project, youth detention center, and adolescent protective and treatment facilities in Daejeon, Cheongnam, and Chungbuk. As analysis methods, descriptive statistical analysis, pearson's correlation, and hierarchical analysis were conducted and the research results are as follows. First, stress coping strategies showed positive relationship with social support and ego-resiliency. Second, a variable that showed greater explanation power for stress coping strategies was the environmental variable, the social support. Third, it was identified that there was greater explanation power when the environmental variable, the social support, and the personal variable, the ego-resiliency, were put in at the same time for stress coping strategies. According to the result, this study implies that schools, community, national policy effort and systemetic approach are required as well as improvement of personal coping capabilities in order to overcome difficulties school-dropout adolescents face.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.367-376
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• 2007

In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1852-1859
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• 2016

The effectiveness of a binarization algorithm in image processing depends on how to eliminate the uncertainty of determining threshold in a reasonable way and on minimizing information loss due to the binarization effect. Fuzzy binarization technique was proposed to handle that uncertainty with fuzzy logic. However, that method is known to be inefficient when the given image has low intensity contrast. In this paper, we propose an improved fuzzy binarization method to overcome such known drawbacks. Our method proposes a trapezoid type fuzzy membership function instead of most-frequently used triangle type one. We also propose an adaptive ${\alpha}$_cut determination policy. Our proposed method has less information loss than other algorithms since we do not use any stretching based preprocessing for enhancing the intensity contrast. In experiment, our proposed method is verified to be more effective in binarization with less information loss for many different types of images with low intensity contrast such as night scenery, lumber scoliosis, and lipoma images.