• International Journal of Air-Conditioning and Refrigeration
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• v.15 no.3
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• pp.129-136
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• 2007

In this paper, we suggest PI control with the Smith predictive controller to improve transient response of a variable speed refrigeration system (VSRS). As the refrigeration system has long dead time inherently, it is difficult to get fast responses of super-heat and reference temperature. We incorporated the Smith predictive controller into PI to compensate the effect of the long dead time of the system. At first, we introduced the decoupling model of the system to control capacity and superheat simultaneously and independently. Next, we designed the predictive controller of the superheat based on PI control law. Finally, the control performance by the proposed method was investigated through some numerical simulations and experiments. The results of the simulations and experiments showed that the proposed PI control with the predictive controller could obtain acceptable transient behaviour for the system.

• Health Policy and Management
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• v.9 no.2
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• pp.1-20
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• 1999

This study was conducted to investigate the predictors of hospital bankruptcy in Korea and to examine the predictive power for 3 types of statistical models of hospital bankruptcy. Data on 17 financial and 4 non-financial indicators of 30 bankrupt and 30 profitable hospitals in 1. 2, and 3 years before bankruptcy were obtained from the hospital performance databank of Korea Institute of Health Services Management. Significant variables were identified through mean comparison of each indicator between bankrupt and profitable hospitals, and the predictive power of statistical models of hospital bankruptcy were compared. The major findings are as follows. 1. Nine out of 21 indicators - fixed ratio, quick ratio, operating profit to total assets, operating profit to gross revenue, normal profit to total assets,normal profit to gross revenue, net profit to gross revenue, inventories turnrounds, and added value per adjusted patient - were found to be significantly predictitive variables in Logit and Probit models. 2. The predicdtive power of discriminant model of hospital bankruptcy in 1. 2, and 3 years before bankruptcy were 85.4, 79.0, and 83.8% respectively. With regard to the predictive power of the Logit model of hospital bankruptcy, they were 82.3, 75.8, and 80.6% respectively, and of the Probit model. 87.1. 80.6, and 88.7% respectively. 3. The predictive power of the Probit model of hospital bankruptcy is better than the other two predictive models.

• 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 the Korean Home Economics Association
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• v.33 no.4
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• pp.173-188
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• 1995

This study examined the characteristics of the relationship of HOME, sociodemographic variables and children's verbal ability at age four, five, six, Expecially this study investigated causal relationships amoong the variables which are supposed to affect children's verbal ability by children's age and sex. The subject of this study were 180 children and their mothers. Instruments included inventory of home stimulation(HOME), inventory of socio-demographic variables, inventory of the children's verbla ability. The results obtained from this study were as follows : 1. For the most part, HOME and socio-demographic variables had a significant positive correlation with children's verbal ability. 2. The variables that significantly predicted children's verbal ability differed according to children's age and sex. That is, play materials, breadth of experience and economic status of the home were predictive of boy's verbal ability at age four, while aspects of physical environment, breadth of experience were predictive at age five, fostering maturity and independence, parent's education were predictive at age six. And developmental stimulation and breadth of experience were predictive of girl's verbal ability at age four, while developmental stimulation, economic status of the home were predictive at age five, developmental stimulation and play materials were predictive at age six. 3. the results of the analysis of the causal model showed that the kind of variables that affected children's verbal ability directly differed according to children's age and sex. That is, indirect stimulation and direct stimulation affected boy's verbal ability directly at age four and five, while indirect stimulation and parent's education affected boy's verbal ability at age six. And indirect stimulation, direct stimulation, emotional climate of the home affected girl's verbal ability directly at age four, while direct stimulation, economic status of the home, indirect stimulation affected directly at age five, parent's education, indirect stimulation and direct stimulation affected girl's verbal ability at age six. 4. Another causal model of the HOME, socio-demographic variables affecting children's verbal ability showed that total HOME scores more significantly affected boys and girl's verbal ability directly than socio-demographic variables at all ages.

• Korean Journal of Head & Neck Oncology
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• v.26 no.1
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• pp.3-8
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• 2010

