• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6407-6412
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• 2015

Purpose: To predict prostatic carcinoma using a logistic regression model on prebiopsy peripheral blood samples. Materials and Methods: Data of a total of 873 patients who consulted Urology Outpatient Clinics of Fatih Sultan Mehmet Training and Research Hospital between February 2008 and April 2014 scheduled for prostate biopsy were screened retrospectively. PSA levels, prostate volumes, prebiopsy whole blood cell counts, neutrophil and platelet counts, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), biopsy results and Gleason scores in patients who had established diagnosis of prostate cancer (PCa) were evaluated. Results: This study was performed on a total of 873 cases, with an age range 48-76 years, divided into three groups as for biopsy results. with diagnoses of benign prostatic hyperplasia (BPH) (n=304, 34.8 %), PCa (n=265, 30.4 %) and histological prostatitis (n=304; 34.8 %). Intra- and intergroup comparative evaluations were performed. White blood cell and neutrophil counts in the histological prostatitis group were significantly higher than those of the BPH and PCa groups (p=0.001; p=0.004; p<0.01). A statistically significant intergroup difference was found for PLR (p=0.041; p<0.05) but not lymphocyte count (p>0.05). According to pairwise comparisons, PLR were significantly higher in the PCa group relative to BPH group (p=0.018, p<0.05, respectively). Though not statistically significant, higher PLR in cases with PCa in comparison with the prostatitis group was remarkable (p=0.067, and p>0.05, respectively). Conclusions: Meta-analyses showed that in patients with PSA levels over 4 ng/ml, positive predictive value of PSA is only 25 percent. Therefore, novel markers which can both detect clinically significant prostate cancer, and also prevent unnecessary biopsies are needed. Relevant to this issue in addition to PSA density, velocity, and PCA3, various markers have been analyzed. In the present study, PLR were found to be the additional predictor of prostatic carcinoma.

• Korean Journal of Agricultural Science
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• v.11 no.1
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• pp.176-181
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• 1984

Linear free energy relation ship(LFER) on the insecticidal activity of O,O-diethylphenylphosphate (A) and 3,5-dimethylphenyl-O,O-diethylphosphate (B) derivatives were studied by EHT MO calculation method and regression analysis method. LFER between varying substituent constants and $pI_{50}$ constants of phosphates, (A) & (B) were calculated with applying Hammett, Okamoto-Brown, Taft and Swain-Lupton's DSP equations;percent resonance effect(R) and field effect(F) of (A) were %R=33.5 & %F=66.5 and also that of (B) were %R=2 & %F=98, respectively. On the basis of above findings, the insecticidal activities were similar for both (A) and (B), but (B) have larger field and inductive contribution than (A), due to the 3,5-dimethyl group of (B).

• Economic and Environmental Geology
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• v.13 no.4
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• pp.215-227
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• 1980

The rock units of Goesan area in the Ogcheon metamor phic terrain established on the basis of field criteria should be redefined into following sequence. Based on shear senses in secondary small structures which are usually observable in the investigated area, the stratigraphy can be lithologically divided into the lower pelite, pebbly mudstone, upper pelite, quartzite and psammite unit in ascending order. This conclusion is in discordance with a previous opinion; Munjuri formation and Guryongsan formation may be equivalent to upper pelite unit, Iwonri formation and Hwanggangri formation to pebbly mudstone. From this, it may be inferred that isoclinal overturned folds repeatly occur in the area. The uranium bearing coaly thin layers in upper pelite unit have relatively broad exposures in Deogpyeongri block of Goesan area along culmination zone in the central part of the investigated area. It is believed that structural feature in the block recognized complexly refolded synform plunging to southwest. Mineralogical and radiometric studies were made on 135 representative samples from the Ogcheon Group of Korea. The mineralogy of all black slate samples is qualitatively similar but quantitatively ·different. The uranium distribution in the studied area show approximately log normal. Uranium in the black slates of the Ogcheon Group was deposited together under same physico-chemical environmental conditions. The chemical and geological factors that controlled the abundance of organic carbon and iron oxides also controlled the uranium content. The relationship of the major components to uranium can be expressed by the following regression equation: $Log(U\times10^4+1)$= 1.70999-0.00367(quartz)0.00512(micas)-0.00930 (other silicates)+0.01911 (iron oxides)-0.03389(other opaques)+0.02062(organic carbon).

