• The Korean Journal of Pesticide Science
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• v.17 no.4
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• pp.314-334
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• 2013

This study explored an efficient modified Quick, Easy, Cheap, Effective, Rugged and safe (QuEChERS) method combined with liquid chromatography-electrospray ionization with tandem mass spectrometric detection for the analysis of residues of 76 pesticides in brown rice, barley and corn including acidic sulfonylurea herbicides. Formic acid (1%) acid in acetonitrile and dispersive solid phase extractions used for extraction of pesticides and clean-up of the extract respectively. Two fortified spikes at 50 and 200 ng $g^{-1}$ levels were performed for recovery test. Mean recoveries of majority of pesticides at two spike levels ranged from 73.2 to 132.2, 80.9 to 136.8, 66.6 to 143.5 for brown rice, barley and corn respectively with standard error (CV) less than 10%. Good linearity of calibration curves were achieved with $R^2$ > 0.9907 within the observed concentration ranged. The modified method also provided satisfactory results for sulfonylurea herbicides. The method was applied to the determination of residues of target pesticides in real samples. A total of 26 pesticides in 36 out of 98 tasted samples were observed. The highest concentration was observed for tricyclazole at 1.17 mg $kg^{-1}$ in brown rice. This pesticide in two brown rice samples exceeded their MRLs regulated for rice in republic of Korea. Except tricyclazole none of the observed pesticides' concentration was higher than their MRLs. The results reveal that the method is effectively applicable to routine analysis of residues of target pesticides in brown rice, barley and corn.

• The Journal of Information Systems
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• v.24 no.2
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• pp.23-52
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• 2015

Purpose This study aims to understand the role of digital knowledge in accepting the green technology. This study combined digital option theory with the second version of the Unified Theory of Acceptance and Use of Technology (UTAUT2). Contrary to other studies in which the UTAUT2 is used to explain IT adoption behavior, we look at the relationship between IT and the UTAUT2 from a new angle, incorporating an important aspect of IT, that is, digitized knowledge richness, as a determinant of the UTAUT2. Design/methodology/approach Grounded in the UTAUT2, a content analysis was conducted to investigate novel constructs dedicated to explaining green technology adoption. In this study, an amended version of the UTAUT2 specific to green technology is offered that better explains the green technology adoption behavior of consumers. Using the items identified by content analysis, we developed a questionnaire with 36 survey items. We measured all the items on a seven-point Likert-type scale. We randomly selected 402 survey respondents from a set of panel data. After a pilot study, we analyzed the main survey data by using PLS 2.0M3 and SPSS 20.0, and employed structural equation modeling to test the hypotheses. Findings The results suggest that the UTAUT2 was found to be extendable to technologies other than conventional IT. Social influence is more significant than conventional utilitarian and hedonic-based constructs such as those utilized in the UTAUT and UTAUT2 in explaining adoption behavior in the context of green technologies. The hypothesized connection between digitized knowledge richness and adoption intention was supported by the results of studies on the role of IT in formation of attitudes toward eco-friendly production. The results also indicate that digital knowledge can also encourage people to try green technology when they learn that their peers are already using the technology successfully.

• Journal of Forest and Environmental Science
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• v.24 no.1
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• pp.41-46
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• 2008

Progeny tests of Abies holophylla were established with 32 open-pollinated families at Hwaseong and Gangneung in 1994. Growth characteristics (height, DBH and volume index) were measured at the age of 15, showing that Gangneung site showed in general better performance than Hwaseong site. Analysis of variance (ANOVA) of the growth characteristics showed that there was a significant difference among families in Gangneung but not in Hwaseong, and Hwaseong site showed that DBH and volume index were statistically different among replications. At Gangneung site, family ${\times}$ replication interaction was significant in DBH and volume index. Based on the combined analysis of both sites, all characteristics except height showed highly significant differences between sites and among families. On the other hand, family ${\times}$ replication interaction was not significant, implying that growth pattern of families could be similar at Gangneung and Hwaseong. Individual heritabilities ($hi^2$) at Gangneung were 0.485 in height, 0.611 in DBH and 0.538 in volume index, and the values of $hi^2$ at Hwaseong were 0.121 in height, 0.054 in DBH and 0.080 in volume index, respectively. Based on both sites, $hi^2$ was estimated as 0.204 in height, 0.326 in DBH and 0.238 in volume index. Individual heritabilities (0.054~0.611) were lower than family heritabilities (0.089~0.723) for all growth characteristics. Realized gain was estimated to be 2.5% in height, 9.2% in DBH and 23.6% in volume. When inferior families (about 50% of all families) are genetically thinned from a seed orchard, genetic gain would be 9.55% in height, 17.0% in DBH and 46.8% in volume.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• Journal of Animal Environmental Science
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• v.6 no.3
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• pp.175-184
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• 2000

