• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.35-48
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• 2022

In this study, it propose a proof theory method for expressing and reasoning knowledge in a multiagent environment. Since this method determines logical results in a mechanical way, it has developed as a core field from early AI research. However, since the proposition cannot always be proved in any set of closed sentences, in order for the logical result to be determinable, the range of expression is limited to the sentence in the form of a clause. In addition, the resolution principle, a simple and strong reasoning rule applicable only to clause-type sentences, is applied. Also, since the proof theory can be expressed as a meta predicate, it can be extended to the metalogic of the proof theory. Metalogic can be superior in terms of practicality and efficiency based on improved expressive power over epistemic logic of model theory. To prove this, the semantic method of epistemic logic and the metalogic method of proof theory are applied to the Muddy Children problem, respectively. As a result, it prove that the method of expressing and reasoning knowledge and common knowledge using metalogic in a cooperative multiagent environment is more efficient.

• The Journal of Internal Korean Medicine
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• v.43 no.4
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• pp.720-737
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• 2022

Objectives: To compare the effectiveness and safety of East Asian traditional medicine treatments (EATMT) versus conventional management in patients following heart valve replacement surgery. Methods: We searched several databases, including the Korean Studies Information Service System, PubMed, China National Knowledge Infrastructure, and Citation Information by NII. The search range included randomized controlled trials from each first issue until June 27, 2021. Two review authors independently extracted the data. We assessed the risk of systematic errors by evaluating risk domains using the "Risk of bias" tool. Results: We included 5 trials in the review. In the EATMT, the investigators reported significant improvements in reshaping of the heart structure: left ventricular end diastolic diameter (MD -4.43, 95% CI -6.06 to -2.79; 130 participants; 2 studies; high evidence). Comparisons with usual care revealed a significant decrease in gastrointestinal complications rate (OR 0.30, 95% CI 0.20 to 0.47; 503 participants; 2 studies; high evidence). We assessed 4 studies as having a low risk of bias and 1 study as having a high risk of bias. Conclusion: This systematic review suggests that East Asian traditional medicine interventions may be effective in preventing and alleviating complications, but we found evidence of important trade-offs between known benefits and known adverse effects in cardiac dysfunction and inflammation following heart valve replacement. Consequently, additional high-quality studies should be conducted.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.2
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• pp.95-103
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• 2022

Objectives This study was conducted to assess the effect of chuna manual therapy after hip arthroplasty. Methods We searched across 9 electronic databases (PubMed, Cochrane Library, Wangfang data, China National Knowledge Infrastructure [CNKI], Oriental Medicine Advanced Searching Integrated System [OASIS], National Digital Science Library [NDSL], Korean Medical Database [KMBASE], Koreanstudies Information Service System [KISS], Research Information Sharing Service [RISS]) to find randomized controlled clinical trials for chuna manual therapy after hip arthroplasty. Results On inclusion criteria, 11 appropriate studies were included and analyzed. The deep vein thrombosis incidence of the chuna manual therapy group was statistically lower than the conventional treatment group (p=0.0002). Chuna manual therapy significantly improved the Harris hip score compared with conventional treatment (p<0.00001). Also, chuna manual therapy combined with herbal fumigation therapy significantly elevated the hip joint function score of Harris hip score compared with the conventional therapy group (p<0.00001). Conclusions The systematic review showed that chuna manual therapy had significant effects on hip arthroplasty. Nonetheless, considering the high risk of bias and geographic bias, further research with well-designed studies is required to support the effectiveness of chuna manual therapy.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.27-40
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• 2022

Medical AI, which has lately made significant advances, is playing a vital role, such as assisting clinicians with diagnosis and decision-making. The field of chest X-rays, in particular, is attracting a lot of attention since it is important for accessibility and identification of chest diseases, as well as the current COVID-19 pandemic. However, despite the vast amount of data, there remains a limit to developing an effective AI model due to a lack of labeled data. A research that used federated learning on chest X-ray data to lessen this difficulty has emerged, although it still has the following limitations. 1) It does not consider the problems that may occur in the Non-IID environment. 2) Even in the federated learning environment, there is still a shortage of labeled data of clients. We propose a method to solve the above problems by using the self-supervised learning model as a global model of federated learning. To that aim, we investigate a self-supervised learning methods suited for federated learning using chest X-ray data and demonstrate the benefits of adopting the self-supervised learning model for federated learning.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.489-502
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• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Journal of Korean Public Health Nursing
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• v.37 no.1
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• pp.5-24
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• 2023

