• 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.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.7
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• pp.876-885
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• 2017

This study aimed to identify the characteristics of Home Meal Replacement (HMR) product purchases and the need for HMR product development for Hong Kong consumers in order to suggest market segmentation strategies according to consumers' dietary lifestyle. For this, an online survey was conducted on a panel of 521 Hong Kong consumers with HMR purchase experience registered at a specialized organization. Data analysis was performed using SPSS (ver. 23.0). HMR purchase characteristics of Hong Kong consumers according to dietary lifestyle showed significant differences in all items, including 'number of purchases', 'purchase location', 'cost of single purchase', and 'reason for purchase'. According to dietary lifestyle, participants were divided into three clusters: 'High interest', 'normal interest', and 'low interest'. In the case of 'high interest in dietary life group', 'low-sodium food' was the most common, followed by 'heating food', 'low sugar food', and 'low calorie food'. In the case of 'moderate interest in dietary life group', 'low-sodium food' was the most common, followed by 'low sugar food', 'low calorie food', and 'nutritious meal'. In the case of 'low interest in dietary life group', 'low sugar food' was the most common, followed by 'low-sodium food', 'various new menu', and 'easy-to-carry dehydrated food'. For the 'high interest' group, the highest proportion of consumers were male in between the ages of 20 to 29, married, and worked in an office job. The 'high interest' consumers also showed a tendency to pay '15,000 to 20,000 KRW' per single purchase. The 'normal interest' group consisted of an even proportion of male and female consumers, with the most common age range being from 30 to 39 years, and most were married. These consumers preferred to spend 'less than 10,000 KRW' or '10,000 KRW to 15,000 KRW' per single purchase, which is in the lower price range for HMR purchases. The 'low interest in dietary life group' had more females gender-wise, were unmarried, and worked in an office job, For a single purchase, the 'low interest' group chose to pay less than 10,000 KRW, which is relatively lower than the other two clusters. The results of this study can be used as baseline data for building marketing strategies for HMR product development. It can also provide basic data and directions for new HMR export products that reflect consumer needs in order to create a market segmentation strategy for industrial applications.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Journal of Preventive Medicine and Public Health
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• v.30 no.4 s.59
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• pp.669-685
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• 1997

Previous studies, reporting the inverse relationship between osteoarthritis and osteoporosis suggest the existence of possible pathophysiologic mechanisms between them. To examinine the hypothesis that 'bone mineral densities of women with osteoarthritis are significantly higher than that of women without osteoarthritis in Korea', subjects from the health and nutritional examination survey in Kuri city were sampled. Samples were selected through multi-stage sampling frame using established clusters in Kuri city. From August 18 to September 10,1997, the survey was conducted. Among the. total number of selected sample population (1,656 people), response .ate was 52.4 percent (348 men and 519 women). 420 women who took BMD measurement, radiologic exam, and anthropometric exam were selected for the analysis. The analytic results are as follows. 1. General characteristics: Mean BMD was $0.493g/cm^2$, mean age was 43.0, mean BMI was $23.9kg/m^2$. The number of women who experienced menopause was 106, hysterectomy was 19. There were 0 case of osteoarthritis of hip, 64 cases of osteoarthritis of knee, and 2 cases of osteoarthritis of hand. 2. Univariate analysis results: Mean BMD of women with the osteoarthritis of knee was significantly lower than that of women without the osteoarthritis of knee(0.4269 vs. $0.5057g/cm^2$). But, there were too few cases of osteoarthritis of hip and hand, so comparative studies of BMD in osteoarthritis of hip and hand could not be conducted. There were significant differences of BMD among pre-menopause group(0.5204), post-menopause group(0.4206), and hysterectomy group(0.4881). Additionally, there were significant differences of BMD among diabetes group(0.4297), impaired glucose tolerance group(0.4874), and normal group(0.5057). Furthermore, age, parity, BMI, bioimpedance were significantly related with BMD. 3. Multivariate analysis results: To examinine the relationship between osteoarthritis and BMD while controlling the other variables' effects which were significant in the univariate analyses, multiple linear regression analysis was done. But, it was found that osteoarthritis of knee was not a significant variable to BMD anymore. While age and menopause had significant negative relationship with BMD. Diabetes, parity, BMI, and bioimpedance did not have significant relationships with BMD. After stratification of subjects according to menopause, multiple linear regression analyses were done to each strata. Consequently, age in post-menopause group, age and osteoarthritis of knee in hysterectomy group showed significant negative relationship with BMD. The results did not support the many results of other previous studies done with white men and women. further studies of biological plausibility to Korean women are recommended. Also it is suggested that longitudinal study to verify the relationship between osteoarthritis and BMD will be valuable.

