• Korean Journal of Environmental Agriculture
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• v.30 no.3
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• pp.295-303
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• 2011

BACKGROUND: Anaerobic digestion process is recently adapted technology for treatment of organic waste such as animal manure because the energy embedded in the waste can be recovered from the waste while the organic waste were digested. Ever increased demand for consumption of meat resulted in the excessive use of antimicrobials to the livestocks for more food production. Most antimicrobials administered to animals are excreted through urine and feces, which might highly affect the biological treatment processes of the animal manure. The aim of this study was to investigate the effects of antimicrobials on the efficiency of anaerobic digestion process and to clarify the interactions between antimicrobials and anaerobes. METHODS AND RESULTS: The experiment was consisted of two parts 1) batch test to investigate the effects of individual antibiotic compounds on production of methane and VFAs(volatile fatty acids), and removal efficiency of organic matter, and 2) the continuous reactor test to elucidate the effects of mixed antimicrobials on the whole anaerobic digestion process. The batch test showed no inhibitions in the rate of methane and VFAs production, and the rate of organic removal were observed with treatment at 1~10 mg/L of antimicrobials while temporary inhibition was observed at 50 mg/L treatment. In contrast, treatment of 100 mg/L antimicrobials resulted in continuous decreased in the rate of methane production and organic removal efficiency. The continuous reactor test conduced to see the influence of the mixed antimicrobials showed only small declines in the methane production and organic matter removal when 1~10 mg/L of combined antimicrobials were applied but this was not significant. In contrast, with the treatment of 50 mg/L of combined antimicrobials, the rate of organic removal efficiency in effluent decreased by 2~15% and the rate of biogas production decreased by 30%. CONCLUSION(s): The antimicrobials remained in the animal manure might not be removed during the anaerobic digestion process and hence, is likely to be released to the natural ecosystem. Therefore, the efforts to decline the usage of antimicrobials for animal farming would be highly recommended.

• Journal of Communication Design
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• v.55
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• pp.240-249
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• 2016

This study focused on cases about user experience using digital media as a marketing. The recent convergence of various types of media is resulting in new types of content. In a situation where approaching consumers through digital and virtual means is no longer an alternative or an option but a necessity, customers must be influenced and stimulated using various types of digital media. Because modern consumers prefer to participate actively rather than to be passively exposed to information, there is a need to maximize and optimize the consumer's experience using digital media. In this research, consumer experiences that utilized digital media were examined, and these case studies were analyzed from an experiential marketing perspective. How the 5 different types of Experiential Marketing proposed by Bernd Schmitt and Digital medias were combined in the digital marketing campaigns was examined. The case studies analyzed in this research were chosen out of widely popular digital marketing campaigns ran by beauty brands that used various experimental marketing types, such as 'Make-up Genius' of L'Or?al, 'Google Glass Tutorials' of Yves Saint Laurent and 'Digital Runway Bar' of The Burberry Beauty Box. This study classified that case samples into paid media, earned media and owned media based on sense, feel, think, act and relate that are the strategic experiential modules of Bernd Schmitt. This study could be confirmed various customer experience as a sense, feel, think, act and relate through that cases using digital media technology and marketing element of digital media. Through the process of examining which digital media types each marketing campaign utilized and how these types of digital marketing were combined, this research is significant in that it helps for the understanding of the current state of digital marketing and in that it can serve as the foundation for future research of efficient digital marketing.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.358-383
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• 2015

The concept of 'carbon footprint' has been developed as a means of quantifying the specific emissions of the greenhouse gases (GHGs) that cause global warming. Although there are still neither clear definitions of the term nor rules for units or the scope of its estimation, it is broadly accepted that the carbon footprint is the total amount of GHGs, expressed as $CO_2$ equivalents, emitted into the atmosphere directly or indirectly at all processes of the production by an individual or organization. According to the ISO/TS 14067, the carbon footprint of a product is calculated by multiplying the units of activity of processes that emit GHGs by emission factor of the processes, and by summing them up. Based on this, 'carbon labelling' system has been implemented in various ways over the world to provide consumers the opportunities of comparison and choice, and to encourage voluntary activities of producers to reduce GHG emissions. In the agricultural sector, as a judgment basis to help purchaser with ethical consumption, 'low-carbon agricultural and livestock products certification' system is expected to have more utilization value. In this process, the 'cradle to gate' approach (which excludes stages for usage and disposal) is mainly used to set the boundaries of the life cycle assessment for agricultural products. The estimation of carbon footprint for the entire agricultural and forestry sector should take both removals and emissions into account in the "National Greenhouse Gas Inventory Report". The carbon accumulation in the biomass of perennial trees in cropland should be considered also to reduce the total GHG emissions. In order to accomplish this, tower-based flux measurements can be used, which provide a direct quantification of $CO_2$ exchange during the entire life cycle. Carbon footprint information can be combined with other indicators to develop more holistic assessment indicators for sustainable agricultural and forestry ecosystems.

