• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

• 한국디지털정책학회:학술대회논문집
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• 2006.06a
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• pp.197-204
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• 2006

This paper tried to develop differentiation strategies of policy process in governance. Firstly, we reviewed model of policy making(output-oriented model and process-oriented model, normative or idealistic approach and realistic or empirical approach, rational model and cognitive model etc). Now gumi city is making the policy based on the process-oriented model, realistic or empirical approach, cognitive model. So gumi city was winner the test of provinces innovation in 2005. Therefore, when we make the policy, consider these factor: citizen and public service personnel participate policy making process and control policy quality.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.1
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• pp.313-336
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• 2016

The study reviews theoretical and empirical research literature in information needs, seeking and uses in order to search for the most pertinent metatheories for studying information practices of the disadvantaged. The study examines the salient features and main theories/models of each cognitive, affective and social approach in the user-centered paradigm through analyzing prior information practices studies. While analyzing the main features of each cognitive, affective and social approach, the study points out the limitation of research using the cognitive and affective approaches to fail to theorize the relationship between individuals and complex and dynamic socio-cultural contexts in information practices. As an alternative, the study suggests using the social approach as a pertinent metatheory for understanding information practices of the disadvantaged who are entangled with myriad social contexts and issues. In order to verify the pertinence, the study examines the advantages of the social approach through analyzing both the main models related to everyday information practices under social constructionism and the main findings from information practices of the disadvantaged.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.17-24
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• 2023

Given the surge in the elderly population, and increasing in dementia cases, there is a growing interest in digital therapies that facilitate steady remote treatment. However, in the cognitive assessment of digital therapies through clinical trials, the absence of log data as an essential evaluation factor is a significant issue. To address this, we propose a solution of utilizing weighted derived variables based on high-importance variables' accuracy in log data utilization as an indirect cognitive assessment factor for digital therapies. We have validated the effectiveness of this approach using machine learning techniques such as XGBoost, LGBM, and CatBoost. Thus, we suggest the use of log data as a rapid and indirect cognitive evaluation factor for digital therapy users.

• The Journal of Information Systems
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• v.27 no.3
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• pp.25-42
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• 2018

Purpose The purpose of this study focused on adopting production systems in cognitive psychology to improve the extraction process of persuasive design characteristics for healthcare-related mobile applications. Design/Methodology/Approach A research approach with four stages was developed. We developed and updated the evaluation guideline for persuasive design characteristics (PDC). We tried to summarize and analyze each of 28 PDC and prepared related production rules. Verification process for both guideline approach and production system approach were performed. Top one hundred apps from both medical category and health and Fitness category were selected and evaluated by two approaches. By comparing the results of the two approaches, we tried to explain the improvement and reliability of introducing the production system in the PDC extraction process. Findings Based on the updated guideline for healthcare-related mobile applications, a production system in cognitive psychology was developed. By comparing the PDC extraction results by two approaches, production system showed a better improvement for evaluation precision and efficiency for decision-making process. The findings of this study can be used for researchers and app developers to apply production system to analyze, evaluate, and develop better healthcare-related apps with persuasion.

• Korean Journal of Cognitive Science
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• v.1 no.2
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• pp.241-253
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• 1989

• Korean Journal of Cognitive Science
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• v.6 no.4
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• pp.5-20
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• 1995

• ETRI Journal
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• v.42 no.1
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• pp.36-45
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• 2020

A priority-based data communication approach, developed by employing cognitive radio capacity for sensor nodes in a wireless terrestrial sensor network (TSN), has been proposed. Data sensed by a sensor node-an unlicensed user-were prioritized, taking sensed data importance into account. For data of equal priority, a first come first serve algorithm was used. Non-preemptive priority scheduling was adopted, in order not to interrupt any ongoing transmissions. Licensed users used a nonpersistent, slotted, carrier sense multiple access (CSMA) technique, while unlicensed sensor nodes used a nonpersistent CSMA technique for lossless data transmission, in an energy-restricted, TSN environment. Depending on the analytical model, the proposed wireless TSN environment was simulated using Riverbed software, and to analyze sensor network performance, delay, energy, and throughput parameters were examined. Evaluating the proposed approach showed that the average delay for sensed, high priority data was significantly reduced, indicating that maximum throughput had been achieved using wireless sensor nodes with cognitive radio capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.331-343
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• 2015

We propose a distributed medium access control protocol for cognitive radio networks to opportunistically utilize multiple channels. Under the proposed protocol, cognitive radio nodes forecast and rank channel availability observing primary users' activities on the channels for a period of time by time series analyzing using smoothing models for seasonal data by Winters' method. The proposed approach protects primary users, mitigates channel access delay, and increases network performance. We analyze the optimal time to sense channels to avoid conflict with the primary users. We simulate and compare the proposed protocol with the existing protocol. The results show that the proposed approach utilizes channels more efficiently.

• Korean Journal of Child Studies
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• v.21 no.2
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• pp.33-44
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• 2000

In this study, a random sample of 111 six-year-old children were assigned to one of 3 experimental conditions: categorization training using cognitive apprenticeship, categorization training using metacognitive procedures, and no categorization training. Level of intelligence was measured by Raven's(1986) Coloured Progressive Matrics(CPM). No difference was found between apprenticeship and metacognitive training in the high CPM children. In the middle and low CPM levels, cognitive apprenticeship training was more efficient than metacognitive training. This indicates that cognitive apprenticeship, which emphasizes the thinkaloud procedure of both the experts and the novice though modeling and coaching for self-implementation, is a more effective approach than the metacognitive approach for categorization in middle and low CPM children.