• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.2
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• pp.277-285
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• 2000

The purpose of this study was to quantify the relationship between the sense of touch and mechanical properties of man-made leather. The first was to develop the five conversion equations which convert mechanical properties of man-made leather into five factor scores, which express five factors of the sense of touch(surface property, stretchiness, thickness & weight, thermal property(warmth & coolness), and moisture property(sticky & clingy)). The second was to develop the conversion equation which converts five factor scores into score of the sense of touch. Five factor scores were predicted by the following mechanical properties; surface property factor by log2HB and (log2HB)2, stretchiness factor by logEM, thickness & weight factor by logT, log2HB, logW, thermal property factor by logT, logHB, logSMd, and moisture property factor by logMMD, RC, RC2, (logEM)2, RT2. Subsequently, these five factor scores were converted into score of the sense of touch. The predictive abilities of the developed equations were satisfied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.822-832
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• 1994

DSC-HDTV image compression algorithm removes spatial, temporal, and amplitude redundancies of an image by using transform coding, motion-compensated predictive coding, and adaptive quantization, respectively. In this paper, leak processing method which is used to recover image quality quickly from scene change and transmission error and adaptive quantization using perceptual weighting factor obtained by HVS are proposed. Perceptual weighting factor is calculated by contrast sensitivity, spatio-temporal masking and frequency sensitivity. Adaptive quantization uses the perceptual weighting factor and global distortion level from buffer history state. Redundant bits according to adaptation of HVS are used for the next image coding. In the case of scene change, DFD using motion compensated predictive coding has high value, large bit rate and unstabilized buffer states since reconstructed image has large quantization noise. Thus, leak factor is set to 0 for scene change frame and leak factor to 15/16 for next frame, and global distortion level is calculated by using standard deviation. Experimental results show that image quality of the proposed method is recovered after several frames and then buffer status is stabilized.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4823-4826
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• 2012

Objective: To explore serum angiogenic factor expression in patients with osteosarcoma and its relationship with metastasis. Methods: Immunohistochemistry was used to test the expression of CD34 and FVIII-Rag in osteosarcoma tissues of 36 patients (osteosarcoma group) and microvessel density (MVD) was also recorded. In addition, ELISA was used to test the level of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), transforming growth factor-${\beta}1$ (TGF-${\beta}1$) and endostatin (ES) in the osteosarcoma group and in a control group. Results: VEGF and ES level were significantly higher than in the control group before operation (P<0.01), VEGF, bFGF and TGF-${\beta}1$ correlating with the ES level (P<0.01). Serum VEGF and ES levels of osteosarcoma patients before surgery were closely related to relapse and metastasis; moreover, serum VEGF increased with MVD (P<0.01). Postoperative VEGF and ES levels were lower than the preoperation values (P<0.01); ES level in relapse group was significantly higher than that of the non-relapse group (P<0.01). Conclusion: Preoperative serum VEGF and postoperative ES levels have great predictive value with regard to relapse of osteosarcoma patients.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2509-2514
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• 2013

Background: The purpose of this study was to identify predictive factors for supraclavicular lymph node recurrence (SCLR) in N1 breast cancer patients and define a high-risk subgroup who might benefit from supraclavicular nodal radiotherapy (RT). Materials and Methods: From January 1995 to December 2009, 113 breast cancer patients with 1 to 3 positive axillary lymph nodes were enrolled in this study. All patients underwent breast-conserving surgery (BCS) or modified radical mastectomy (MRM). RT was given to all patients who received BCS. Among the patients given MRM, those with breast tumors >5 cm in size received RT. Regional nodal irradiation was not applied. Systemic chemotherapy was given to 105 patients (92.9%). Patient data were retrospectively reviewed and analyzed to identify predictive factors for SCLR. Results: The median follow-up duration was 6.5 years, with 5- and 10-year actuarial SCLR rates of 9.3% and 11.2%, respectively. Factors associated with SCLR on univariate analysis included histologic grade, number of dissected axillary lymph nodes, lymphovascular invasion, extracapsular extension (ECE), and adjuvant chemotherapy. On multivariate analysis, histologic grade and ECE remained significant. The patient group with grade 3 and ECE had a significantly higher rate of SCLR compared with the remainder (5-year SCLR rate; 71.4% vs. 4.0%, p<0.001). Conclusions: Histologic grade and ECE status are significant predictive factors for SCLR. Supraclavicular nodal RT is necessary in N1 breast cancer patients featuring histologic grade 3 and ECE.

• Childhood Kidney Diseases
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• v.10 no.2
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• pp.132-141
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• 2006

Purpose : This study was aimed to determine the predictive risk factors for the treatment response and relapse rate in children diagnosed with idiopathic nephrotic syndrome. Methods : We analyzed the medical records of children who were diagnosed and treated for childhood idiopathic nephrotic syndrome from November 1991 to May 2005. Variables selected in this study were age at onset, sex, laboratory data, concomitant bacterial infections, days to remission, and interval to first relapse. Results : There were 46 males and 11 females, giving a male:female ratio of 4.2:1. The age($mean{\pm}SD$) of patients was $5.8{\pm}4.1$ years old. Of all patients who were initially given corticosteroids, complete remission(CR) was observed in 54(94.7%). Of the 54 patients who showed CR with initial treatment, 40(70.2%) showed CR within 2 weeks and 14(24.6%) showed CR after 2 weeks. The levels of serum IgG were lower in the latter group who showed CR after 2 weeks(P=0.036). Of the 54 patients who showed CR with initial treatment, 47(82.5%) relapsed. Of these patients, 35.1% were frequent relapsers and 43.9% were infrequent relapsers. There was no significant correlation between the frequency of relapse and the following variables : sex, days to remission, and laboratory data. However, age at onset and interval to first relapse had a negative correlation with the frequency of relapse(Pearson's coefficient=-0.337, -0.433, P<0.012, P<0.01). Conclusion : The age at onset and the interval to first relapse were found to be predictive clinical parameters for the relapse rate, while the levels of serum IgG at initial presentation were a predictive laboratory factor for treatment response in childhood idiopathic nephrotic syndrome.

