• Asia pacific journal of information systems
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• v.18 no.3
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.3
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• pp.147-175
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• 2011

The purpose of this study is to examine the effects of store choice criteria on customer satisfaction and store loyalty, and the moderating effects of customer emotions on the causal relationship between store choice criteria and customer satisfaction. In this regard, this study tries to identify the effects of store choice criteria on customer satisfaction and store loyalty in case of mass merchandisers, and to analyze the moderating effects of customer emotions on the causal relationship between store choice criteria and customer satisfaction. For this purpose, 300 customers, who have ever shopped at mass merchandisers, were surveyed and 246 valid responses were finally used for the data analysis. The results of this study are as follows. First, out of six store choice criteria, product factors, store reputation and physical environment turn out to have statistically significant effects on customer satisfaction. This result confirms those of the previous studies. On the other hand, store accessibility, subsidiary facilities and store atmosphere are not found to have statistically significant effects on customer satisfaction. This result is somewhat different from those of previous studies, and so further research on the subject needs to be carried out. Secondly, it turns out that customer satisfaction has a statistically significant effect on store loyalty, which is in line with the results of previous studies that perceived emotions affect customers' store attitudes which in turn influence their revisit intentions. Thirdly, as for the moderating effects of customer emotions on the relationship between store choice criteria and customer satisfaction, pleasure moderates the effects of store accessibility, subsidiary facilities and store atmosphere on customer satisfaction, arousal moderates the effects of product factors, subsidiary facilities and store reputation on customer satisfaction, and finally dominance moderates the effects of product factors and subsidiary facilities on customer satisfaction. These findings partially support the results of previous studies that customers' in-store emotional experiences such as feeling good or bad enhance their store loyalty.

• Journal of Food Hygiene and Safety
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• v.29 no.2
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• pp.158-163
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• 2014

In this study, two commercial PCR and ELISA test kits were examined for identification of eight animal species (beef, pork, chicken, duck, turkey, goat, lamb, and horse) from raw meat and meat products in Korea. The detection limit in RAW meat ELISA kit$^{(R)}$ on three types of meat samples blended with beef, pork and chicken, demonstrated that all meat species were differentiable down to 0.2%. RAW meat ELISA kit$^{(R)}$ on animal species resulted in differentiation rate of 94.5% for beef, 93.3% for pork, 90% for lamb, and 100% for chicken, duck, turkey, goat, and horse. In contrast, Powercheck Animal Species ID PCR kit$^{TM}$ resulted in 100% specificity at 0.05% limit of detection for all meat species. The detection limit of Cooked Meat ELISA kit$^{(R)}$ on mixed meat samples heat-treated with different temperatures and times, resulted in 0.1% for all heat-treated mixed meat except for chicken at 1.0%. Additionally, ELISA kit on sixty meat products resulted in specificity of 31.8% for ham, 13.6% for sausages, and 12.5% for ground processed products, and relatively low rate for more than 2 types of mixed meats. On the contrary, meat species differentiation using PCR kit showed higher percentage than that using ELISA kit$^{(R)}$: 50.0% for ham, 41.7% for sausages, and 28.6% for ground processed meat. Futhermore, PCR kit on 54 dried beef meats detected pork genes in 13 products whereas ELISA kit showed negative results for all products. Hence, the possibility of cross-contamination during manufacturing process was investigated, and it was found that identical tumblers, straining trays, cutters and dryers were used in both beef and pork jerky production line, suggesting the inclusion of pork genes in beef products due to cross-contamination. In this study, PCR and ELISA test kits were found to be excellent methods for meat species differentiation in raw meat and heat-processed mixed meat. However, lower differentiation rate demonstrated in case of meat processed products raised the possibility of inclusion of other species due to cross-contamination during manufacturing process.

