• Korean Journal of Poultry Science
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• v.38 no.3
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• pp.173-179
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• 2011

This experiment was conducted to evaluate the dietary effects of multiple mixture of probiotics on laying performance and the faecal examination in laying hens (Hy-line Brown) at the early (21~40 wk) and middle (41~65 wk) laying term. Multiple probiotics were produced by developing products and the properties of microorganisms were examined for detecting of acid-resistance, bile salt-resistance and antibacterial activity against pathogenic enteric bacteria. Probiotics produced to the fermenting cultures of four selected organisms and soybean meal substrates by nine steps of NK proliferating system. The most microorganisms were shown higher resistance of acidity and bile salt. High antibacterial activities against Bacillus subtilis, Lactobacillus plantarum and Enterococcus faecium were observed, but was not against Saccharomyces cerevisiae. Total egg production of the treatment was significantly higher than control group but was not statistically different between 0.1% and 0.2% treatments (P>0.05). Average egg weight of the treatment in early laying term was also significantly higher than control but was not significantly different between 0.1% and 0.2% treatments (P>0.05). But the egg weight of the treatment in middle laying term was significantly higher than control and between 0.1% and 0.2% treatments (P>0.05). The mortality of 0.2% treatment was significantly lower than control (P<0.05), and 0.2% treatment in the early laying term was tended to decreased than 0.1% treatment and control. But there was not significantly between 0.1% and 0.2% treatments in middle laying term. In feed intake, 0.2% treatment in middle laying term was significantly increased than control and 0.1% treatment (P<0.05) but not in early laying term. In faecal examination, the total number of Lactobacillus of 0.1% treatment was significantly increased than control in whole laying term (P<0.05), but Coli form of the treatment was decreased than control in middle laying term. In conclusion, dietary long term supplementation of multiple probiotics improved performance of lay hens, egg weight and mortality drop by regulating enteric bacteria.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Journal of Bio-Environment Control
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• v.25 no.1
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• pp.63-70
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• 2016

Water drainage from the open hydroponics often causes significant environmental pollution due to agrochemicals and loss of water and nutrients. The objectives of this study were to show the potential application of an irrigation schedule based on threshold values of volumetric substrate water content for tomato (Solanum lycopersicum L. 'Samsamgu') cultivation in a commercial hydroponic farm during spring to summer cultivation. This study was performed for minimizing effluent from coir substrate hydroponics using a frequency domain reflectometry (FDR) sensor-automated irrigation, as compared with an integrated solar-radiation (IR) and conventional timer-irrigation (TIMER) after transplanting. In results, no significant difference in daily irrigation volume was found among the treatments until 88 days after transplant (DAT). However, during the 88 to 107 DAT, the daily irrigation volume was in the order of IR (2125 mL) > TIMER (2063 mL) > FDR (1983 mL), and during the 108 to 120 DAT, it was in the order of IR (2000 mL) > TIMER (1664 mL) > FDR (1500 mL). The lowest drainage volume was observed in the FDR treatment with the order of IR (12~19%) > TIMER (4~12%) > FDR (0~7%) during the entire growing period. A lower irrigation volume in the FDR treatment after 88 DAT may be due to the sensor's detecting capacity for less water absorption by plant after completing fruit maturity with apical pruning and removal of lower leaves, while a higher irrigation volume in the IR treatment may be due to gradual increase in integrated solar-radiation amount as closer to summer season. There was no significant difference in plant growth and fruit yield among the treatments; however, a 11% and 18% of higher soluble sugar content was observed in the FDR than that of TIMER and IR treatment. respectively.

