• 한국환경성돌연변이발암원학회지
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• 제25권1호
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• pp.6-12
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• 2005

Many compounds might become activated after absorption of UV light energy. In some cases, the resulting molecule may undergo further biological reaction of toxicological relevance related especially to the photo-carcinogenicity resulting from photo-genotoxicity. However, no regulatory requirements have been issued with the exception of guideline issued by the Scientific Committee of Cosmetology, Commission of the European Communities (SCC/EEC) on the testing of sunscreens for their photo-genotoxicity. Thus, the objectives of this study are to investigate the utility of photo-Ames assay for detecting photo-mutagens, and to evaluate its ability to predict rodent photo-carcinogenicity. Photo-Ames assay was performed on five test substances that demonstrated positive results in photo-carcinogenicity tests: 8-methoxypsoralen (photoactive substance that forms DNA adducts in the presence of ultraviolet A irradiation), chlorpromazine (an aliphatic phenothiazine an a-adr-energic blocking agent), lomefloxacin (an antibiotic in a class of drugs called fluoroquinolones), anthracene (a tricyclic aromatic hydrocarbon a basic substance for production of anthraquinone, dyes, pigments, insecticides, wood preservatives and coating materials) and retinoic acid (a retinoid compound closely related to vitamin A). Out of 5 test substances, 3 showed a positive outcome in photo-Ames assay. With this limited data set, an investigation into the predictive value of this photo-Ames test for determining the photo-carcinogenicity showed that photo-Ames assay has relatively low sensitivity (the ability of a test to predict carcinogenicity). Thus, to determine the use of in vitro genotoxicity tests for prediction of carcinogenicity,' several standard photo-genotoxicity assays should be compared for their suitability in detecting photo-genotoxic compounds.

• 대한화학회지
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• 제35권5호
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• pp.469-479
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• 1991

B. Fricke(J. Chem. Phys., 84, 862 (1986))의 최근 논문에 의하면 원자의 편극성(${\alpha}$)은 원소족내에서 1차 이온화에너지(IP)와 대단히 좋은 상관관계를 보인다고 보고하였다. 본 연구에서는 최소자승법을 적용하여 ln${\alpha}$와 lnIP간의 대단히 좋은 상관관계를 얻었다. 원소족내의 1차 이온화에너지와 원자의 편극성에 대한 다양하게 정의된 원자의 전기음성도와 상관관계를 조사함으로써, 3a와 4a족을 제외한 모든 원소들에 대해서 좋은 상관계수를 얻었다. 원소의 주기내에서는 모든 원소들에 대해서 좋은 상관계수를 얻었다. 이러한 결과로부터 미결정된 여러 가지 원자의 편극성에 대해 매우 좋은 예측을 가능하게 한다.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.10-16
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• 2023

The ever-increasing amount of data generated by various industries and systems has led to the development of data mining techniques as a means to extract valuable insights and knowledge from such data. The electrical energy industry is no exception, with the large amounts of data generated by SCADA systems. This study focuses on the analysis of historical data recorded in the SCADA database of the Libyan Electricity Company. The database, spanned from January 1st, 2013, to December 31st, 2022, contains records of daily date and hour, energy production, temperature, humidity, wind speed, and energy consumption levels. The data was pre-processed and analyzed using the WEKA tool and the Apriori algorithm, a supervised machine learning technique. The aim of the study was to extract association rules that would assist decision-makers in making informed decisions with greater efficiency and reduced costs. The results obtained from the study were evaluated in terms of accuracy and production time, and the conclusion of the study shows that the results are promising and encouraging for future use in the Libyan Electricity Company. The study highlights the importance of data mining and the benefits of utilizing machine learning technology in decision-making processes.

• Asian-Australasian Journal of Animal Sciences
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• 제3권4호
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• pp.353-361
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• 1990

A number of correlation and regression analyses were performed on data from apparent and true digestibility of amino acids at ileal and fecal level with finishing pigs, in order to investigate whether these amino acid digestibilities could be predicted with certainly degree on their fiber fractions content (chemical analysis). The data comprised 16 diets varying in 4 levels of crude fiber and from 4 fiber sources. The relationships between fiber fractions including crude fiber (CF), NDF, ADF lignin and cellulose contents on apparent and true digestibility of almost all amino acids in both ileal and fecal level were negative, except glutamine at fecal level. In apparent digestibility at ileal level, the correlations of fiber fractions were moderate (r of NDF = 0.53 to 0.63; ADF, 0.50 to 0.77; cellulose, 0.50 to 0.75), with an exception of CF content was relatively high (r of 0.58 to 0.81). The correlations to true digestibility of amino acids were weaker. In case of at fecal level, the higher correlation (negative) was found with NDF than CF content. Estimations of amino acids digestibility were performed using regression equation. The data showed that apparent digestibility of amino acids could be estimated for almost amino acids except arginine, threonine, valine and tyrosine at fecal level and phenylalaine, valine and glycine at ileal level. The best prediction at ileal and fecal level ($r^2=0.55-0.77$ and 0.52-0.76), respectively was obtained with NDF content. Prediction for true digestibility of amino acids, none of fiber fractions could be estimated for arginine, leucine and valine at all collection levels. At ileal level, CF could be used for most of amino acids except phenylalanine, glycine and praline; cellulose, only for lysine and methionine and NDF, only for proline. At fecal level, glutamine digestibility could be estimated only from CF and ADF content. The best predictor at ileal level was ADF content whereas at fecal level was NDF content. These results indicate that lignin content could not be used as predictor for all amino acids at both levels neither in apparent nor true digestibility.

