• Journal of Animal Science and Technology
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• v.50 no.4
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• pp.499-508
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• 2008

This study was conducted to evaluate the effect of bio-starch from corn processing to replace dried whey in weaned pigs. A total of 120 crossbred [(Landrace×Yorkshire)×Duroc] pigs were weaned at 21 days of age weighing 6.01±0.34 kg in average. Five week feeding trial consisted of phase 1(0~2 wks) and phase 2(3~5 wks). Dietary treatments included 1) CON(basal diet), 2) BS5(whey 5%, partial substitution of bio-starch), 3) BS10(whey 10%, partial substitution of bio-starch) and 4) BS15(whey 15%, partial substitution of bio-starch). There were four dietary treatments with six replicate pens per treatment and five pigs per pen. During the overall period, there were no significant differences in the ADG(average daily gain) and gain/feed ratio among the treatments(P>0.05). However, the ADFI(average daily feed intake) was higher in BS5 and BS15 treatments than in CON treatment(P<0.05). At the 2nd week, dry matter and nitrogen digestibility were increased(quadratic effect, P=0.03 and P=0.01, respectively; cubic effect, P<0.001 and P=0.01, respectively) with the highest at 10% of bio-starch inclusion in the diets. At the last week of the experiment, dry matter, nitrogen and energy digestibility were increased(P<0.05) with the highest at 5% of bio-starch inclusion in the diets. At the 2nd week total protein concentration was increased(linear effect, P=0.04; cubic effect, P=0.01) with the highest at 10% of bio-starch inclusion in the diets. Also, BUN(blood urea nitrogen) was increased(linear effect, P=0.01) as the level of bio-starch inclusion increased in the diets. Fecal consistency score was inclined to lowers CON treatment than other treatments. In conclusion, the result of trial indicates that bio-starch can be included at the level of 5~10% of weaning pig diet replacing part of the dried-whey, and digestibilities were positively affected by bio-starch at growth stage.

• Journal of The Korean Society of Grassland and Forage Science
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• v.24 no.2
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• pp.93-104
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• 2004

This pot experiment was conducted to investigate the effects of combined micronutrient application($T_1$; control, $T_2$; Fe, $T_3$; Fe+Mn, $T_4$; Fe+Mn+Cu, $T_5$ ; Fe+Mn+Cu+Zn, $T_6$ ; Fe+Mn+Cu+Zn+Mo, T$_{7}$; Fe+Mn+Cu+Zn + Mo + B) on forage performance of pure and mixed cultures of orchardgrass and white clover. The fifth part was concerned with the changes in the total and relative contents, uptake amounts, and mutual ratios. of micronutrients in forages. The results obtained are summarized as follows: 1. The relative contents(total contents of 6 micronutrients = 100%) of Fe and Mn were considerably influenced by the antagonism between Fe and Mn, and also were influenced by the differences in Mn-absorption between orchardgrass and white clover. Compared with pure culture, orchardgrass showed high relative contents of Mn, and low relative contents of Fe and B in mixed culture. White clover, however, tended to be exactly opposed to the above trends. In relative contents, the T$_6$ 6/ resulted generally in decrease of Fe. However the $T_7$ resulted in increase of Mn and B. In addition, the $T_7$ resulted in decrease of Cu and Zn in orchardgrass, and Mo in white clover. 2. In general, there were differences in the tendency between the yield changes and the uptake amounts of micronutrients. General differences have been showed in the uptake amounts and mutual ratios of micronutrients based on the forage species, pure/mixed culture, additional fertilization, and antagonism. The uptake amounts of total micronutrients were generally increased by the treatments with increased combination. In uptake amounts, the $T_7$ resulted in the increase of Mn and B, and decrease of Mo. 3. The mutual ratios of Fe/Mn, Fe/Cu, and Mn/Cu were considerably influenced by the antagonism between Fe and Mn. At the $T_7$ , very low ratio of Fe/Mo affected by the T6 tended to be somewhat improved because of the decrease of Mo content． The poor growth of forages at the $T_6$ was improved by the $T_7$ . This fact was likely to be caused by the adequate B/Mo ratio.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.21 no.1
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• pp.97-124
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• 1976