• Journal of Digital Convergence
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• v.16 no.10
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• pp.145-153
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• 2018

Recently the Korean society has suffered severe conflicts over the rate of increase in the minimum wage, while academics have failed to provide appropriate standards through reliable research. Recent foreign studies using natural experimentation or meta-regression analysis show that the increase in minimum wage has little effect on employment. Domestic studies are not yet numerous in number, and they present different conclusions on employment effects depending on the data used, sample period, and research model. To properly assess the employment effects of the minimum wage, future studies should minimize measurement errors in minimum wage dataset, and appropriately consider the endogenous change of minimum wage, economic situation and trends of employment changes. It is also necessary to utilize natural experiment methods before and after the increase of the minimum wage.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.6-6
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• 2017

본 연구의 목적은 독립적으로 수행되어진 하천 복원 가치추정 선행연구들을 대상으로 메타회귀분석을 활용한 편익이전을 제시함으로써, 편익이전의 타당성 및 적용 가능성을 검토하는 데 있다. 문헌검색을 통해 '하천 가치평가', '하천 가치', '물 환경 가치추정', '하천 편익' 등에 관한 자료를 수집하였으며, 총 60편의 연구를 수집했다. 그 중 중복된 연구를 제외하고 가치추정 단위를 '원/년/가구'로 통일함으로써 51편의 연구를 분석에 사용했으며, 90개의 가치 추정치가 실증분석에 사용되었다. 본 연구는 국내에서 수행된 하천 복원 가치 추정연구를 집대성하여 DB를 구축하고 요약통계량을 중심으로 선행연구 결과를 기술하였으며, 메타회귀분석을 실시한 후, policy site의 특성과 조건에 맞게 함수를 조정하고, 조정된 함수를 사용하여 policy site의 가치를 예측하였다. 종속변수로는 총 가치(원/년/가구, 2015년 불변가격)가, 독립변수로는 하천유형, 위치, 규모, 환경 서비스특성, 그리고 방법론 특성, 지불형태, 대상지 사회경제적 특성 변수들이 포함되었다. 모형의 추정결과 조정된 값은.420으로써 종속변수 총변이의 42.0%를 모형이 설명하는 것으로 나타났다. 메타회귀분석을 통해 본류에서 멀어지는 소규모하천일수록 하천의 경제적 가치를 더 크게 느끼는 것으로 나타났으며, 전체적인 영향력 크기를 고려해 본다면 하천을 복원할 때 수질정화기능, 서식지기능, 이수기능, 치수기능, 여가 및 수변공간으로의 기능 순으로 고려하는 것이 하천의 가치를 보다 높일 수 있을 것으로 보였다. 또한 지불방법은 매월, 인당 지불하는 것으로 제시할 때 경제적 가치 추정치를 높일 수 있는 것으로 해석되었다. 모델추정 결과를 활용한 함수이전에서는 만경강의 특성을 반영하고 조정함으로써 만경강의 가치를 추정하였으며, 모형으로부터 얻은 만경강 가치 예측치는 가구당 매년 41,214원으로 추정되었다. 본 연구의 메타회귀분석은 선행연구를 객관적으로 종합할 수 있는 분석의 틀로서 충분한 활용 타당성이 인정되는 것으로 보이며, 편익이전 시에 policy site의 자원특성과 조건에 맞춰 함수를 조정하여 예측치를 제시함으로써 메타회귀분석 함수이전의 융통성을 보여주었다. 이에 메타회귀분석을 통한 편익이전은 타당성 및 적용 가능성 측면에서 긍정적으로 판단된다.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.199-211
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• 2019

