• ETRI Journal
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• v.42 no.6
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• pp.965-975
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• 2020

This paper proposes a new framework for the development and deployment of honeypots for evolving malware threats. As new technological concepts appear and evolve, attack surfaces are exploited. Internet of things significantly increases the attack surface available to malware developers. Previously independent devices are becoming accessible through new hardware and software attack vectors, and the existing taxonomies governing the development and deployment of honeypots are inadequate for evolving malicious programs and their variants. Malware-propagation and compromise methods are highly automated and repetitious. These automated and repetitive characteristics can be exploited by using embedded reinforcement learning within a honeypot. A honeypot for automated and repetitive malware (HARM) can be adaptive so that the best responses may be learnt during its interaction with attack sequences. HARM deployments can be agile through periodic policy evaluation to optimize redeployment. The necessary enhancements for adaptive, agile honeypots require a new development and deployment framework.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.57-57
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• 1988

This paper develops an adaptive scheduling policy for flexible manufacturing systems. The inductive learning methodology used for constructing this state-dependent scheduling policy provides and understanding of the relative importance of the various system parameters in determining the appropriate scheduling rule. Experimental studies indicated the superiority of the suggested approach over the alternative approach involving the repeated application of a single scheduling rule for randomly generated test problems as well as a real system, and under both stationary and nonstationary conditions. In particular, its relative performance improves further when there are frequent disruptions, and when disruptions are caused by the introduction of tiiight due date jobs, one of the most common surces of disruptions in most manufacturing systems.

• Korean Management Science Review
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• v.13 no.1
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• pp.57-70
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• 1996

This paper develops an adaptive scheduling policy for flexible manufacturing systems. The inductive learning methodology used for constructing this state-dependent scheduling policy provides and understanding of the relative importance of the various system parameters in determining the appropriate scheduling rule. Experimental studies indicated the superiority of the suggested approach over the alternative approach involving the repeated application of a single scheduling rule for randomly generated test problems as well as a real system, and under both stationary and nonstationary conditions. In particular, its relative performance improves further when there are frequent disruptions, and when disruptions are caused by the introduction of tiiight due date jobs, one of the most common surces of disruptions in most manufacturing systems.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.39-48
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• 2021

This study aimed to analyze the level of professors' understanding and perception of adaptive learning and proposed how college can implement successful adaptive learning in college classes. For research purposes, online survey was conducted by 162 professors of A university in capital region. As a result, professors seemed to feel pressure to provide students personalized feedback and gave concerned that students don't study enough in advance before participating in class. It was also found that professors realized that they have low level of understanding about adaptive learning, while they revealed intention to make use of adaptive learning in their class. They also answered that adaptive learning system is the most helpful support for encouraging professors to apply adaptive learning in real class. We proposed what is required to encourage professor to implement adaptive learning in their class.

• Journal of Environmental Policy
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• v.5 no.4
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• pp.19-49
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• 2006

As global climate change is expected to influence regional water resources, water resource managers need to establish adaptive management to cope with climate change. We examined adaptive management efforts in the US, UK, Canada, Australia, and the Netherlands. Each country is implementing different levels of adaptation efforts based on current water management practices, institutional arrangements, as well as the varying degree of water availability, current climate effects and expected climate change effects. Based on the comparison of these countries, we suggest policy implications for the sustainable water resource management of Korea under climate changes.

• Journal of The Korean Association of Information Education
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• v.26 no.4
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• pp.249-263
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• 2022

The purpose of this study is to investigate the effects of assessment by adopting adaptive learning in higher education that are rarely examined in previous studies. In particular, this study applied research questions: 1) How does technical perception, perceived contents and features, and perceived integration of the AI-based adaptive system with lecture affect overall satisfaction, overall effectiveness, overall usefulness, overall motivation for the study, and intention to use it with other classes? 2) How do overall satisfaction, overall effectiveness, overall usefulness, motivation for the class, and intention to use affect loyalty on the AI-based adaptive system? This study conducted online surveys after the completion of the classes adopted AI-based adaptive learning system, ALEKS. This study applied ANOVA, regression, and factor analyses. The results of this study found that perceived integration of the AI-based adaptive learning system with the lectures on overall satisfaction, effectiveness, motivation, and intention to use for other classes showed significant with higher effect size. The results of this study provides implication that the AI-based learning system help improve learning outcomes in graduate level studies. The results provide policy and managerial implications that the AI-based adaptive learning system should improve better customer relationships in higher education.

• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1207-1236
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• 2018

This paper explores the life cycle of innovation cluster, especially focussing on the Korean representative innovation cluster, Daedeok Innopolis. For this purpose, we review theoretically how an innovation cluster has been growing up. In particular, we discuss how a cluster has been formed and activated by governmental innovation policies from an evolutionary perspective. By doing so, the study identifies the typical features of an innovation cluster according to each dimensions of the cluster life cycle. The results of this study are as follows: First, in this study, Daedeok Innopolis has characteristics of latency, emergence, growth, and maturity from evolutionary perspective. Second, the governmental structure of the Daedeok Innopolis is a strong government-led and top-down structure, which has features of inclusiveness and flexibility such as umbrella policy. Third, the Daedeok Innopolis can be seen that adaptive or renewal development, as while, it can be applied fine adjustment the innovation cluster policy towards the recognition of innovation obstacle at each dimensions of the life cycle. Therefore, these discussions expose what kind of policy interventions should be addressed to form and develop the innovation cluster according to the cluster life cycle, as while, the development of adaptive policies during the risk and take-off period. Ultimately, the study provides that a different kind of policy instruments and tools should be implemented according to innovation cluster development and its distinctive characteristic per each dimensions of the cluster life cycle.

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.87-107
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• 2018

With more than 10 million inhabitants, in particular, Seoul, the capital of Korea, has already experienced a number of severe heat wave. To alleviate the potential impacts of heat wave and the vulnerability to heat wave, policy-makers have generally considered the option of heat wave strategies containing adaptation elements. From the perspective of sustainable planning for adaptation to heat wave, the objective of this study is to identify the elements of vulnerability and assess heat wave-vulnerability at the dong level. This study also performs an exploratory investigation of the spatial pattern of vulnerable areas in Seoul to heat wave by applying exploratory spatial data analysis. Then this study attempts to select areas with the relatively highest and lowest level of adaptive capacity to heat wave based on an framework of climate change vulnerability assessment. In our analysis, the adaptive capacity is the relatively highest for Seongsan-2-dong in Mapo and the relatively lowest for Changsin-3-dong in Jongno. This study sheds additional light on the spatial patterns of heat wave-vulnerability and the relationship between adaptive capacity and heat wave.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.49-61
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• 2017

Transactional Memory (TM) has greatly changed the parallel programming paradigm for transaction processing and is classified into STM, HTM, HyTM according to hardware or software frameworks. However, the existing studies have a problem that they provide static retry policy for all workloads. To solve the problems, we propose an hybrid transactional memory scheme using sampling-based adaptive retry policy in multi-core environment. First, the proposed scheme determines whether to use STM or HTM according to the characteristic of a transaction. Otherwise, it executes HTM and STM concurrently by using a bloom filter. Second, the proposed scheme provides adaptive retry policy for HTM according to the characteristic of transactions in each workload. Finally, through the experimental performance evaluation using STAMP, the proposed scheme shows 10~20% better performance than the existing schemes.

• Journal of Information Technology Services
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• v.19 no.5
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• pp.15-31
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• 2020

This study explores the process in which employees adopt the information security policy. The results of this study, which surveyed 234 employees in three call centers and four hospitals, show that the employees adapt the information security policy through the social structuring process suggested by the AST model. In particular, this study identifies roles of two appropriation activities (FOA : Faithfulness of Appropriation & COA : Consensus on Appropriation) observed in the social structuring process. Regarding to the interactions between the two appropriation activities, FOA, which indicates a better understanding of the information security policy, is examined as a more critical factor than COA, which indicates the degree of agreement among employees about how to use it. FOA not only has a direct effect on compliance intention toward the information security policy, but also indirectly through COA, whereas COA has only a indirect effect through FOA. This result shows that, in order for a company to successfully implement a new information security policy, it is important for employees to understand its purpose and intention. The adaption of information security policy through two appropriation activities is observed in both hospitals and call centers, but due to the different working environments, there were differences in the preceding variables affecting the appropriation activities. The results of this study are expected to provide guidelines for companies who want to successfully adopt information security policy.