• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2567-2570
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• 2013

Background: This study analyzed Surveillance, Epidemiology and End Results (SEER) data to assess if socio-economic factors (SEFs) impact on endometrial cancer survival. Materials and Methods: Endometrial cancer patients treated from 2004-2007 were included in this study. SEER cause specific survival (CSS) data were used as end points. The areas under the receiver operating characteristic (ROC) curve were computed for predictors. Time to event data were analyzed with Kaplan-Meier method. Univariate and multivariate analyses were used to identify independent risk factors. Results: This study included 64,710 patients. The mean follow up time (S.D.) was 28.2 (20.8) months. SEER staging (ROC area of 0.81) was the best pretreatment predictor of CSS. Histology, grade, race/ethnicity and county level family income were also significant pretreatment predictors. African American race and low income neighborhoods decreased the CSS by 20% and 3% respectively at 5 years. Conclusions: This study has found significant endometrial survival disparities due to SEFs. Future studies should focus on eliminating socio-economic barriers to good outcomes.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6781-6785
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• 2014

Purpose: This study used receiver operating characteristic curves to analyze Surveillance, Epidemiology and End Results (SEER) medulloblastoma (MB) and primitive neuroectodermal tumor (PNET) outcome data. The aim of this study was to identify and optimize predictive outcome models. Materials and Methods: Patients diagnosed from 1973 to 2009 were selected for analysis of socio-economic, staging and treatment factors available in the SEER database for MB and PNET. For the risk modeling, each factor was fitted by a generalized linear model to predict the outcome (brain cancer specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A Monte Carlo algorithm was used to estimate the modeling errors. Results: There were 3,702 patients included in this study. The mean follow up time (S.D.) was 73.7 (86.2) months. Some 40% of the patients were female and the mean (S.D.) age was 16.5 (16.6) years. There were more adult MB/PNET patients listed from SEER data than pediatric and young adult patients. Only 12% of patients were staged. The SEER staging has the highest ROC (S.D.) area of 0.55 (0.05) among the factors tested. We simplified the 3-layered risk levels (local, regional, distant) to a simpler non-metastatic (I and II) versus metastatic (III) model. The ROC area (S.D.) of the 2-tiered model was 0.57 (0.04). Conclusions: ROC analysis optimized the most predictive SEER staging model. The high under staging rate may have prevented patients from selecting definitive radiotherapy after surgery.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.3
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• pp.111-118
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• 2017

Performance factors such as the EER(Energy Efficiency Ratio) and the COP (Coefficient of Performance) are being replaced by seasonal energy efficiency factors, like the SEER (Seasonal EER) and the SCOP (Seasonal COP) to evaluate the performance of a heat pump by the time of the year. Seasonal performance factors, such as the CSPF (Cooling Seasonal Performance Factor) and the HSPF (Heating Seasonal Performance Factor) are used to describe the heat pump's performance during the cool and hot seasons. In this study, the optimization of all heat pump's operating parameters was experimentally conducted to enhance the SEER based on the EU standard (EN 14825). Moreover, the SEER was improved by the compressor frequency, as well as indoor and outdoor fan speeds. In addition, the performance characteristics of the heat pump were studied under partial load conditions. As a result, the SEER was enhanced by 17% when the compressor frequency was optimized. An additional 2% improvement was achievable with the optimization of indoor and outdoor fan speeds.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.347-352
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• 2016

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Conclusions: Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.353-356
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• 2016

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) for glassy cell carcinoma data to identify predictive models and potential disparities in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors. For risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. Area under the receiver operating characteristic curves (ROCs) were computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate modeling errors. Risk of glassy cell carcinoma death was computed for the predictors for comparison. Results: There were 79 patients included in this study. The mean follow up time (S.D.) was 37 (32.8) months. Female patients outnumbered males 4:1. The mean (S.D.) age was 54.4 (19.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.69). The risks of cause specific death were, respectively, 9.4% for localized, 16.7% for regional, 35% for the un-staged/others category, and 60% for distant disease. After optimization, separation between the regional and unstaged/others category was removed with a higher ROC area of 0.72. Several socio-economic factors had small but measurable effects on outcome. Radiotherapy had not been used in 90% of patients with regional disease. Conclusions: Optimized SEER stage was predictive and useful in treatment selection. Underuse of radiotherapy may have contributed to poor outcome.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3219-3221
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• 2013

