• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.595-600
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• 2024

As the use of artificial intelligence technologies such as machine learning increases in research fields that predict learning outcomes or optimize learning pathways, the use of artificial intelligence in education is gradually making progress. This research is gradually evolving into more advanced artificial intelligence methods such as deep learning and reinforcement learning. This study aims to improve the method of predicting future learning performance based on the learner's past learning performance-history data. Therefore, to improve prediction performance, we propose conditional probability applying the Markov Chain method. This method is used to improve the prediction performance of the classifier by allowing the learner to add learning history data to the classification prediction in addition to classification prediction by machine learning. In order to confirm the effectiveness of the proposed method, a total of more than 30 experiments were conducted per algorithm and indicator using empirical data, 'Teaching aid-based early childhood education learning performance data'. As a result of the experiment, higher performance indicators were confirmed in cases using the proposed method than in cases where only the classification algorithm was used in all cases.

• Korean Journal of Radiology
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• v.20 no.1
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• pp.83-93
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• 2019

Objective: The purpose of this study was to prospectively investigate the value of the myocardial extracellular volume fraction (ECV) in predicting myocardial functional outcome after revascularization of coronary chronic total occlusion (CTO). Materials and Methods: Thirty patients with CTO underwent cardiovascular magnetic resonance (CMR) before and 6 months after revascularization. Three baseline markers of functional outcome were evaluated in the dysfunctional segments assigned to the CTO vessels: ECV, transmural extent of infarction (TEI), and unenhanced rim thickness (RIM). At the global level, the ECV values of the whole myocardium with and without a hyperenhanced region (global and remote ECV) were respectively measured. Results: In per-segment analysis, ECV was superior to TEI and RIM in predicting functional recovery (area under receiver operating characteristic curve [AUC]: 0.86 vs. 0.75 and 0.73, all p values < 0.010), and it emerged as the only independent predictor of regional functional outcome (odds ratio [OR] = 0.83, 95% confidence interval [CI]: 0.77-0.89; p < 0.001) independent of collateral circulation. In per-patient analysis, global baseline ECV was indicative of ejection fraction (EF) at the follow-up examination (β = -0.61, p < 0.001) and changes in EF (β = -0.57, p = 0.001) in multivariate regression analysis. A patient with global baseline ECV less than 30.0% (AUC, 0.93; sensitivity 94%, specificity 80%) was more likely to demonstrate significant EF improvement (OR: 0.38; 95% CI: 0.17-0.85; p = 0.019). Conclusion: Extracellular volume fraction obtained by CMR may provide incremental value for the prediction of functional recovery both at the segmental and global levels in CTO patients, and may facilitate the identification of patients who can benefit from revascularization.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.113-114
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• 2013

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging is a powerful technique for producing chemical images of small biomolecules (ex. metabolites, lipids, peptides) "as received" because of its high molecular specificity, high surface sensitivity, and submicron spatial resolution. In addition, matrix-assisted laser desorption and ionization time-of-flight (MALDI-TOF) imaging is an essential technique for producing chemical images of large biomolecules (ex. genes and proteins). For this talk, we will show that label-free mass imaging technique can be a platform technology for biomedical studies such as early detection/diagnostics, accurate histologic diagnosis, prediction of clinical outcome, stem cell therapy, biosensors, nanomedicine and drug screening [1-7].

• Structural Engineering and Mechanics
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• v.45 no.6
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• pp.853-865
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• 2013

Inflatable panels made of modern and new textile materials can be inflated at high pressure to have a high mechanical strength. This paper is based on the finite element method as a general solution to determine the characteristics of deformed inflatable panels at high pressure in various end and loading conditions. Proposed method is based on the construction of weak form of formulation and application of Reduced Integration Element method (RIE) to solve the numerical problem of shear locking. The numerical results are validated as an outcome of comparison with other published results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.672-675
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• 1995

Because of a sudden growth of the research of fatigue failure, recent machines or structures have been designed by damage tolerance design in many fields. Consequently, it is the most primary factor to clarity the specific character of fatique failure in the design of machines or structures considering reliability. A statistical analysis is required to analyze the outcome of an experiment or a life estimate by reason of that fatigue failure contains lots of random elements. Reliability analysis which has tukenn the place of the existing analyses in the consideration of the uncertainty of a material, is a very efficient way. Even reliability analysis, however, is not a perfect way to analyses the uncertainties of all the materials. This thesis would refer to a newly conceived data analysis that the coefficient of a system could cause the ambiguity of the relationship of an input and output.

• The korean journal of orthodontics
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• v.44 no.6
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• pp.342-349
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• 2014

Because of the potential morbidity and complications associated with surgical procedures, limiting the extent of orthognathic surgery is a desire for many orthodontic patients. An eighteen-year-old woman had a severe Class III malocclusion and required bi-maxillary surgery. By changing the patient's maxillary occlusal plane using orthodontic mini-implants, she was able to avoid the maxillary surgery; requiring only a mandibular setback surgery. To accurately predict the post-surgery outcome, we applied a new soft tissue prediction method. We were able to follow and report the long-term result of her combined orthodontic and orthognathic treatment. The changes to her occlusal plane continue to appear stable over 6 years later.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.605-612
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• 2011

In multi-center randomized clinical trial the treatment eect may be changed over centers. It is thus important to investigate the heterogeneity in treatment eect between centers. For this, uncorrelated random-eect models assuming independence between random-eect terms have been often used, which may be a strong assumption. In this paper we propose a correlated frailty modelling approach of investigating such heterogeneity using the hierarchical-likelihood method when the outcome is time-to-event. In particular, we show how to construct a proper prediction interval for frailty, which explores graphically the potential heterogeneity for a treatment-by-center interaction term. The proposed method is illustrated via numerical studies based on data from the design of a multi-center clinical trial.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.210-212
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• 1999

This paper proposes a novel wavelet transform based technique for prediction of System Marginal Price(SMP). In this paper, Daubechies D1(haar), D2, D4 wavelet transforms are adopted to predict SMP and the numerical results reveal that certain wavelet components can effectively be used to identify the SMP characteristics with relation to the system demand in electric power systems. The wavelet coefficients associated with certain frequency and time localisation are adjusted using the conventional multiple regression method and then reconstructed in order to predict the SMP on the next scheduling day through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed wavelet transform approach can be used as an attractive and effective means for the SMP forecasting.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.463-467
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• 2015

Mega-shock means a sporadic event such as the earning shock, which occurred by sudden market changes, and it can cause serious problems of profit loss of international construction projects. Therefore, the early response and prevention by analyzing and predicting the Mega-shock is critical for successful project delivery. This research is preliminary study to develop a prediction model that supports market condition analysis and Mega-shock forecasting. To avoid disadvantages of classic statistical approaches that assume the market factors are linear and independent and thus have limitations to explain complex interrelationship among a range of international market factors, the research team explored the Fractal Theory that can explain self-similarity and recursiveness of construction market changes. The research first found out correlation of the major market factors by statistically analyzing time-series data. The research then conducted a base of the Fractal analysis to distinguish features of fractal from data. The outcome will have potential to contribute to building up a foundation of the early shock warning system for the strategic international project management.

• Korea Journal of Hospital Management
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• v.11 no.3
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• pp.19-41
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• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.