To find out the most effective method of treatments for the induction of sprouting of dormant seed potato pieces for the fall crop production of Irish cobbler, this experiment was carried out with sprout inducing bed and field performance trial. In GA treatments, about 10 days were required to sprout and resulted uniform and thin 3-4 sprouts per tuber piece, but sprouts were slender and rooting was not observed. In Ethrel treatments, 20-25 days were required, and sprouts were inferior than that of GA treatment in uniformity of sprouting, and percentage of rotten pieces and of healthy sprouted tuber pieces, but number of sprouts per tuber pieces was low, being 1-2, and sprouts were short, thick, and healthy, and showed good rooting. In GA and Ethrel mixture treatments, 1-2 more days were required to sprout than GA treatments, but sprouts were relatively healthy, and other sprouting pattern were like that of GA treatments. In Ethylene chlorohydrin and 6-Benzyl-adenine treatments, sprouting was like that of Ethrel treatments, but much more days were required than Ethrel treatments and tendency of severe rotting was observed. Optimum treating methods of promising chemicals found to be 1-2 and 2-5 ppm GA solution, 500 and 1000-2000 ppm Ethrel solution, and 1-2＋250-500 and 5＋250-500 ppm GA and Ethrel mixture solution for 60 min. treatment of tuber piece and whole-tuber, respectively. Induction of sprouting in dry and hot time resulted severer rotting of tuber pieces during the induction of sprouting and with the advancement of dormancy, being delayed in date of treatment, tendency of promotion of sprouting and rooting was observed. When sprouted tuber piece was transplanted at the same date, yields were in order of Ethrel, GA and Ethrel mixture, and GA treatment, indicating the correlation between yield and healthiness of sprout and rooting status of sprouted tuber piece. In all treatments, earlier transplanting resulted higher yields.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.17 no.2
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• pp.93-103
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• 1981

It is well-known that nowadays heat resisting and anti-corrosive materials have been widely used as the components materials of gas turbines, nuclear power plants and engines etc. In the fields of machine production industry. And materials for engine components, like as the exhaust valve of internal combustion engine, have been required to operate under the high temperature range of $700^{\circ}C$-$800^{\circ}C$ and high pressured gas with repeated mechanical load for the high performance of engines. For these components, friction welding for bonding of dissimilar steels can be applied for in order to obtain process shortening, production cost reduction and excellent bonding quality. And age hardening recently has been noticed to the heat resisting materials for further strengthening of high temperature strength, especially high temperature fatigue strength. However, it is difficult to find out any report concerning the effects of age hardening for strengthening high temperature fatigue strength to the Friction welded heat resisting and anti-corrosive materials. In this study the experiment was carried out as the high temperature rotary bending fatigue testing under the condition of $700^{\circ}C$ high temperature to the friction welded domestic heat resisting steels, SUH3-SUS303, which were 10hr., 100hr. aging heat treated at $700^{\circ}C$ after solution treatment 1hr. at $1, 060^{\circ}C$ for the purpose of observing the effects of the high temperature fatigue strength and fatigue fracture behaviors as well as with various mechanical properties of welded joints. The results obtained are summarized as follows: 1) Through mechanical tests and micro-structural examinations, the determined optimum welding conditions, rotating speed 2420 rpm, heating pressure 8kg/mm super(2), upsetting pressure 22kg/mm super(2), the amount of total upset 7mm (heating time 3 sec and upsetting time 2 sec) were satisfied. 2) The solution treated material SUH 3, SUS 303, have the highest inclination gradient on S-N curve due to the high temperature fatigue testing for long time at $700^{\circ}C$. 3) The optimum aging time of friction welded SUH3-SUS 303, has been recognized near the 10hr. at $700^{\circ}C$ after the solution treatment of 1hr. at $1, 060^{\circ}C$. 4) The high temperature fatigue limits of aging treated materials were compared with those of raw material according to the extender of aging time, on 10hr. aging, fatigue limits were increased by SUH 3 75.4%, SUS 303 28.5%, friction welded joints SUH 3-SUS 303 44.2% and 100hr. aging the rates were 64.9%, 30.4% and 36.6% respectively. 5) The fatigue fractures occurred at the side of the base matal SUS303 of the friction welded joints SUH 3-SUS 303 and it is difficult to find out fractures at the friction welding interfaces. 6) The cracking mode of SUS 303, SUH 3-303 is intergranular in any case, but SUH 3 is fractured by transgranular cracking.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Korean Journal of Soil Science and Fertilizer
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• v.10 no.1
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• pp.55-60
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• 1977