• Journal of Radiation Protection and Research
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• v.25 no.4
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• pp.223-232
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• 2000

Comparative study was performed for the assessment of DNA damage and Chromosomal aberration in human lymphocyte exposed to low dose radiation using fluorescence in situ hybridization(FISH) and single cell gel electrophoresis(SCGE). Chromosomal aberrations in human lymphocytes exposed to radiation at doses of 5, 10, 30 and 50cGy were analysed with whole chromosome-specific probes by human chromosome 1, 2 and 4 according to PAINT system. FISH with chromosome-specific probe has been used to be a valid and rapid method fer detection of chromosome rearrangements induced by low dose radiation. The frequencies of stable translocation per cell equivalents were 0.0116, 0.0375, 0.040f, 0.0727 and 0.0814 for 0, 5, 10, 30 and 50cGy, respectively, and those of dicentric were 0.00, 0.0125, 0.174, 0.0291 and 0.0407 respectively. Radiation induced DNA damage in human lymphocyte in a dose-dependent manner at low doses from 5cGy to 50cGy, which were analysed by single tell gel electrophoresis(SCGE). From above results, FISH seemed to be useful for radiation biodosimetry by which the frequencies of stable aberrations in human lymphocyte can be observed more easily than by conventional method and SCGE also seemed to be sensitive method f9r detecting DNA damage by low dose radiation exposure, so that those methods will improve our technique to perform meaningful biodosimetry for radiation at low doses.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.6
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• pp.309-315
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• 2006

Purpose: Accurate evaluation of cervical lymph node (LN) metastasis of head and neck squamous cell canter (SCC) is important to treatment planning. We evaluated the diagnostic accuracy of F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for the detection of cervical LN metastasis of head and neck SCC and performed a retrospective comparison with CT/MRI findings. Materials & Methods: Seventeen patients with pathologically proven head and neck SCC underwent F-18 FDG PET/CT and CT/MRI within 4 week before surgery. We recorded lymph node metastases according to the neck level system of imaging-based nodal classification. F-18 FDG PET/CT images were analyzed visually for assessment of regional tracer uptake in LN. We analyzed the differences in sensitivity and specificity between F-18 FDG PET/CT and CT/MRI using the Chi-square test. Results: Among the 17 patients, a total of 123 LN levels were dissected, 29 of which showed metastatic involvement. The sensitivity and specificity of F-18 FDG PET/CT for detecting cervical LN metastasis on a level-by-level basis were 69% (20/29) and 99% (93/94). The sensitivity and specificity of CT/MRI were 62% (18/29) and 96% (90/94). There was no significant difference in diagnostic accuracy between F-18 FDG PET/CT and CT/MRI. Interestingly, F-18 FDG PET/CT detected double primary tumor (hepatocellular carcinoma) and rib metastasis, respectively. Conclusion: There was not statistically significant difference of diagnostic accuracy between F-18 FDG PET/CT and CT/MRI for the detection of cervical LN metastasis of head and neck SCC. The low sensitivity of F-18 FDG PET/CT was due to limited resolution for small metastatic deposits.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.126-134
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• 2017

There have been numerous studies on extracting the R-peak from electrocardiogram (ECG) signals. However, most of the detection methods are complicated to implement in a real-time portable electrocardiograph device and have the disadvantage of requiring a large amount of calculations. R-peak detection requires pre-processing and post-processing related to baseline drift and the removal of noise from the commercial power supply for ECG data. An adaptive filter technique is widely used for R-peak detection, but the R-peak value cannot be detected when the input is lower than a threshold value. Moreover, there is a problem in detecting the P-peak and T-peak values due to the derivation of an erroneous threshold value as a result of noise. We propose a robust R-peak detection algorithm with low complexity and simple computation to solve these problems. The proposed scheme removes the baseline drift in ECG signals using an adaptive filter to solve the problems involved in threshold extraction. We also propose a technique to extract the appropriate threshold value automatically using the minimum and maximum values of the filtered ECG signal. To detect the R-peak from the ECG signal, we propose a threshold neighborhood search technique. Through experiments, we confirmed the improvement of the R-peak detection accuracy of the proposed method and achieved a detection speed that is suitable for a mobile system by reducing the amount of calculation. The experimental results show that the heart rate detection accuracy and sensitivity were very high (about 100%).