A lab-scale MF membrane reactor was installed to investigate the membrane permeability, characteristics of membrane fouling at each conditions, and quality of permeate (liquid livestock manure) in the separation of solid-matters using membrane. Experiment was divided three filtration type such as follows; continuous filtration, gravity filtration, and intermittent filtration. As a result of experiment, flux 1 LMH was maintained for 7days, and trans-membrane pressure(TMP) was increased gradually under 10cmHg, but it was increased immediately after 10cmHg, respectively. However, the flux was increased, the Tmax was decreased exponential more and more. During the pure-flux test, most of the fouling of membrane was reversible. At the gravity filtration, permeate could be obtained as 1.75 LMH for 3.5days without any other electronic pressure. As an investigation of membrane surface, this study could be decided that the reason of fouling at the lower flux (Run 1 and 2) was attached matters in membrane surface, but at the higher flux (Run 4-6) was concentration polarization.

• Applied Biological Chemistry
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• v.50 no.4
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• pp.245-252
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• 2007

FTA (fault tree analysis), an analytical method for system failure management, was employed in the management of faults in running PCR analysis. PCR is executed through several processes, in which the process of PCR machine operation was selected for the analysis by FTA. The reason for choosing the simplest process in the PCR analysis was to adopt it as a first trial to test a feasibility of the FTA approach. First, fault events-top event, intermediate event, basic events-were identified by survey on expert knowledge of PCR. Then those events were correlated deductively to build a fault tree in hierarchical structure. The fault tree was evaluated qualitatively and quantitatively, yielding minimal cut sets, structural importance, common cause vulnerability, simulation of probability of occurrence of top event, cut set importance, item importance and sensitivity. The top event was 'errors in the step of PCR machine operation in running PCR analysis'. The major intermediate events were 'failures in instrument' and 'errors in actions in experiment'. The basic events were four events, one event and one event based on human errors, instrument failure and energy source failure, respectively. Those events were combined with Boolean logic gates-AND or OR, constructing a fault tree. In the qualitative evaluation of the tree, the basic events-'errors in preparing the reaction mixture', 'errors in setting temperature and time of PCR machine', 'failure of electrical power during running PCR machine', 'errors in selecting adequate PCR machine'-proved the most critical in the occurrence of the fault of the top event. In the quantitative evaluation, the list of the critical events were not the same as that from the qualitative evaluation. It was because the probability value of PCR machine failure, not on the list above though, increased with used time, and the probability of the events of electricity failure and defective of PCR machine were given zero due to rare likelihood of the events in general. It was concluded that this feasibility study is worth being a means to introduce the novel technique, FTA, to the management of faults in running PCR analysis.

• Journal of Korean Academy of Nursing
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• v.26 no.2
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• pp.387-398
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• 1996

The objective of this study was to clarify whether there are any differences between normal and over-weight middle-aged(40∼59yrs)women in their perceived weight, health status, health conception and health behavior choices. The sample consisted of 39 normal weight and 55 over-weight (11％ above on the Body Index Scale) women who live in Juan, Inchon. The Participants were randomly selected in each weight group considering socio-demographic factors. The findings from this study are summarized below. 1) Among the 55 overweight middle-aged women, 16 were above 20％ on the Body Index Scale and 14 were above 30％. Twenty-five(45.5％) of the overweight group and 12(30.8％) of the normal weight group had one disease, and there were 12(21.8％) in the overweight group and 8(20.5％) in the normal weight group where one of the family members had a disease, but these differences were not statistically significant. The average monthly family income for the overweight group was ￦l,880,000 compared to ￦2,140, 000 for the normal weight group, but this difference was also not significant. The age range for the whole group was between 40 and 59(mean＝46.8 for total, 48.6 for overweight and 45.7 for normal weight group). Again no significant difference found. Occupations were housemaker 53(56.4％), private business(13.8％), salarywoman(9.6％), and teacher (2.1％). Thirty housemaker(54.5％) from the overweight group and 23(59％) from the normal group did not constitute a statistically significant different. For the educational status, 34(61.8％) of the overweight women and 33(84.6％)of the normal weight group finished high school or more educational courses, but there was no significant statistical difference. Eleven(20.0％) of the overweight women and 5(12. 8％) of the normal weight group were single, but again no significant statistical difference was found. 2) A test for difference in health characteristics between two weight groups indicated that two groups do not show statistical differences in their perceived health status, health conception or health behavior choice. That is, the overweight group, also perceive their health status as good as the normal group, and regard ‘Health’ as a state that enables them to carry out social roles and functions rather than as the traditional concept of health as no disease or no symptoms. Moreover. the overweight group selected their health behaviors not for the prevention of diseases or maintenance of health but for promotion of health. To determine if no statistical difference might be related to the overweight group's failure of perceive themselves as overweight, the perceived and objective overweight status were compared by the chi-square analysis, and no difference was found（X/sup²＝49.37, df＝1, p＝.000）. However, 7(17.9％) of the normal group perceived themselves as being overweighted and 7(12.7％) of the overweight group thought they were of normal weight. Even though the overweight group employed in this study perceived themselves as being overweight, they regarded themselves as healthy as those in the normal weight group. It was shown that there was no statistical difference between two groups in health conception, and that they chose health behaviors to promote health status. 3) Perceived health conception was shown to be significantly related to health behavior choice （r＝ .28, p＝.006 for whole group : r＝.33, p＝.014 for overweight group : and r＝.12. p＝.463 for normal group） .There was an indication that the more complicated the perceived health conception was, the more the trend of health behavior choice to promote health. This was especially true for the overweight group. But, the perceived health status did not related to health behavior choice statistically（r＝.13, p＝.202）, and it was thought that reasons for selecting health behaviors were not related to their health status. That is, the overweight group perceive themselves as healthy as the normal weight group or thought that overweight itself does not incur any risk on their health. Data from two groups were combined and analyzed with multiple regression methodology, because the relationship pattern of the two groups was similar. The analysis showed that health behavior has a significant relationship with age and the perceived health conception（r/sup²＝.1517, p=.05, F＝8.133）. It means they come to health behavior along with their health conception and their age rather than their weights, perceived weight, health status or other social characteristics. This study was intended to understand how overweight middle-aged women perceive ‘weight’ and ‘health’, and how they meet their health related needs in comparison with normal weight middle-aged women. Other factors related to the health behavior in overweight middle-aged woman need to be determined through further descriptive studies outlined in the following recommendations. a) Reseach with the study area expanded. b) Reseach with grouping more detailed : much more overweight and underweight group c) Reseach on restricted relationship between overweight and age or profession. d) Reseach on what overweight middle-aged women do to reduce their weight and what factors motivate them to do it