• Journal of Oral Medicine and Pain
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• v.36 no.3
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• pp.147-160
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• 2011

Eugenol (4-allyl-2-methoxyphenol) is a natural phenolic constituent extensively used in dentistry as a component of zinc oxide eugenol cement and is applied to the mouth environment. Chios gum mastic (CGM) is a resinous exudate obtained from the stem and the main leaves of Pistacia lenticulus tree native to Mediterranean areas. This study was undertaken to investigate the synergistic apoptotic effect of co-treatment with a natural product, CGM and natural phenolic compound, eugenol on SCC25 human tongue squamous cell carcinoma cell line. To investigate whether the co-treatment with eugenol and CGM compared to each single treatment efficiently reduces the viability of SCC25 cells, MTT assay was conducted. Induction and augmentation of apoptosis were confirmed by Hoechst staining, TUNEL staining and DNA hypoploidy. Westen blot analysis and immunofluorescent staining were performed to study the alterations of the expression level and the translocation of apoptosis-related proteins in co-treatment. In this study, co-treatment of with eugenol and CGM on SCC25 cells showed several lines of apoptotic manifestation such as nuclear condensations, DNA fragmentation, the increase and decrease of Bax and Bcl-2, decrease of DNA content, the release of cytochrome c into cytosol, translocation of AIF and DFF40 (CAD) onto nuclei, and activation of caspase-3, caspase-6 caspase-7, caspase-9, PARP, Lamin A/C and DFF45 (ICAD) whereas each single treated SCC25 cells did not show or very slightly these patterns. Although the single treatment of 40 ${\mu}g$/ml CGM and 0.5 mM eugenol for 24 h did not induce apoptosis, the co-treatment of these reagents prominently induced apoptosis. Therefore our data provide the possibility that combination therapy with CGM and eugenol could be considered as a novel therapeutic strategy for human oral squamous cell carcinoma.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.4
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• pp.341-352
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• 2021

Acerola is an excellent ingredient because of its high natural vitamin C content, but it is difficult to stabilize and has hardly been studied as a cosmetic material. Therefore, this study developed a mixed liposome preparation for stabilizing acerola extract. As a safety test, the skin irritation test was evaluated by BCOP assay and HET-CAM assay. We evaluated the inhibition of tyrosinase activity, the whitening effect of melanin production, and the wrinkle effect of prochloragentype-I C-peptide production, and confirmed the possibility of functional cosmetics. In addition, a cream of liposomes containing acerola extract mixture was developed to evaluate the clinical studies of skin wrinkles and whitening. BCOP assay, HET-CAM assay and human skin primary irritation test results of liposomes containing acerola extract mixture showed no irritation and were safe from skin and eye. The result of tyrosinase activity by 75.8% at 1,000 ㎍/mL. As a result of the melanogenesis inhibition test, liposome with acerola extract showed the melanin content by 46.2% at 1,000 ㎍/mL that does not effect the viability of the B16F10 cell line. The result of collagen production test using ELISA kit, liposomes containing acerola extract mixture showed collagen synthesis ability by 152.1% at 1,000 ㎍/mL that does not affect the viability of the HS68 cell line. But it did not showed any inhibition of collagenase (MMP-1) activity at all concentrations in the MMP-1 activity inhibition test in the HS68 cell line. We performed clinical studies for the whitening and skin-wrinkle activity of cream containing acerola extract mixes liposome, was showed that the melanin contents and wrinkle was statistically significant reduction. These results suggest that liposomes containing acerola extract mixture have safe natural material, and skin wrinkle, whitening effects allowing their application in cosmetics as a natural product.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Korean Journal of Poultry Science
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• v.38 no.1
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• pp.59-69
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• 2011