In order to study the availability of soil P and applied P to rice plant under water-logged system, a pot experiment with five soils having different levels of available P (24, 64, 100, 144 and 231 ppm) under four levels of applied P (0, 30, 60 and 90 ppm) was conducted. The availability of P was measured in terms of plant performance and the behaviors of P in soils were studied through the fractionation of various forms of P and by measuring the adsorption and desorption characteristics. The results are summarized us following. 1. The rice plant responded to applied P in the soils containing less than 144 ppm of available P as measured by Lancaster's method in terms of number of tillers in early growth stages. However, when the response of rice plant to applied P was evaluated in terms of grain yield there was no response even in the soil containing 24 ppm of available P. 2. Applied P was fixed as Al-P at the early stages and converted into Fe-P at later stages. 3. The P adsorption maxima of soils measured by Langmuir's isotherm ranged from 70 to 100mg/100g. No relationships between the level of available P and P adsorption maxima were observed. 4. There was a trend that the higher the level of available P, the higher the release of water soluble p. 5. The reduction of soil increased the level of available P by the factor of 1.8 times of air dried soils.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.253-263
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• 2013

Frequency Scanning Interferometry(FSI) system, one of the most promising optical surface measurement techniques, generally results in superior optical performance comparing with other 3-dimensional measuring methods as its hardware structure is fixed in operation and only the light frequency is scanned in a specific spectral band without vertical scanning of the target surface or the objective lens. FSI system collects a set of images of interference fringe by changing the frequency of light source. After that, it transforms intensity data of acquired image into frequency information, and calculates the height profile of target objects with the help of frequency analysis based on Fast Fourier Transform(FFT). However, it still suffers from optical noise on target surfaces and relatively long processing time due to the number of images acquired in frequency scanning phase. 1) a Polarization-based Frequency Scanning Interferometry(PFSI) is proposed for optical noise robustness. It consists of tunable laser for light source, ${\lambda}/4$ plate in front of reference mirror, ${\lambda}/4$ plate in front of target object, polarizing beam splitter, polarizer in front of image sensor, polarizer in front of the fiber coupled light source, ${\lambda}/2$ plate between PBS and polarizer of the light source. Using the proposed system, we can solve the problem of fringe image with low contrast by using polarization technique. Also, we can control light distribution of object beam and reference beam. 2) the signal processing acceleration method is proposed for PFSI, based on parallel processing architecture, which consists of parallel processing hardware and software such as Graphic Processing Unit(GPU) and Compute Unified Device Architecture(CUDA). As a result, the processing time reaches into tact time level of real-time processing. Finally, the proposed system is evaluated in terms of accuracy and processing speed through a series of experiment and the obtained results show the effectiveness of the proposed system and method.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.155-169
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• 2014