Background: This study used receiver operating characteristic (ROC) curves to screen Surveillance, Epidemiology and End Results (SEER) skin melanoma data to identify and quantify the effects of socioeconomic factors on cause specific survival. Methods: 'SEER cause-specific death classification' used as the outcome variable. The area under the ROC curve was to select best pretreatment predictors for further multivariate analysis with socioeconomic factors. Race and other socioeconomic factors including rural-urban residence, county level % college graduate and county level family income were used as predictors. Univariate and multivariate analyses were performed to identify and quantify the independent socioeconomic predictors. Results: This study included 49,999 parients. The mean follow up time (SD) was 59.4 (17.1) months. SEER staging (ROC area of 0.08) was the most predictive foctor. Race, lower county family income, rural residence, and lower county education attainment were significant univariates, but rural residence was not significant under multivariate analysis. Living in poor neighborhoods was associated with a 2-4% disadvantage in actuarial cause specific survival. Conclusions: Racial and socioeconomic factors have a significant impact on the survival of melanoma patients. This generates the hypothesis that ensuring access to cancer care may eliminate these outcome disparities.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.507-511
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• 2008

There have been enormous technological advances in science & technology domain and frequent convergences between its sub-domains. Topic analysis with science & technology corpus is a key process to grasp topic trends and relations between topics. The main objective of this research is to show various analytic approaches with topics extracted from CiteSeer corpus, which is widely used in information technology domain. This paper will also show a case study of Onto-Frame, an R&D support system developed by KISTI, to reveal the role of topics on the system.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.159-163
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• 2013

Background: This study used Surveillance, Epidemiology and End Results (SEER) pancreatic cancer data to identify predictive models and potential socio-economic disparities in pancreatic cancer outcome. Materials and Methods: For risk modeling, Kaplan Meier method was used for cause specific survival analysis. The Kolmogorov-Smirnov's test was used to compare survival curves. The Cox proportional hazard method was applied for multivariate analysis. The area under the ROC curve was computed for predictors of absolute risk of death, optimized to improve efficiency. Results: This study included 58,747 patients. The mean follow up time (S.D.) was 7.6 (10.6) months. SEER stage and grade were strongly predictive univariates. Sex, race, and three socio-economic factors (county level family income, rural-urban residence status, and county level education attainment) were independent multivariate predictors. Racial and socio-economic factors were associated with about 2% difference in absolute cause specific survival. Conclusions: This study s found significant effects of socio-economic factors on pancreas cancer outcome. These data may generate hypotheses for trials to eliminate these outcome disparities.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.4 no.3
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• pp.204-216
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• 1992

In most cases, EER(Energy Efficiency Ratio) is available to present energy efficiency of air-conditioners. But, EER is not adapt to measure energy efficiency at actual life environment because it is based on fixed temperature and humidity contditions. To overcome this disadvantage, there is need to introduce SEER(Seasonal Energy Efficiency Ratio) established at time varient temperature and humidity conditions. In this paper, SEER measurement method and conditions based on actual life environment of the country is introduced, and discussed SEER value about two air-conditioner type, that is, non inverter air-conditioner and inverter air-conditioner. As a result of, inverter air-conditioner was superior to non inverter air-conditioner at cooling seasonal energy efficiency.

• 유체기계공업학회:학술대회논문집
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• 2003.12a
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• pp.693-696
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• 2003

Hermetic Compressor circulates refrigerant with constant flow rate regardless of operation condition. so, at the operating condition requiring low cooling capacity, too much refrigerant flow deteriorates seasonal energy efficiency ratio(SEER). In this reason, modulated compressor is needed to improve SEER. Among many types of modulated compressor, non-inverter type modulated compressor is required for its low cost and easy to development. In the modulated scroll compressor by bypass method, EER steeply decreases for many loss like re-compression, changes of volume ratio, decrease of motor efficiency by torque variation. So. the range of modulation ratio for optimized SEER must be selected accompany with air conditioner set development.