• Food Science and Biotechnology
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• 제15권5호
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• pp.715-720
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• 2006

This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

• 한국컴퓨터정보학회논문지
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• 제21권10호
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• pp.21-28
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• 2016

The aim of this research is to analyze Perceived Usefulness(PU) and Perceived Ease of Use(PEOU) based on Technology Acceptance Model in , and how viewing experiences and knowledge of motion graphics have an impact on attitude toward using and behavioral intention to use. Both usability for learning and usability for appreciation in terms of PU have significant correlations with the degree of satisfaction and immersion, and behavioral intention to use. On the other hand, PEOU has an influence on degree of exhibition satisfaction and immersion, and onto behavioral intention to use with the exception of intention to revisiting . Unlike PU or PEOU, previous viewing experiences do not have correlation with attitude toward using and behavioral intention to use. Only previous knowledge of motion graphics has a correlation with degree of satisfaction and immersion, and behavioral intention to use. As the influence on PU and PEOU's attitude toward using and and behavioral intention to use has been verified, our findings show that two variables of TAM enable the prediction of user's technology acceptance on digital exhibitions and as a result prove the suitability for TAM as an evaluation model for digital exhibition of remediating the originals. This study offers a fresh understanding of the importance of motion graphic effects which influence attitude toward using and behavioral intention to use from the perspective of curating methodology.

• 대한화학회지
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• 제32권5호
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• pp.458-463
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• 1988

역상 액체크로마토그래피법으로 페놀류에 대한 분리현상을 용해도파라미터이론에 의해 알아 본 결과 예측한 용리거동이 제한된 범위내에서만 일치하고 있었다. 이 용해도 파라미터이론에 의한 용리현상의 설명은 실제 실험의 결과와 상당히 상이하게 나타났고 많은 예외가 있었다. 그러므로 새로운 용질-용매상호작용파라미터 ${\delta}_{im}$ 을 첨가하여 실제 실험값에 가까운 용해도파라미터 이론식으로 수정하였다. 이 새로운 용질-용매상호작용파라미터, ${\delta}_{im}$ 는 용매의 종류, 용매분율과 용질의 구조에 의존하고 있으며 이 파라미터, ${\delta}_{im}$와 혼합이동상의 용해도파라미터, ${\delta}_{im}$ 와는 직선의 관계가 있었다. 이것은 머무름거동을 예측하는데 이전의 Schoenmakers의 식보다 더 좋은 결과로 나타났다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권8호
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• pp.3111-3116
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• 2015

Background: This study was designed to investigate the value of CEA and CA199 in predicting the treatment response to palliative chemotherapy for advanced gastric cancer. Materials and Methods: We studied 189 patients with advanced gastric cancer who received first-line chemotherapy, measured the serum CEA and CA199 levels, used RECIST1.1 as the gold standard and analyzed the value of CEA and CA199 levels changes in predicting the treatment efficacy of chemotherapy. Results: Among the 189 patients, 80 and 94 cases had increases of baseline CEA (${\geq}5ng/ml$) and CA199 levels (${\geq}27U/ml$), respectively. After two cycles of chemotherapy, 42.9% patients showed partial remission, 33.3% stable disease, and 23.8% progressive disease. The area under the ROC curve (AUC) for CEA and CA199 reduction in predicting effective chemotherapy were 0.828 (95%CI 0.740-0.916) and 0.897 (95%CI 0.832-0.961). The AUCs for CEA and CA199 increase in predicting progression after chemotherapy were 0.923 (95%CI 0.865-0.980) and 0.896 (95%CI 0.834-0.959), respectively. Patients who exhibited a CEA decline ${\geq}24%$ and a CA199 decline ${\geq}29%$ had significantly longer PFS (log rank p=0.001, p<0.001). With the exception of patients who presented with abnormal levels after chemotherapy, changes of CEA and CA199 levels had limited value for evaluating the chemotherapy efficacy in patients with normal baseline tumor markers. Conclusions: Changes in serum CEA and CA199 levels can accurately predict the efficacy of first-line chemotherapy in advanced gastric cancer. Patients with levels decreasing beyond the optimal critical values after chemotherapy have longer PFS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.3989-4006
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• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• 대한영양사협회학술지
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• 제15권1호
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• pp.52-68
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• 2009

This study compared activity factor. predicted resting metabolic rate (RMR), and nutrient intakes between athletic and non-athletic high school students in Gangwon-do. Fifty soccer players (30 males and 20 females; mean ages 16.7${\pm}$1.0 years and 16.4${\pm}$1.1 years. respectively) and 50 non-athletic (30 males and 20 females: mean ages 17.5${\pm}$0.4 years and 16.4${\pm}$1.1 years respectively) high school students were included. Anthropometric measurements included: weight and height. triceps skinfold, mid-ann circumference, and body fat. Prediction equations consisted of those from the Harris-Benedict. FAO/WHO/VNU, IMNA, Cunningham, Mifflin et al., and Owen et al. A one-day activity diary was collected by interview, and the 24-hour recall method was used to analyze nutrient intakes of subjects. The activity factors of the male and female athletic groups (2.23 and 2.16, respectively) were significantly higher than those (1.52 and 1.46, respectively) of the non-athletic group. There was only a significant difference in RMR by use of the Cunningham's equation between two groups. For the males. almost all nutrient intakes of the athletic group (except carbohydrate, iron, vitamin $B_1$, $B_6$, and niacin) of athletic group were significantly higher than those of the non-athletic group. The female athletic group showed significantly higher nutrient intakes with the exception of most vitamins. These results suggest that assessments of energy balance between energy intake and energy expenditure by employing RMR and activity factors would be useful to prevent and treat obesity in high school athletes. In addition, the Cunningham's equation would be appropriate for predicting their energy needs.