• Journal of the Korea Concrete Institute
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• v.26 no.2
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• pp.151-157
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• 2014

Since recently developed Ultra-High-Performance-Concrete (UHPC) provides very high strength, stiffness, and durability, many studies have been made on the application of the UHPC to bridge decks. Due to high strength and stiffness of UHPC bridge deck, the structural contribution of top flange of steel girder composite to UHPC deck would be much lower than that of conventional concrete deck. At this point of view, this study proposes a inverted-T shaped steel girder composite to UHPC deck. This girder requires a new type of shear connector because conventional shear connectors are welded on top flange. This study also proposes three different types of shear connectors, and evaluate their ultimate strength via push-out static test. The first one is a stud shear connector welded directly to the web of the girder in the transverse direction. The second one is a puzzle-strip type shear connector developed by the European Commission, and the last one is the combination of the stud and the puzzle-strip shear connectors. Experimental results showed that the ultimate strength of the transverse stud was 26% larger than that given in the AASHTO LRFD Bridge Design Specifications, but a splitting crack observed in the UHPC deck was so severe that another measure needs to be developed to prevent the splitting crack. The ultimate strength of the puzzle-strip specimen was 40% larger than that evaluated by the equation of European Commission. The specimens combined with stud and puzzle-strip shear connectors provided less strength than arithmetical sum of those. Based on the experimental observations, there appears to be no advantage of combining transverse stud and puzzle-strip shear connectors.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

• Journal of the Korea Concrete Institute
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• v.19 no.5
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• pp.613-621
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• 2007

Due to the increasing significance of durability, much researches on carbonation, one of the major deterioration phenomena are carried out. However, conventional researches based on fully hardened concrete are focused on prediction of carbonation depth and they sometimes cause errors. In contrast with steel members, behaviors in early-aged concrete such as porosity and hydrates (calcium hydroxide) are very important and may be changed under carbonation process. Because transportation of deteriorating factors is mainly dependent on porosity and saturation, it is desirable to consider these changes in behaviors in early-aged concrete under carbonation for reasonable analysis of durability in long term exposure or combined deterioration. As for porosity, unless the decrease in $CO_2$ diffusion due to change in porosity is considered, the results from the prediction is overestimated. The carbonation depth and characteristics of pore water are mainly determined by amount of calcium hydroxide, and bound chloride content in carbonated concrete is also affected. So Analysis based on test for hydration and porosity is recently carried out for evaluation of carbonation characteristics. In this study, changes in porosity and hydrate $(Ca(OH)_2)$ under carbonation process are performed through the tests. Mercury Intrusion Porosimetry (MIP) for changed porosity, Thermogravimetric Analysis (TGA) for amount of $(Ca(OH)_2)$ are carried out respectively and analysis technique for porosity and hydrates under carbonation is developed utilizing modeling for behavior in early-aged concrete such as multi component hydration heat model (MCHHM) and micro pore structure formation model (MPSFM). The results from developed technique is in reasonable agreement with experimental data, respectively and they are evaluated to be used for analysis of chloride behavior in carbonated concrete.