• Health Policy and Management
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• v.16 no.2
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• pp.21-48
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• 2006

As prior studies indicate that chronic diseases are mainly attributed to health behavior, preventive health care rather than treatment for illness needs to improve health status. Since chronic conditions require long-term therapy, health care expenditures to treat chronic diseases have been substantial burden at national level. In this point of view, this study suggests that the health promotion program should be based on Knowledge Based System Using Data Mining Technique, we developed a predictive model for preventive healthcare management on diabetes mellitus. Generally, in the outbreak of diabetes mellitus there is a difference in lifestyle and the risk factors according to gender. So we developed a predictive model in accordance with gender difference and applied the Logistic Regression Model based on Data Mining process. The result of the study were as follow. The lift of the last predictive model was an average 2.23 times(male model : 2.13, female model 2.33) more improved than in the random model in upper 10% group. The health risk factors of diabetes mellitus are gender, age, a place of residence, blood pressure, glucose, smoking, drinking, exercise rate. On the basis of these factors, we suggest the program of the health promotion.

• Asian Oncology Nursing
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• v.3 no.2
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• pp.122-132
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• 2003

Purpose: The purpose of this study was to identify predictive factors of Brest Self-Examination practice of clinical nurses. Method: The subject for this study were 277 nurses in 8 university hospitals in Busan. The data were collected from September 21 to October 20, 2001 by means of a structure questionnaire. The instruments used for this study were Choi's BSE knowledge scale. Kim's BSE attitude scale and Jung's BSE practice scale. The data were analyzed using frequency, percentage, mean, Peason Correlation, t-teat, ANOVA, scheffe's test, and multiple stepwise Regression using SPSS program. Result: 1. The mean score of BSE practice for the total sample was 7. 25${\pm}$4.62. 2. Statistically significant factors influencing the BSE Practice among social demographic characteristics were age(F=2.734, P=0.44), Married status(t=2.598, p=0.010). 3. Statistically significant factors influencing the BSE Practice among BSE relating characteristics were enlisting the help of significant peers(t=3.34, P=0.00), Intention of Practice for BSE(t=10.462, p=0.00), performance of BSE(t=7.800, P=0.00), frequency of performance in BSE(F=13.932, p=0.00), confidence in Knowledge of BSE technique(F=5.350, p=0.00), confidence in finding breast nodule(F=7.204, p=.00), asking client's BSE (t=3.153, P=0.01). 4.The mild correlation between nurse's BSE knowledge and practice was found(r=0.366,p=0.000). 5. There were significant predictors of BSE Practice. Performance of BSE was the best significant predictive factor(R2=.383, p=.000) Another significant predictive factors were knowledge, intension of practice, married status, frequency of performance. Conclusion: Degree of nurses' performance of BSE was average. It is necessary to develope the nurses' educational program for BSE with its focus on above predictive factors of performance of BSE.

• Computers and Concrete
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• v.19 no.5
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• pp.457-465
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• 2017

The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.

• Radiation Oncology Journal
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• v.32 no.2
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• pp.77-83
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• 2014

Purpose: To determine the prognostic and predictive value of liver volume in colorectal cancer patients with unresectable liver metastases. Materials and Methods: Sixteen patients received whole liver radiotherapy (WLRT) between January 1997 and June 2013. A total dose of 21 Gy was delivered in 7 fractions. Results: The median survival time after WLRT was 9 weeks. In univariate analysis, performance status, serum albumin and total bilirubin level, liver volume and extrahepatic metastases were associated with survival. The mean liver volume was significantly different between subgroups with and without pain relief (3,097 and 4,739 mL, respectively; p = 0.002). Conclusion: A larger liver volume is a poor prognostic factor for survival and also a negative predictive factor for response to WLRT. If patients who are referred for WLRT have large liver volume, they should be informed of the poor prognosis and should be closely observed during and after WLRT.

• Food Science of Animal Resources
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• v.35 no.1
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• pp.108-113
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• 2015

The purpose of this study was to develop predictive models for the growth of Listeria monocytogenes in pork Bulgogi at various storage temperatures. A two-strain mixture of L. monocytogenes (ATCC 15313 and isolated from pork Bulgogi) was inoculated on pork Bulgogi at 3 Log CFU/g. L. monocytogenes strains were enumerated using general plating method on Listeria selective medium. The inoculated samples were stored at 5, 15, and $25^{\circ}C$ for primary models. Primary models were developed using the Baranyi model equations, and the maximum specific growth rate was shown to be dependent on storage temperature. A secondary model of growth rate as a function of storage temperature was also developed. As the storage temperature increased, the lag time (LT) values decreased dramatically and the specific growth rate of L. monocytogenes increased. The mathematically predicted growth parameters were evaluated based on the modified bias factor ($B_f$), accuracy factor ($A_f$), root mean square error (RMSE), coefficient of determination ($R^2$), and relative errors (RE). These values indicated that the developed models were reliably able to predict the growth of L. monocytogenes in pork Bulgogi. Hence, the predictive models may be used to assess microbiological hygiene in the meat supply chain as a function of storage temperature.