• The Journal of Korean Medicine
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• v.40 no.4
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• pp.49-60
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• 2019

Objectives: To develop a standardized diagnostic pattern identification equation for stroke patients, our group conducted a study to derive the predictive logistic equations. However, the sample size was relatively small. In the current study, we aimed to derive new predictive logistic equations for each diagnostic pattern using an expanded number of subjects. Methods: This study was a hospital-based multi-center trial recruited stroke patients within 30 days of symptom onset. Patients' general information, and the variables related to diagnostic pattern identification were measured. The diagnostic pattern of each patient was identified independently by two Korean Medicine Doctors. To derive a predictive model for pattern identification, binary logistic regression analysis was applied. Results: Among the 1,251 patients, 385 patients (30.8%) had the Fire Heat Pattern, 460 patients (36.8%) the Phlegm Dampness Pattern, 212 patients (16.9%) the Qi Deficiency Pattern, and 194 patients (15.5%) the Yin Deficiency Pattern. After the regression analysis, the predictive logistic equations for each pattern were determined. Conclusion: The predictive equations for Fire Heat, Phlegm Dampness, Qi Deficiency, and Yin Deficiency would be useful to determine individual stroke patients' pattern identification in the clinical setting. However, further studies using objective measurements are necessary to validate these data.

• Journal of Korean Elementary Science Education
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• v.23 no.1
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• pp.61-73
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• 2004

The purpose of this study was to suggest a grounded theory on the process of undergraduate students' generating pattern-knowledge about scientific episodes. The pattern-discovery tasks were administered to seven college students majoring in elementary education. The present study found that college students show five types of procedural knowledge represented in the process of pattern-discovery, such as element, elementary variation, relative prior knowledge, predictive-pattern, and final pattern-knowledge. Furthermore, subjects used seven types of thinking ways, such as recognizing objects, recalling knowledges, searching elementary variation, predictive-pattern discovery, confirming a predictive-pattern, combining patterns, and selecting a pattern. In addition, pattern-discovering process involves a systemic process of element, elementary variation, relative prior knowledge, generating and confirming predictive-pattern, and selecting final pattern-knowledge. The processes were shown the abductive and deductive reasoning as well as inductive reasoning. This study also discussed the implications of these findings for teaching and evaluating in science education.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.1027-1038
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• 2006

There are many technical problems in the recommendation system based on very large database(VLDB). So, it is necessary to study the recommendation system' structure and the data-mining technique suitable for the large scale Internet shopping mail. Thus we design and implement the product recommendation system using k-means clustering algorithm and sequential pattern technique which can be used in large scale Internet shopping mall. This paper processes user information by batch processing, defines the various categories by hierarchical structure, and uses a sequential pattern mining technique for the search engine. For predictive modeling and experiment, we use the real data(user's interest and preference of given category) extracted from log file of the major Internet shopping mall in Korea during 30 days. And we define PRP(Predictive Recommend Precision), PRR(Predictive Recommend Recall), and PF1(Predictive Factor One-measure) for evaluation. In the result of experiments, the best recommendation time and the best learning time of our system are much as O(N) and the values of measures are very excellent.

• Annals of Clinical Neurophysiology
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• v.2 no.1
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• pp.13-20
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• 2000

Background and Objective : Visual evoked potentials(VEPs) is considered to be a reliable diagnostic procedure for examining patients with anterior visual pathways. Some abnormalities in the recordings on monocular stimulation have been said to indicate retrochiasmal lesion, but less consistent results have been reported. This study is to evaluate the positive predictability of VEP for the detection of retrochiasmal lesion. Methods : We reviewed VEPs that could be interpreted as indicative of a retrochiasmal lesions, based on amplitude or latency asymmetry recorded on the left(O1) and right(O2) occipital regions. Bilateral absent VEPs on both recording(O1 and O2) without evidence of prechiasmal lesion were included. During 5 years, we identified 31 patients who met the above criteria and who had undergone magnetic resonance imaging(MRI) of brain(one patient underwent computerized tomography). Twenty three patients underwent pattern reversal VEPs and others underwent flash goggle VEPs. Results : Brain imagings were abnormal in 29 and were normal in 2. Of the 29 abnormal scans, lesions in posterior visual pathway were detected in 21 scans(predictive value=68%). The predictive value was not significantly different between flash goggle VEP(75%) and pattern reversal VEP(68%). The predictive value was higher in patient with visual field defect(100%) than those without visual field defect(25%). The pathologic nature of lesion also showed close relations to the predictive value. VEPs is usually paradoxically lateralized(78%), but not in all patients. Conclusion : VEPs abnormalities suggesting retrochiasmal lesion were usually corresponded with brain MRI findings. Diagnostic reliability could be increased when considering the visual field defect and nature of lesion. Therefore, the authors suggest that VEPs studies could be useful in evaluating the patients with the retrochismal lesion.