With the rapid advances in technologies, organizations are more likely to depend on information systems in their decision-making processes. Business Intelligence (BI) systems, in particular, have become a mainstay in dealing with complex problems in an organization, partly because a variety of advanced computational methods from statistics, machine learning, and artificial intelligence can be applied to solve business problems such as demand forecasting. In addition to the ability to analyze past and present trends, these predictive analytics capabilities provide huge value to an organization's ability to respond to change in markets, business risks, and customer trends. While the performance effects of BI system use in organization settings have been studied, it has been little discussed on the use of predictive analytics technologies embedded in BI systems for forecasting tasks. Thus, this study aims to find important factors that can help to take advantage of the benefits of advanced technologies of a BI system. More generally, a BI system can be viewed as an advisor, defined as the one that formulates judgments or recommends alternatives and communicates these to the person in the role of the judge, and the information generated by the BI system as advice that a decision maker (judge) can follow. Thus, we refer to the findings from the advice-giving and advice-taking literature, focusing on the role of explanations of the system in users' advice taking. It has been shown that advice discounting could occur when an advisor's reasoning or evidence justifying the advisor's decision is not available. However, the majority of current BI systems merely provide a number, which may influence decision makers in accepting the advice and inferring the quality of advice. We in this study explore the following key factors that can influence users' advice taking within the setting of a BI system: explanations on how the box-office grosses are predicted, types of advisor, i.e., system (data mining technique) or human-based business advice mechanisms such as prediction markets (aggregated human advice) and human advisors (individual human expert advice), users' evaluations of the provided advice, and individual differences in decision-makers. Each subject performs the following four tasks, by going through a series of display screens on the computer. First, given the information of the given movie such as director and genre, the subjects are asked to predict the opening weekend box office of the movie. Second, in light of the information generated by an advisor, the subjects are asked to adjust their original predictions, if they desire to do so. Third, they are asked to evaluate the value of the given information (e.g., perceived usefulness, trust, satisfaction). Lastly, a short survey is conducted to identify individual differences that may affect advice-taking. The results from the experiment show that subjects are more likely to follow system-generated advice than human advice when the advice is provided with an explanation. When the subjects as system users think the information provided by the system is useful, they are also more likely to take the advice. In addition, individual differences affect advice-taking. The subjects with more expertise on advisors or that tend to agree with others adjust their predictions, following the advice. On the other hand, the subjects with more knowledge on movies are less affected by the advice and their final decisions are close to their original predictions. The advances in predictive analytics of a BI system demonstrate a great potential to support increasingly complex business decisions. This study shows how the designs of a BI system can play a role in influencing users' acceptance of the system-generated advice, and the findings provide valuable insights on how to leverage the advanced predictive analytics of the BI system in an organization's forecasting practices.

• Korean Journal of Agricultural Science
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• v.19 no.2
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• pp.129-135
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• 1992

Characteristics of ten glutinous maize hybrids developed at the Genetics and Breeding Lab. of Department of Agronomy, College of Agriculture, Chungnam National University were compared. Inbred lines used in the development of the ten hybrids were all originated from the Korean local maize lines which were collected in 1980s and they were developed by ear-to-row method. All the inbreds used had very unique plant characteristics such as plant height, ear height, ear length, ear diameter, 100 kernel weight and kernel color. The highest inbred in plant height was Jewon and the Jewon was also highest in ear height. While the ear of Jewon inbred was slender and slimmy, the ear of Dangjin inbred was rather short and promp. 100 kernel weight of the Bosung inbred was highest and the kernel weight of Chilbo was lightest. Kernel color of Jewon, Bosung and Danyang was white and the kernel color of Yunghee and Chilbo was purple. Dangjin had yellow kernel color. A total of 11 hybrids including one check hybrid developed by the Crop Experiment Station, ADR were included in performance trial. The hybrids which showed high grain yield were Dangjin/Bosung, Sosung/Dangjin and Dangjin/Chilbo. These hybrids were about 10% higher than the check in yield capacity. Each hybrid had also unique characteristics such as plant height, ear height and flowering date.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.