This study was conducted to investigate the effects of dietary supplementation of CS682, a fermentation product of Actinomycetae(Nocardia sp. CS682), and its commercial product DSC682$^{(R)}$ on the performance, blood parameters, intestinal microflora, and immune response in laying hens. Hy-Line Brown$^{(R)}$ laying hens were housed in two bird cages. Feeding trial lasted 5 wk under 16.5 h:7.5 h(L:D) lighting regimen. In Exp.1, a total of 480 birds of 86 wk old were assigned to four dietary treatments: Control, Antibiotics (6 ppm avilamycin), CS682-0.1 (CS682 0.1%) and CS682-1.0 (CS682 1.0% supplementation). Each treatment was replicated five times with 24 birds (or 12 cages) per replication. In Exp. 2, a total of 1,000 birds of 26 wk old were assigned to five dietary treatments: Control, Antibiotics (6 ppm avilamycin), DCS682-0.05 (DCS682 0.05%), DCS682-0.1 (DCS682 0.1%), DCS682-0.2 (DCS682 0.2% supplementation). Each treatment was replicated five times with 40 birds (or 20 cages) per replication. In Exp. 1, there were no significant differences among treatments in egg production, egg weight, broken & soft egg production, feed intake, and feed conversion ratio. Also, there were no significant differences among treatments in eggshell thickness, eggshell color and Haugh unit. However, eggshell strength was significantly (p<0.05) greater in CS682 and Antibiotics treatments than Control, and egg yolk color was significantly (p<0.05) higher in CS682-1.0 than Control. In Exp. 2, feed intake was significantly (p<0.05) lower in DSC682-0.05 than Control. Lightness(L) of Hunter Lab color of eggshell of DCS and Antibiotics treatments was significantly (p<0.05) lower than Control. Egg yolk color of DCS 0.1 and 0.2 treatments was significantly (p<0.05) higher than Control. Haugh unit increased significantly (p<0.05) in Antibiotics and DCS682-0.1 treatments. The immunoglobulin levels of plasma (IgG and IgA) and eggyolk (IgY) were not significantly affected by treatments. Antibiotics and CS682 or DCS682 treatments significantly (p<0.05 or 0.01) influenced some of the erythrocytes and leukocytes parameters in blood. In Exp.1, mean corpuscular volume (MCV) decreased by CS682 treatments and mean corpuscular hemoglobin (MCH) was highest in Antibiotics treatments. In Exp.2, the level of monocyte (MO) decreased in DCS682-0.10 and 0.20 treatments. The cfu of C. perfringens and S. typhimurium in small intestinal content were highest in Control and lowest in Antibiotics in both experiments. In Exp. 2, DSC682-0.05 and -0.1 treatments were highest and Antibiotic treatment was lowest in Lactobacilli spp. The results of the present layer experiments indicated that supplementation of 0.1~0.2% CS682 or DCS682 may increase eggshell strength, color of eggshell and eggyolk, Haugh unit, and control harmful intestinal microbes.

• Journal of Distribution Research
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• v.15 no.4
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• pp.1-19
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• 2010