• Advances in Computational Design
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• v.7 no.2
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• pp.113-128
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• 2022

Water consumption is strongly affected by numerous factors, such as population, climatic, geographic, and socio-economic factors. Therefore, the implementation of a reliable predictive model of water consumption pattern is challenging task. This study investigates the performance of predictive models based on multi-layer perceptron (MLP), multiple linear regression (MLR), and support vector regression (SVR). To understand the significant factors affecting water consumption, the stepwise regression (SW) procedure is used in MLR to obtain suitable variables. Then, this study also implements three predictive models based on these significant variables (e.g., SWMLR, SWMLP, and SWSVR). Annual data of water consumption in Thailand during 2006 - 2015 were compiled and categorized by provinces and distributors. By comparing the predictive performance of models with all variables, the results demonstrate that the MLP models outperformed the MLR and SVR models. As compared to the models with selected variables, the predictive capability of SWMLP was superior to SWMLR and SWSVR. Therefore, the SWMLP still provided satisfactory results with the minimum number of explanatory variables which in turn reduced the computation time and other resources required while performing the predictive task. It can be concluded that the MLP exhibited the best result and can be utilized as a reliable water demand predictive model for both of all variables and selected variables cases. These findings support important implications and serve as a feasible water consumption predictive model and can be used for water resources management to produce sufficient tap water to meet the demand in each province of Thailand.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.377-382
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• 2005

This paper presents a new method for the attitude control of planar space robots. In order to control highly constrained non-linear system such as a 3D space robot, the analytical formulation for the system with complex dynamics and effective control methodology based on the formulation, are not always obtainable. In the proposed method, correspondingly, a non-analytical but effective self-organizing modeling method for controlling a highly constrained system is proposed based on a polynomial data mining algorithm. In order to control the attitude of a planar space robot, it is well known to require inputs characterized by a special pattern in time series with a non-deterministic length. In order to correspond to this type of control paradigm, we adopt the Model Predictive Control (MPC) scheme where the length of the non-deterministic horizon is determined based on implementation cost and control performance. The optimal solution to finding the size of the input pattern is found by a solving two-stage programming problem.

• Advances in robotics research
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• v.1 no.1
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• pp.41-59
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• 2014

This paper deals with the problem of steering a group of mobile robots along a reference path while maintaining a desired geometric formation. To solve this problem, the overall formation is decomposed into numerous geometric patterns composed of pairs of robots, and the state of the geometric patterns is defined. A control algorithm for the problem is proposed based on the Nash equilibrium strategies incorporating receding horizon control (RHC), also known as model predictive control (MPC). Each robot calculates a control input over a finite prediction horizon and transmits this control input to its neighbor. Considering the motion of the other robots in the prediction horizon, each robot calculates the optimal control strategy to achieve its goals: tracking a reference path and maintaining a desired formation. The performance of the proposed algorithm is validated using numerical simulations.

• Progress in Superconductivity and Cryogenics
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• v.23 no.4
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• pp.49-55
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• 2021

The Cable in Conduit Conductor (CICC) configurations are designed, tested and realized to make high field superconducting (SC) magnets. The evolution of CICC design makes it challenging to forecast thermo-hydraulic behavior. A common objective of thermo-hydraulic studies is to obtain the most reliable predictive correlation for friction factor in CICC geometries and to reduce the dependency on the experiment. So far, only the void fraction and Reynolds number have been considered in the predictive correlations in an explicit way. In the present paper, the CICC twisting pattern dependency, called tortuosity (τ), on the pressure drop prediction, has been assessed through a numerical simulation approach. The CICC twisting pattern with 6+1 petals (solid conductor in the present study) with different twisting pitches is mimicked in the numerical simulation for the range 100 ≤ Re ≤10000 and 1 < τ < 1.08 and a correlation for friction factor, f, has been proposed as a function of Re and τ.

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.142-147
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• 2003

• The Korean Journal of Cytopathology
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• v.8 no.1
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• pp.1-10
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• 1997

The fine needle aspiration biopsy(FNAB) has become a popular method to diagnose mass lesions of the liver. Although many reports have listed FNAB criteria to be used to diagnose hepatocellular carcinoma(HCC), a diagnostic dilemma still exists at the extreme ends of the spectrum, particularly for well differentiated HCC. The authors reviewed a series of FNAB specimens of the liver to distinguish well differentiated HCC from nonneoplastic liver. Fifteen cytologic features were examined in this study: high cellularity, large sheet formation, trabecular pattern, acinar pattern, dispersed pattern, irregular arrangement, increased nuclear/cytoplasmic ratio, naked nuclei, irregular chromatin, irregular nuclear contour, multinucleation, uniform macronucleoli, multiple nuclei, uniform small cytoplasm and monotony of atypia. These features were examined in a series of 76 FNAB specimens. Fifty two specimens were from patients with HCC and 24 specimens were from patients with nonneoplastic lesion or tumors other than HCC containg adequate amount of nonneoplastic hepatocytes in smear. All specimens were coded as to the presence or absence of the above cytologic features. With the use of step-wise logistic regression analysis, three features were identified as the key cytologic features predictive of HCC: irregular chromatin, monotony of atypia and absence of large sheet formation. When these criteria were used, the sensitivity diagnosing HCC by FNAB was 94.2%, specificity 100%, positive predictive value 100% and negative predictive value was 88.9%.