• Korean Journal of Food Science and Technology
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• v.42 no.4
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• pp.494-501
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• 2010

The purpose of this study was to examine the presence of Bacillus cereus, aerobic bacteria and coliforms in the raw material of infant formulas and investigate the manufacturing process in terms of microbial safety. Among ten kinds of raw infant formula material samples (n=20), Bacillus cereus appeared in two (n=4). Aerobic bacteria were not detected in raw infant formula material or maximum 4.15 log CFU/g. Eleven species of aerobic bacteria were isolated and 76% of them were Sphingomonas paucimobilis, Pseudomonas fluorescens, Rhizobium radiobactor, or Stenotrophomonas maltophilia. A Pearson's correlation analysis revealed that the most influential factors for detecting Bacillus cereus were aerobic bacteria and coliforms. In other words, when the measured values of aerobic bacteria and coliforms were higher, the possibility that Bacillus cereus would appear increased. In a regression model to predict Bacillus cereus, the rate of appearance was correlated with aerobic bacteria and coliforms, and its contribution rate for effectiveness was 86%. Improving microbial quality control by pasteurization, spray dry, popping and extrusion resulted in a decrease in the numbers of Bacillus cereus, aerobic bacteria and coliforms in the raw materials. The results suggest that a hazard analysis and critical control point system might be effective for reducing microbiological contamination.

• Journal of Dairy Science and Biotechnology
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• v.33 no.2
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• pp.119-127
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• 2015

To date, detection of microbial populations in dairy products has been performed using culture media, which is a time-consuming and laborious method. The recently developed chromogenic media could be more rapid and specific than classical culture media. However, the newly developed molecular-based technology can detect microbial populations with greater rapidity and sensitivity than the classical method involving culture media and chromogenic media. This molecular-based technology could provide various options for monitoring the characterization of different states of bacteria and cells. Thus, it could help upgrade the processing system of the dairy industry so as to maintain the safety and quality of dairy foods. Among the various newly developed molecular-based technologies, flow cytometry can potentially be used for monitoring microbiological populations in the dairy industry if official international standards are available for this purpose. When omics technology would have biomarker identification, it could be regarded as the rapid and sensitive analytical methods. Methods based on PCR, which has become a basic technique in microbiological research, can be developed and validated as alternative methods for quantification of dairy microorganisms. This review discusses methods for monitoring microbiological populations in dairy foods and the limitations of these studies, as well as the need for further research on such methods in the dairy industry.

• Tuberculosis and Respiratory Diseases
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• v.47 no.4
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• pp.478-487
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• 1999

Background : Differential diagnosis of pleural malignant mesothelioma from secondary metastatic adenocarcinoma is often difficult. A variety of pathologic techniques have been developed to make a differential diagnosis of carcinoma from mesothelioma. Immunohistochemistry detecting diverse antigenic substances such as CEA, Leu-M1, Bn-3, S-100 protein, vimentin, CK and EMA has been claimed to be of value as a panel in the differential diagnosis of adenocarcinoma from mesothelioma. The aim of this study was to investigate the suitable antibodies to distinguish mesothelioma from metastatic adenocarcinoma and establish candidate markers in a panel. Methods : Complete, one-hour immunohistochemical staining using antibodies against cytokeratin (CK), epithelial membrane antigen(EMA), S-100 protein, vimentin, B72-3, Leu-M1, and carcino-embryonic antigen(CEA) was applied to cell blocks from 7 mesotheliomas and 7 adenocarcinomas which were confirmed by electron microscopic and histpathologic methods. Results : All adenocarcinomas and 71.4% of mesotheliomas expressed the cytokeratin and EMA. S-100 protein and vimentin were expressed in 57.1% and 42.9% of mesotheliomas and 14.3% and 28.5% of adenocarcinomas, respectively. B72-3 was expressed in all adenocarcinomas, but in none of mesotheliomas. Leu-M1 was positive in 71.4% of the adenocarcinoma and 14.3% of the mesotheliomas. CEA was positive in all adenocarcinomas and 42.9% of mesotheliomas. Leu-M1 and B72-3 were coexpressed in 71.4% of adenocarcinomas but in none of mesothelioma. B72-3 and CEA were coexpressed in all adenocarcinomas, but in none of mesotheliomas. Conclusion : We concluded that B72-3 immunohistochemistry or panel staining of B72-3 and CEA could be recommanded for the differential diagnosis of pleural mesothelioma from metastatic adenocarcinoma.