• Journal of the Korean Society of Costume
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• v.32
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• pp.293-312
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• 1997

Deconstructionism is a philosophical stream in the latter half of 20'th century which goes against western metaphysics and tries to deconstruct the dualism e.g. eastern/west-ern man/woman. Its main concepts are 'indi-vidual' 'other' 'difference' 'restoration of the repressed' 'decentralization' 'Today it shows strong influences in literature art, and other social fields. This study investigated inner meanings and exterior forms represented in clothing on the base of Jacques Derrida's theory in order to re-search modes of deconstruction in is. And it compared clothing with architecture among other genres of art in order to discover similarities between through and modes of art in a certain period. For illuminating concept of deconstruction I referred to the literatures of preceding studies and for deconstruction's characteristics in both clothing and architec-ture I referred work's collection book $\ulcorner$collec-tions$\lrcorner$ and other related books dealing from 1960's to this point. As a rsult there are four modes of decons-truction in both clothing and architecture as follows; 1) Differenance which is a concept of the dif-ference in time and space as being trace. 2) In termeaning of meanings which is not present in reality but re-interpreted a new in the future. 3) Interxtuality in which a texte is not alone but with others 4) Dis.De phenomenon in which distortion and fragmentation forms occur as the result of the denial of perfection and reson. There are characteristics of modes of de-construction in clothing as follows; 1) Differance; R.Gigli, P. Rabanne. G.Bersace, V.Westwood are representatives of the cloth-ing which is combined with the past the pres-ent and the future or is re-viewed as the clothing of the past in the present point of view. J. Watanabe R. Dawakubo I miyake are representatives of the clothing which is out-date but re-viewed in the sense of recollec-tion and re-usage. 2) Intermeaning of meanings: R. kawakubo I, Miyake Y,Yamamoto are representatives of the clothing which is incomplete but re-interpreted in the future and appears to be new-fashioned according to ways of bnding wearing throwing on and tying J.C. Castel-bajac K.Hamnett S.Sprouse are representa-tives of the clothing which is made up of ab -stract forms scribbling or symbolic letters which appears to be different according to view-point of observers. 3) Intertextuality ;J.P.Gaultier K.Hamnett, Comme des Gar ons are representatives of intertextuality of gender which avoids the 여-ality of man/woman J.P Gaultier G,Versace J. galliano are representatives of the intertex-tuality of time place and occasion which mixes temporality extensity and purposiveness. J.P Gaultier G,Versace are representatives of the intertextuality of coordination which combines items different in image purpose and use. P.Rabanne A,Courr ges R,Gernreic I,Miyake are representatives of the intertextuality of mat-ter which uses heterogeneous matter different from cloth. 4) Dis.De-phenomenon: R, Kawakubo I.Mi-yake J.P.Gaultier are representatives of the de-composition which discloses distortion and exag-geration of form through destructing the estab-lished way of construction J.Galliano R.Kawa-kubo Devota Y Lomba arte representatives of the decentring which restores the repressed and the alienated on the one hane and shows front-centrality on the other. Comme des Gar ones is representative of the discontinuity because of which right and left up and down are not in har-mony with one another. J,Galliano J.P,Gaultier T,Mugler are representatives of the disruption by way of which one makes one's body exposed through intentional slashes or holes. As a consequence deconstructionism enabled us to investigate similarities between through of deconstruction and modes of art interms of diffrance Intermeaning of meanings intertextuality and Dis De-phenomenon. And we found that deconstruction was a phase of development in that it as a all-comprising and multiple concept tries to pursue the new through deconstruction.

• Journal of Animal Science and Technology
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• v.45 no.5
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• pp.875-884
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• 2003

