• Economic and Environmental Geology
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• v.44 no.4
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• pp.273-288
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• 2011

Chon-Ashuu copper mining claim area is located, in terms of the geotectonic setting, in the northern part of the suture line which is bounded with the marginal part of Issik-kul micro-continent on the southern part of North Tien-Shan terrane. The geological blocks of Chon-Ashuu districts belong to the southern tip of Kazakhstan orocline. The rock formation of this area are composed of the continental crust or/and arc collage and the paleo-continental fragments-accretionary wedge complex of pre-Altaid orogenic materials. ASI(Alumina Saturation Index) of Paleozoic plutonic rocks in Chon-Ashuu area belong to the peraluminous and metaluminous rocks which were generated from fractional crystallization of Island and volcanic arc crusts in syn-post collisional plate. The geology of the ChonAshuu area consists of upper Proterozoic and Paleozoic rock formations. According to Harker variation diagrams for Chon-Ashuu arenaceous sedimentary rocks, the silty sandstone of Chon-Ashuu area showing the mineralogical immaturity were derived from Island arc or the marginal environments of active continent in Cambro-Carboniferous period. Numerous intrusive rocks of Chon-Ashuu area are distributed along north east trending tectonic structures and are bounded on four sides by the conjugate pattern. The most common type of the plutonic rocks are granodiorite and monzodiorite. According to the molecular normative An-Ab-Or composition (Barker, 1979), the plutonic rocks in Chon-Ashuu area are classified into tonalite - trondhjemite - granodiorite (TTG) series which are an aggregation of rocks which is the country rock of copper mineralization, that are formed by melting of hydrous mafic crust at high pressure.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.41 no.4
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• pp.391-400
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• 2015

In the present study, 50% ethanol extract, the ethyl acetate and aglycone fraction were prepared from mate (Ilex paraguariensis) and their antioxidative ability was evaluated. The yields of extract and fractions were 32.0, 4.48 and 0.82% per dried powder, respectively. Free radical scavenging activities were performed by 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay and total antioxidant capacity was estimated using luminol-dependent chemiluminescence assay. Free radical scavenging activities ($FSC_{50}$) of 50 % ethanol extract, ethyl acetate fraction and aglycone fraction were 8.83, 5.84 and $6.05{\mu}g/mL$, respectively. Their total antioxidant capacities ($OSC_{50}$) were similar to that of L-ascorbic acid ($1.72{\mu}g/mL$), known as a prominent water soluble antioxidant, in all extracts and 50% ethanol extract ($1.03{\mu}g/mL$) was the most effective. The cellular protective effects on the $^1O_2$-induced cellular damage of erythrocytes were evaluated and the results showed that all extracts were significantly higher than (+)-${\alpha}$-tocopherol at $10{\mu}g/mL$. Especially, the ${\tau}_{50}$ value of aglycone fraction was 5 times higher than (+)-${\alpha}$-tocopherol at $10{\mu}g/mL$ and $50{\mu}g/mL$. The inhibitory effects of the ethyl acetate and aglycone fractions on tyrosinase were similar to arbutin, known as the whitening agent in cosmetics. These results suggest that the extracts of mate have the applicability as antioxidant and anti-aging cosmeceutical ingredients.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.45 no.2
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• pp.161-173
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• 2019

In this study, the antioxidative and inhibitory activity of tyrosinase and collagenase for the solvent extract and silica column fractions of Artocarpus nitidus were evaluated. The activities were quantified using the 4 parameter logistic. LC/MS analysis showed that the major component of the fractions was polyphenol and the total polyphenol content of the extract was $48.1{\pm}2.6mg\;GAE/g$. The radical scavenging activities ($SC_{50}$) for 1,1-diphenyl-2-picrylhydrazyl of the extract, fraction-1 and fraction-2 were 16.7, 42.0 and $10.1{\mu}g/mL$, respectively. The value for fraction-2 was the closest to ascorbic acid ($1.5{\mu}g/mL$). The tyrosinase inhibitory activity of the extracts and the fractions showed $IC_{50}$ of 64.9, 0.9 and $1.2{\mu}g/mL$, respectively, and overall activity was higher than that of kojic acid ($7.4{\mu}g/mL$) and arbutin ($119.0{\mu}g/mL$). In the experiment by zebrafish embryo, the whitening activity of fraction-2 (27.5%) was higher than that of kojic acid (18.6%), and there was no adverse effect up to $500{\mu}g/mL$ of fraction-2. For the collagenase inhibitory activity, the samples showed $IC_{50}$ of 139.8, 20.6, and $16.8{\mu}g/mL$, respectively, which were competitive to 1, 10-Phenanthroline ($55.4{\mu}g/mL$). The extract and fraction-2 showed $IC_{50}$ of 61.8 and $67.1{\mu}g/mL$ for elastase. These results suggest that A. nitidus extract can be used as a cosmetic material useful for antioxidant, whitening, and prevention of skin aging without adverse effects.

• Korean Journal of Heritage: History & Science
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• v.43 no.2
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• pp.60-81
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• 2010

Jeju Island, in Korea, shows many characteristics that are differentiated from the rest of Korea. Its culture is rooted in mythology which advocates a egalitarian, rather than hierarchical, social structure, the place of women in the home is relatively high, and the formation of buildings, the separation of cooking and heating facilities, and the living format of residential homes is dissimilar. These disparities in culture indicate that Jeju Island's heritage was not formed only from influences from the North, but also from other places as well. To fill in the blanks, residential homes in Jeju Island were compared with those scattered throughout the East China Sea, which connect the southern coastline of the Korean peninsula and Jeju Island. The regions encompassed by the East China Sea, sharing the Kuroshio current and a seasonal wind, can be considered as one cultural region integrating cultural aspects from the continental North and the oceanbound South. The unique characteristics of southern culture as seen in southern residences was examined through an investigation of the sacred places in which gods were considered to dwell. First, the myths of these areas usually concerned with the ocean, and a sterile environment made sustenance impossible without a dual livelihood, usually taking on the forms of half-farming and half-fishing, or half-farming, half-gardening. Although family compositions were strongly matricentric or collateral thanks to southern influence, a patriarchical system like those found in the North were present in the upper classes and in the cities. Therefore, residential spaces were not divided based on age or gender, as in hierarchical societies, but according to family and function. Second, these areas had local belief systems based on animism and ancestor worship, and household deities were closely related to women, agriculture and fire. The deities of the kitchen, the granary and the toilet were mostly female, and the role of priest was often filled by a woman. After Buddhism and Confucianism were introduced from mainland Korea, China and Japan, the sacred areas of the household took on a dual form, integrating the female-focused local rites with male-centered Buddhist and Confucian rites. Third, in accordance with worship of a kitchen deity, a granary deity, and a toilet deity led to these areas of the home being separated into disparate buildings. Eventually, these areas became absorbed into the home as architectural technology was further developed and lifestyles were changed. There was also integration of northern and southern cultures, with rites concerning granary and toilet deities coming from China, and the personality of the kitchen deity being related to the southern sea. In addition, the use of stone in separate kitchens, granaries, and toilets is a distinguishing characteristic of the East China Sea. This research is a part of the results gained from a project funded by the Korea Research Foundation in 2006.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.