As having the movement of developing private brand (PB) goods, domestic big retailers are facing up with new problems. Thus, it is required studies of PB products, and how consumers recognize PB products as a consideration commodity set. Also, it is worthy in order that it gives us the important meaning on the marketing strategy with focusing on evaluating the differences between customers buying PB grocery goods with respect to demographic characteristics and purchasing behaviors. PB has some advantages for customers and retailers. However, according to AC Nielson's report (2005), Asian and emerging market has 1/5 sales relatively to Western countries. But we can assume that the emerging market has the most potential growth through this result. As a result from several other studies, it becomes necessary to not only increase the rate of selling composition of PB product temporarily, but also analyze the characteristics of customers using big retailers and segmenting customer groups to make PB product as a consideration commodity set for them. In addition, it is needed to have a variety of acts of marketing. From studies related to PB, there is a prejudice - cheap products have low quality - but, evaluation by customers who have used those products shows neutral stand, and there is a study representing that it is the most important to accumulate the belief between the retailers selling PB products and consumers using those for the accurate evaluation and intention on purchasing. Also, by the result from analyzing the characteristics of customers buying PB products, we could assume that higher income and higher education level, more preference on PB products. Especially, according to TNS's research, the primary targets of PB product are 30's who seeks value for money and planned spending habits, and 40's who have teenager children, and are interested in encouraging themselves. This paper used Probit model to analyze the characteristics of consumers. This model helps us to analyze with the variables representing the demographic characteristics of consumers (gender, age, educational level, occupation, income level, living area), and variables related to purchasing behavior (visiting frequency on big retailers, the average amount that they pay for goods in there, and check-up which brand made those goods). The method we used in this study is by man to man interview and survey on-line with the rate of 89% and 11% in Seoul and Gyunggi Province, respectively, for about one month from the beginning of February, 2008. As a result of this, under the assumption that people buy PB products more as long as they go shopping more, it was not meaningful for target groups which we pointed out as frequently visiting customers to be. Although, we have expected women buy more PB products than men do, gender doesn't mean anything for the result. And, it has inferred that married people buy more PB goods than singles do. It was also meaningless with variables related to occupation. Because housewives are often exposed to any kind of supermarket than workers are, we could not get any relatives. Moreover, we couldn't proof that younger generation prefer big retailers more than older people who 50~60's. Education levels doesn't affect on the purchase of PB product as well. Related to living area, the result is statistically not similar as we expected whether living in Seoul or not. It shows there is no relationship with the preference on retail brands and PB products, and it is similar with the study researched by TNS(2008) that customers tend to buy PB product impulsively no matter which brand it is and where they are even though their shopping place is the big market where customers are often using. Variables on which we had meaningful results are income level and living place. That is, customers who have 3,000,000~6,000,000 WON every month on average are more willing to buy PB products than other customers whose income is over 6,000,000 WON, and residents not living in Seoul prefer PB goods than those who are living in Seoul. To explain more about what we got, if there is only one condition about customer's visiting frequency on big retails, we could come up with this result that more exposed to PB products, more purchasing frequency. Consequently, it brings the important insight that large retailers have to prepare something to make customers visit them often to increase selling rate of PB products. To demonstrate the result of analyzing more, what is more efficient variables are demographically including marital status, income level, and residential area to buy items that affect the PB products and could include the frequency of visiting large markets by the purchase habits. Specifically, then, married couples rather than singles, middle-income customers than high-income customers, and local residents not living in Seoul than customers in Seoul are more likely to purchase PB goods. In addition, as long as a customer visits two times more, then the purchasing rate of PB products is to increase over 5.3%. Therefore, it seems that retailers are better to make a shopping place as fun and comfortable places. With overwhelming the idea that PB products are just cheap, one-time purchase goods, it is needed to increase the loyalty on those goods like NB products, try to make PB products as a consideration products set, and occur to sustainable sales. Especially, as suggested by this paper, it seems like it strongly needs to identify the characteristics of customers who prefer PB, to segment those customers, and to select the main target, and to do positioning with well-planned marketing strategies. Then, it is able to give us a meaningful point on marketing strategy by developing the field of PB study, identifying the difference of life style and shopping habits of customers.

• Journal of the Korean Geotechnical Society
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• v.15 no.4
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• pp.175-184
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• 1999

Several major land reclamation projects such as the Inchon International Airport construction, Songdo New City construction, LNG Tank and LPG storage construction are underway along the coastal line of Inchon in Korea. This study was carried out to investigate the feasible use of waste lime in the land reclamation projects. Waste lime (hydrated lime) used in this study is produced as a by-product in the manufacturing process of $Na_2CO_3$ from local chemical factory in Inchon. This study presents the characteristics of bearing capacity and settlement on the ground formed by layers of waste lime and dredged soil. From the laboratory and in-situ plate load test, the ultimate bearing capacity by in-situ test was 1.25~1.37 times higher than that of the theoretical ultimate bearing capacity. Based on the settlement analysis by Magset- II, the total settlement of layered ground steadly increased up to the ratio of waste lime depth 0.2 and therefore rapidly increased with the increase of waste lime depth. The results of the present study indicate that the ratio of waste lime depth for reclamation work is about 0.2.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.6 s.360
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• pp.8-18
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• 2007

In this paper, a 4bit cell way structure of PoRAM and the sensing method to drive this structure are researched. PoRAM has a different operation from existing SRAM and DRAM. The operation is that when certain voltage is applied between top electrode and bottom electrode of PoRAM device we can classify the cell state by measuring cell current which is made by changing resistance of the cell. In the decoder selected by new-addressing method in the cell array, the row decoder is selected "High" and the column decoder is selected "Low" then certain current will flow to the bit-line. Because this current is detect, in order to make large enough current, the voltage sense amplifier is used. In this case, usually, 1-stage differential amplifier using current mirror is used. Furthermore, the detected value at the cell is current, so a diode connected NMOSFET, that is, a device resistor is used at the input port of the differential amplifier to converter current into voltage. Using this differential amplifier, we can classify the cell states, erase mode is "Low" and write mode is "High", by comparing the input value, Vin, that is a product of current value multiplied by resistor value with a reference voltage, Vref.