Background : Though papillary microcarcinoma(PMC) of thyroid gland is known to have very favorable long-term prognosis, the recurrence in the neck and distant metastasis have been often reported. The predictive factors of node metastasis and tumor recurrence in clinical course were investigated to define surgical decision or guidelines in surgery of papillary microcarcinoma. Methods : The authors conducted a retrospective analysis of 216 patients of PMC treated with surgery at Department of Surgery, Busan Paik Hospital for the period from 1997 to 2007. Of these patients, 58 cases showing cervical lymph node metastasis at initial surgery were studied. Results : In overall 216 patients, the sex ratio of male to female was 1 : 9.3(male 21, female 195 cases), the mean age at the time of diagnosis was 44.7 years and the median tumor size was 6.61mm. Neck lymph node metastasis was found in 58 patients(26.9%), thyroid capsular invasion was 56 cases(25.9%), multifocality and bilaterality were found in 32(14.8%) and 29 cases(13.4%), respectively. Through statistical analysis, sex, capsular invasion, ETE, and tumor size(>5mm) were considered to be predictive factors of cervical lymph nodes metastasis. Of them, capsular invasion was the most predictive indicator of cervical lymph node metastasis on multivariate analysis. Nodal recurrence was observed in 6 of 58 patients of node positive at initial surgery. Conclusion : The cervical lymph node metastasis is known to be a risk factor of prognosis in PMC of thyroid gland. The results of this study showed four statistically significant independent predictive factors of cervical lymph node metastasis in PMC : capsular invasion, tumor size(>5mm), ETE, and sex. On multivariate analysis, capsular invasion was a great influencing factor in prediction of lymph node metastasis. Basically, patients who has predictive factors of cervical lymph node metastasis should have a thorough investigation, and close surveillance for nodal status is required in follow-up.

• Journal of Korean Port Research
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• v.14 no.1
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• pp.66-75
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• 2000

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.271-280
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• 2019

Smart factory, a critical part of digital transformation, enables data-driven decision making using monitoring, analysis and prediction. Predictive maintenance is a key element of smart factory and the need is increasing. The purpose of this study is to analyze the degradation characteristics of a galvanizing kettle for the steel plating process and to predict the remaining useful life(RUL) for predictive maintenance. Correlation analysis, multiple regression, principal component regression were used for analyzing factors of the process. To identify the trend of degradation, a proposed rolling window was used. It was observed the degradation trend was dependent on environmental temperature as well as production factors. It is expected that the proposed method in this study will be an example to identify the trend of degradation of the facility and enable more consistent predictive maintenance.

• Physical Therapy Rehabilitation Science
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• v.7 no.1
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• pp.29-34
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• 2018

Objective: This study aimed to predict balance and gait abilities with the Trunk Impairment scales (TIS) in persons with stroke. Design: Cross-sectional study. Methods: Sixty-eight participants with stoke were assessed with the TIS, Berg Balance scale (BBS), and Functional Gait Assessment (FGA) by a therapist. To describe of general characteristics, we used descriptive and frequency analyses, and the TIS was used as a predictive variable to determine the BBS. In the simple regression analysis, the TIS was used as a predictive variable for the BBS and FGA, and the TIS and BBS were used as predictive variables to determine the FGA in multiple regression analysis. Results: In the group with a BBS score of >45 for regression equation for predicting BBS score using TIS score, the coefficient of determination ($R^2$) was 0.234, and the $R^2$ was 0.500 in the group with a BBS score of ${\leq}45$. In the group with an FGA score >15 for regression equation for predicting FGA score using TIS score, the $R^2$ was 0.193, and regression equation for predicting FGA score using TIS score, the $R^2$ was 0.181 in the group of FGA score ${\leq}15$. In the group of FGA score >15 for regression equation for predicting FGA score using TIS and BBS score, the $R^2$ was 0.327. In the group of FGA score ${\leq}15$ for regression equation for predicting FGA score using TIS and BBS score, the $R^2$ was 0.316. Conclusions: The TIS scores are insufficient in predicting the FGA and BBS scores in those with higher balance ability, and the BBS and TIS could be used for predicting variables for FGA. However, TIS is a strong predictive variable for persons with stroke who have poor balance ability.

• Proceedings of the KIPE Conference
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• 2014.11a
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• pp.1-2
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• 2014

In this paper the partial switching PFC converter which is based on predictive control is proposed. In terms of satisfying the harmonic standard, the predictive control shows a similar performance to the conventional average current mode control PFC in the normal input condition. Moreover, the current harmonic characteristic is insensitive to the distorted input voltage. With predictive control method, novel on-line partial switching strategy is suggested in this paper. Depending on the operating condition, the partial switching PFC converter can boost its output voltage. Also when its efficiency needs to be improved, according to load condition, the partial switching can be achieved. The proposed strategy is proved by the results of FFT and the loss analysis using PSIM 9.0.

• Journal of applied mathematics & informatics
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• v.3 no.1
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• pp.11-24
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• 1996

The focus of this research is the class of sequential al-gorithms called predictive sorting algorithms for sorting a given set of n elements using pairwise comparisons. The order in which these pairwise comparisons are made is defined by a fixed sequence of all un-ordered pairs of distinct integers{1,2 ···,n} called a sort sequence. A predictive sorting algorithm associated with a sort sequence spec-ifies pairwise comparisons of elements in the input set in the order defined by the sort sequence except that the comparisons whose out-comes can be inferred from the preceding pairs of comparisons are not performed. in this paper predictive sorting algorithms are obtained based on known sorting algorithms and are shown to be required on the average O(n log n) comparisons.