Operational parameters for struvite crystallization, as a process to recover nitrogen and phosphorus resources from animal wastewater, were studied in this research. Crystallization distinctive of NH$_4$-N and PO$_4$$^{3-}$ in accordance to chemical sources, influent pH, aeration and stirring was examined using 2L of working volume of struvite reactor. Also, to find an effective treatment process combining with electrolysis method, removal characteristics of NH$_4$-N and PO$_4$$^{3-}$ in 6 different processes was tested. As chemical sources for the derivation of struvite formation, MgSO$_4$ and MgCl$_2$ were superior to CaCO$_3$ and CaCl$_2$. From experiment which was conducted to know the effects of aeration and stirring on struvite formation, it was revealed that aeration stimulated the crystallization reaction by inducing faster pH increase. While 90% of P removal was achieved within 1 hour under aeration, 14 hours was consumed under stirring condition. Struvite formation under aeration was affected by influent pH. No crystallization was observed at pH 5 level, but active crystallization reaction was induced over pH 6.0. 95% of P removal by struvite formation at pH 6, 7 and 9 was achieved within 3h, 2h and 10 min., respectively. However, over pH 10, operational problem due to excessive foam formation occurred, and blunting of crystallization reaction was observed at pH 11. When consider the pH range of animal wastewater, pH 7 to 9, efficient struvite formation could be achieved by simple aeration, without any chemical usage for pH adjustment. Among tested processes, the treatment process which electrolyzing the supernatant from struvite reactor, providing air to both reactors, showed best pollutant removal efficiencies. In this combined process, the removal efficiencies of NH$_4$-N and PO$_4$$^{3-}$ was 86% and 98%, respectively, and 92.4% of color removal was obtained.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.10
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• pp.1481-1486
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• 2010

In this study we investigated the antioxidant activities and quality characteristics of Halocynthia aurantium and Halocynthia roretzi. The pH of H. aurantium was higher than that of H. roretzi. The volatile basic nitrogens of H. roretzi and H. aurantium were 22.41 mg% and 16.80 mg%, respectively. Lightness and yellowness of H. roretzi were higher than those of H. aurantium, but redness of H. aurantium was higher. The results of sensory evaluation showed that the H. aurantium was better for color, odor, taste and acceptability. Total combined amino acid contents of H. roretzi and H. aurantium were $36368.23\;{\mu}mol/g$ and $36500.12\;{\mu}mol/g$, respectively. Our results showed that H. roretzi had relatively higher contents of Asp, Glu, Gly, DPPH radical scavenging activity, ABTS radical scavenging activity and reducing power. Also total phenol content of H. roretzi was higher than that of H. aurantium. The organoleptic properties of the H. aurantium were superior but the antioxidant activities were relatively lower than those of H. aurantium. For commercial usage, additional study would be helpful in the two ascidians to recommend.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.255-264
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• 2019

In this study, we conducted the hot box tests to compare the changes in thermal insulation for the four types of multi-layer thermal screens by the used period after collecting them from the greenhouses in the field when they were replaced at the end of their usage. The main materials for these four types of multi-layer thermal screens were matt georgette, non-woven fabrics, polyethylene (PE) foam, chemical cotton, etc. These materials were differently combined for each multi-layer thermal screen. We built specimens ($70{\times}70cm$) for each of these multi-layer thermal screens and measured the temperature descending rate, heat transmission coefficient, and thermal resistance for each specimen through the hot box tests. With regard to the material combinations of multi-layer thermal screens, thermal insulation can be increased by applying a multi-layered PE foam. However, it is considered that the multi-layered PE foam significantly less contributes to heat-retaining than chemical wool that forms an air-insulating layer inside multi-layer thermal screens. For the suitable heat-retaining performance of multi-layer thermal screens, basically, materials with the function of forming an air-insulating layer such as chemical cotton should be contained in multi-layer thermal screens. The temperature descending rate, heat transmission coefficient, and thermal resistance of multi-layer thermal screens were appropriately measured through the hot box tests designed in this study. However, in this study, we took into consideration only the four kinds of multi-layer thermal screens due to difficulties in collecting used multi-layer thermal screens. This is the results obtained with relatively few examples and it is the limit of this study. In the future, more cases should be investigated and supplemented through related research.

• Journal of the Korean Recycled Construction Resources Institute
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• v.6 no.4
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• pp.297-303
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• 2018

With the changing trend of the building construction to high rising and large scaling, the underground structure has been increased, and its usage also increased and variety. Hence, to protect the underground structure against underground water, various water proofing methods has been developed. Among the many water proofing methods, the combined water proofing method using both asphalt seal and sheet has been widely used to secure the sufficient performance and decrease the construction failure. However, during the summer period of extremely high temperature conditions, the asphalt sealing materials were separated and leaked into the structure. Therefore, the aim of the research is to provide the quality standard of asphalt sealing material based on the various temperature changes depending on seasons. According to the experimental results, the temperature of the sealing materials applied on the slab was increased up to $54^{\circ}C$ which was $3^{\circ}C$ higher than the structure temperature of $51^{\circ}C$. Based on the melting test for asphalt sealing materials applied on the outside wall of the structure, in the case of water-dispersing typed materials showed significant melting down due to its slow evaporation and low viscosity. Furthermore, from the accelerated test conducted indoor conditions, a solvent-type and water-dispersing typed materials showed significant melting down due to their low viscosity and melting point in ambient conditions. Based on these results, viscosity and melting point are found as the important factors on asphalt sealing materials' quality, and it is necessary to designate the quantitative level of the viscosity and melting point for quality control.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.