• The Korean Journal of Mycology
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• v.38 no.2
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• pp.112-119
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• 2010

Pleurotus spp. have been used for edible and medicinal purposes in Asian countries for a long time. The fruiting bodies of the Pleurotus ostreatus, Pleurotus citrinopileatus and Pleurotus salmoneostramineus contained many physiologically beneficial substances for human health. Therefore, it is necessary to study the genetic diversity of Pleurotus mushroom cultivars commercially cultivated in Korea. Eleven strains of Pleurotus spp. were collected from different geographical regions in South-East Asia and ITS regions of rDNA and RAPD of genomic DNA were analyzed. The size of the ITS1 and ITS2 regions of rDNA from the different strains varied from 167 to 254 bp and 156 to 213 bp, respectively. The sequence of ITS1 was more variable than that of ITS2, and the 5.8S sequences were identical. A phylogenetic tree based on the ITS region sequences indicated that selected strains could be classified into 4 clusters. Eleven Pleurotus species were also analyzed by RAPD with 20 arbitrary primers. Ten of these primers were efficiently amplified the genomic DNA. The number of amplified bands varied with the primers and strains, with polymorphic fragments in the range from 0.1 to 2.0kb. The results revealed that genetic diversity of selected strains of P. ostreatus, P. citrinopileatus and P. salmoneostramineus is low.

• Restorative Dentistry and Endodontics
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• v.32 no.1
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• pp.47-60
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• 2007

The purpose of this study is to compare and to evaluate the effect of pH and lactic acid concentration on the progression of artificial root caries lesion using polarizing microscope, and to evaluate the morphological changes of hydroxyapatite crystals of the demineralized area and to investigate the process of demineralization using scanning electron microscope. Artificial root caries lesion was created by dividing specimens into 3 pH groups (pH 4.3, 5.0, 5.5), and each pH group was divided into 3 lactic acid concentration groups (25 mM, 50 mM, 100 mM). Each group was immersed in acid buffer solution for 5 days and examined. The results were as follows : 1. Under polarized microscope, the depth of lesion was more effected by the lactic acid concentration rather than the pH. 2. Under scanning electron microscope, dissolution of hydroxyapatite crystals were increased as the lactic acid concentration increased and the pH decreased. 3. Demineralized hydroxyapatite crystals showed peripheral dissolution and decreased size and number within cluster of hydroxyapatite crystals and widening of intercluster and intercrystal spaces as the pH decreased and the lactic acid concentration increased. 4. Under scanning electron microscope evaluation of the surface zone, clusters of hydroxyapatite crystals were dissolved, and dissolution and reattachment of crystals on the surface of collagen fibrils were observed as the lactic acid concentration increased. 5. Under scanning electron microscope, demineralizatlon of dentin occurred not only independently but also with remineralization simultaneously. In conclusion, the study showed that pH and lactic acid concentration influenced the rate of progression of the lesion in artificial root caries. Demineralization process was progressed from the surface of the cluster of hydroxyapatite crystals and the morphology of hydroxyapatite crystals changed from round or elliptical shape into irregular shape as time elapsed.

• Restorative Dentistry and Endodontics
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• v.32 no.2
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• pp.130-137
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• 2007

This in vitro study examined the effect of surface defects on cutting blades on the extent of the cyclic fatigue fracture of HEROShaper Ni-Ti rotary files using fractographic analysis of the fractured surfaces. A total of 45 HEROShaper (MicroMega) Ni-Ti rotary flies with a #30/.04 taper were divided into three groups of 15 each. Group 1 contained new HEROShapers without any surface defects. Group 2 contained HEROShapers with manufacturing defects such as metal rollover and machining marks. Croup 3 contained HEROShapers that had been clinically used for the canal preparation of 4-6 molars A fatigue-testing device was designed to allow cyclic tension and compressive stress on the tip of the instrument whilst maintaining similar conditions to those experienced in a clinic. The level of fatigue fracture time was measured using a computer connected the system. Statistical analysis was performed using a Tukey's test. Scanning electron microscopy (SEM) was used for fractographic analysis of the fractured surfaces. The fatigue fracture time between groups 1 and 2, and between groups 1 and 3 was significantly different (p<0.05) but there was no significant difference between groups 2 and 3 (p>0.05). A low magnification SEM views show brittle fracture as the main initial failure mode At higher magnification, the brittle fracture region showed clusters of fatigue striations and a large number of secondary cracks. These fractures typically led to a central region of catastrophic ductile failure. Qualitatively, the ductile fracture region was characterized by the formation of microvoids and dimpling. The fractured surfaces of the HEROShapers in groups 2 and 3 were always associated with pre-existing surface defects. Typically, the fractured surface in the brittle fracture region showed evidence of cleavage (transgranular) facets across the grains, as well as intergranular facets along the grain boundaries. These results show that surface defects on cutting blades of Ni-Ti rotary files might be the preferred sites for the origin of fatigue fracture under experimental conditions. Furthermore this work demonstrates the utility of fractography in evaluating the failure of Ni-Ti rotary flies.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.12
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• pp.1896-1904
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• 2020