Purpose: The objective of this review was to identify the research trends in Information and Communication Technology (ICT)-based health-related intervention studies for children and adolescents published in South Korea over the past 10 years. Methods: A scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) and the system classification framework for digital health intervention 1.0 of the World Health Organization (WHO) was applied to analyze how technology was being used to support the needs of the health system. Results: A total of 18 studies were included in the final analysis. The participants were mainly children with a variety of diseases. No studies had used innovative technology platforms such as artificial intelligence (AI), the Internet of Things (IoT), and robotics. In addition, the scope of application of the WHO classification criteria was quite limited. Finally, no intervention study considered technical operational indicators, such as the number of website visits and streaming as outcome measurements. Conclusions: Researchers should introduce advanced technology-based strategies to provide customized and professional healthcare services to children and adolescents in South Korea and continue efforts to integrate innovative ICT for various research purposes, subjects, and environments.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.1-10
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• 2009

The field of the web service orchestration introduced to generate a valuable service by reusing single services. Recently, it suggests rule-based searching and composition by the AI (Artificial Intelligence) instead of simple searching or orchestration based on the IOPE(Input, Output, Precondition, Effect) to implement the Semantic web as the web service of the next generation. It introduce a AOP programming paradigm from existing object-oriented programming paradigm for more efficient modularization of software. In this paper, we design a dynamic web service orchestration and invocation scheme applying Aspect-Oriented Programming (AOP) and Reflection for Semantic web. The proposed scheme makes use of the Reflection technique to gather dynamically meta data and generates byte code by AOP to compose dynamically web services. As well as, our scheme shows how to execute composed web services through dynamic proxy objects generated by the Reflection. For performance evaluation of the proposed scheme, we experiment on search performance of composed web services with respect to business logic layer and user view layer.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.9-15
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• 2009

Ant Colony System is new meta heuristic for hard combinatorial optimization problem. The original ant colony system accomplishes a pheromone updating about only the global optimal path using global updating rule. But, If the global optimal path is not searched until the end condition is satisfied, only pheromone evaporation happens to no matter how a lot of iteration accomplishment. In this paper, the length of the global optimal path does not improved within the limited iterations, we evaluates this state that fall into the local optimum and selects the next node using changed parameters in the state transition rule. This method has effectiveness of the search for a path through diversifications is enhanced by decreasing the value of parameter of the state transition rules for the select of next node, and escape from the local optima is possible. Finally, the performance of Best and Average_Best of proposed algorithm outperforms original ACS.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1055-1065
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• 2023

Recently, various studies using deep reinforcement learning (deep RL) technology have been conducted to solve complex problems using big data collected at industrial internet of things. Deep RL uses reinforcement learning"s trial-and-error algorithms and cumulative compensation functions to generate and learn its own data and quickly explore neural network structures and parameter decisions. However, studies so far have shown that the larger the size of the learning data is, the higher are the memory usage and search time, and the lower is the accuracy. In this study, model-agnostic learning for efficient federated deep RL was utilized to solve privacy invasion by increasing robustness as 55.9% and achieve 97.8% accuracy, an improvement of 5.5% compared with the comparative optimization-based meta learning models, and to reduce the delay time by 28.9% on average.

• Information Systems Review
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• v.20 no.1
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• pp.115-135
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• 2018

The growing interest in the privacy paradox involving discussions about discrepancy between attitude and behavior led to an increase in the number of studies on the topic. An in-depth theoretical review of the privacy paradox is essential to promote qualitative growth of domestic research in the privacy paradox. In this study, we conducted literature review of existing domestic studies in the privacy paradox. The results of this study showed that the quantity and the quality of research showed marked improvement. Earlier studies primarily focused on the existence of the privacy paradox phenomenon, but existing studies on the causes of the phenomenon gradually increased. Despite the use of various methodologies and analytical tools to investigate the causes of the privacy paradox, research in privacy paradox remains in its infancy. Further efforts are needed to achieve qualitative growth, and further studies should be conducted to introduce the behavioral economic approach. This approach posits that bounded rationality could contribute to a clear understanding of the privacy paradox and the academic development of the privacy field.