This study analyzed the research trends of college students' entrepreneurship in 172 scholarly articles in the registered journals of the Korea Research Foundation from 2010 to 2018. The results of this study are as follows: First, the research areas and topics on university students' entrepreneurship focuses on not only characteristics of entrepreneurship and entrepreneur but also entrepreneurship education. Also, the research method was dependent on the quantitative research method coupled with the statistic techniques such as descriptive statistics, correlation, t-test, ANOVA, regression analysis, and structural equation modeling. In future research, it is necessary to expand research areas to startup idea design, startup business environment and policies. Also, it is necessary to explore various variables related to entrepreneurship, not focusing on specific variables such as entrepreneurship, entrepreneurship education as well as to analyze meta analysis of the relationship between the variables influencing on the entrepreneurial intention. In addition, qualitative research and mixed research are needed to explore the process of developing entrepreneurship and the factors affecting the process of entrepreneurship.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.2
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• pp.57-64
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• 2021

This study presents a method for realtime fuel consumption prediction using real data collected from OBDII. With the advent of the era of self-driving cars, electronic control units(ECU) are getting more complex, and various studies are being attempted to extract and analyze more accurate data from vehicles. But since ECU is getting more complex, it is getting harder to get the data from ECU. To solve this problem, the firmware was developed for acquiring accurate vehicle data in this study, which extracted 53,580 actual driving data sets from vehicles from January to February 2019. Using these data, the ensemble stacking technique was used to increase the accuracy of the realtime fuel consumption prediction model. In this study, Ridge, Lasso, XGBoost, and LightGBM were used as base models, and Ridge was used for meta model, and the predicted performance was MAE 0.011, RMSE 0.017.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.489-502
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• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Tuberculosis and Respiratory Diseases
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• v.86 no.2
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• pp.120-132
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• 2023

Background: To systematically review studies on inhaled corticosteroids (ICS) and lung cancer incidence in chronic airway disease patients. Methods: We conducted electronic bibliographic searches on OVID-MEDLINE, EMBASE, and the Cochrane Database before May 2020 to identify relevant studies. Detailed data on the study population, exposure, and outcome domains were reviewed. Results: Of 4,058 screened publications, 13 eligible studies in adults with chronic obstructive pulmonary disease (COPD) or asthma evaluated lung cancer incidence after ICS exposure. Pooled hazard ratio and odds ratio for developing lung cancer in ICS exposure were 0.81 (95% confidence interval, 0.64 to 1.02; I²=95.7%) from 10 studies and 1.02 (95% confidence interval 0.50 to 2.07; I²=94.7%) from three studies. Meta-regression failed to explain the substantial heterogeneity of pooled estimates. COPD and asthma were variously defined without spirometry in 11 studies. Regarding exposure assessment, three and 10 studies regarded ICS exposure as a time-dependent and fixed variable, respectively. Some studies assessed ICS use for the entire study period, whereas others assessed ICS use for 6 months to 2 years within or before study entry. Smoking was adjusted in four studies, and only four studies introduced 1 to 2 latency years in their main or subgroup analysis. Conclusion: Studies published to date on ICS and lung cancer incidence had heterogeneous study populations, exposures, and outcome assessments, limiting the generation of a pooled conclusion. The beneficial effect of ICS on lung cancer incidence has not yet been established, and understanding the heterogeneities will help future researchers to establish robust evidence on ICS and lung cancer incidence.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.5095-5099
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• 2015

Background: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. Materials and Methods: A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. Results: The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05%(200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (${\geq}65$ years), use of antibiotics, low serum albumin concentrations (${\leq}37.18g/L$), radiotherapy, surgery, low hemoglobin hyperlipidemia (${\leq}93.67g/L$), long time of hospitalization (${\geq}14$days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model($0.829{\pm}0.019$)was higher than that of LR model ($0.756{\pm}0.021$). Conclusions: The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.