Objective: Estimating the genetic diversity and structures, both within and among chicken breeds, is critical for the identification and conservation of valuable genetic resources. In chickens, microsatellite (MS) marker polymorphisms have previously been widely used to evaluate these distinctions. Our objective was to analyze the genetic diversity and relationships among 22 chicken breeds in Asia based on allelic frequencies. Methods: We used 469 genomic DNA samples from 22 chicken breeds from eight Asian countries (South Korea, KNG, KNB, KNR, KNW, KNY, KNO; Laos, LYO, LCH, LBB, LOU; Indonesia, INK, INS, ING; Vietnam, VTN, VNH; Mongolia, MGN; Kyrgyzstan, KGPS; Nepal, NPS; Sri Lanka, SBC) and three imported breeds (RIR, Rhode Island Red; WLG, White Leghorn; CON, Cornish). Their genetic diversity and phylogenetic relationships were analyzed using 20 MS markers. Results: In total, 193 alleles were observed across all 20 MS markers, and the number of alleles ranged from 3 (MCW0103) to 20 (LEI0192) with a mean of 9.7 overall. The NPS breed had the highest expected heterozygosity (H_exp, 0.718±0.027) and polymorphism information content (PIC, 0.663±0.030). Additionally, the observed heterozygosity (H_obs) was highest in LCH (0.690±0.039), whereas WLG showed the lowest H_exp (0.372±0.055), H_obs (0.384±0.019), and PIC (0.325±0.049). Nei's DA genetic distance was the closest between VTN and VNH (0.086), and farthest between KNG and MGN (0.503). Principal coordinate analysis showed similar results to the phylogenetic analysis, and three axes explained 56.2% of the variance (axis 1, 19.17%; 2, 18.92%; 3, 18.11%). STRUCTURE analysis revealed that the 22 chicken breeds should be divided into 20 clusters, based on the highest ΔK value (46.92). Conclusion: This study provides a basis for future genetic variation studies and the development of conservation strategies for 22 chicken breeds in Asia.

• Journal of Animal Science and Technology
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• v.55 no.3
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• pp.185-194
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• 2013

Microsatellite markers have been a useful genetic tool in determining diversity, relationships and individual discrimination studies of livestock. The level of genetic diversity, relationships among two Korean indigenous chicken brand populations (Woorimatdag: WR, Hanhyup3: HH) as well as two pure populations (White Leghorn: WL, Rhode Island Red: RIR) were analyzed, based on 26 MS markers. A total of 191 distinct alleles were observed across the four chicken populations, and 47 (24.6%) of these alleles were unique to only one population. The mean $H_{Exp}$ and PIC were estimated as 0.667 and 0.630. Nei's $D_A$ genetic distance and factorial correspondence analysis (FCA) showed that the four populations represented four distinct groups. However, the genetic distance between each Korean indigenous chicken brand (WR, HH) and the pure population (WL, RIR) were threefold that among the WR and HH. For the STRUCTURE analyses, the most appropriate number of clusters for modeling the data was determined to be three. The expected probabilities of identity among genotypes of random individuals (PI) were calculated as $1.17{\times}10^{-49}$ (All 26 markers) and $1.14{\times}10^{-15}$, $7.33{\times}10^{-20}$ (9, 12 with the highest PI value, respectively). The results indicated that the brand chicken breed traceability system employing the own highest PI value 9 to 12 markers, and might be applicable to individual identification of Korean indigenous chicken brand.

• Horticultural Science & Technology
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• v.28 no.5
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• pp.836-844
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• 2010

This study was carried out to investigate plant characteristics and nutritional components of the genetically modified (GM) Chinese cabbage and its control line grown in the central and northern parts of Korea in order to establish the evaluating protocol and standard assessment. The GM and non-GM Chinese cabbage was planted with normal and concentrated density at two locations in spring and fall of 2008 and 2009. From the statistic analysis on plant characteristics and nutritional components, there were not many significant differences between GM and non-GM Chinese cabbage. Only few differences in the plant characteristics were found between the dense and normal planting. In the dense planting, there was no significant difference between GM and non-GM Chinese cabbages except for three out of 18 plant traits, such as leaf shape, hairiness and midrib length. On the other hand, nine plant traits including leaf length, leaf width, leaf color, leaf shape, fresh weigh of ground part, number of leaf, midrib length, midrib width and root diameter were slightly different between GM and non-GM Chinese cabbage in the normal planting. In case of leaf length, midrib length, midrib width and fresh weigh of ground part, there were significantly differences not only between two lines, but also between two locations. From nutritional component analysis, only five fatty acids were identified in the Chinese cabbage: palmitic acid, oleic acid, stearic acid, linoleic acid and linolenic acid. Except linoleic acid, four fatty acids in one gram of dried sample from GM line were little higher than those from non-GM line. However, there were no significant differences in total contents of fatty acids not only between GM and non-GM Chinese cabbage line, but also between northern and central cultivating areas in the normal and dense planting. According to the composition of inorganic elements identified in the samples from both lines, there were six macro-elements, such as N, P, Ca, K, Mg and Na, and four micro-elements, Cu, Fe, Mn and Zn. Based on the result from PCA analysis, specific clusters were not found between GM Chinese cabbage and the control line, but found between two regions.