• Journal of the Korean Society of Food Culture
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• v.9 no.4
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• pp.379-394
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• 1994

The purpose of this study was to identify the correlation between the factors influencing on housewives' decision-making processes of organic foods and the relating variables, and the 5 stages of decision-making processes of the EBK model is utilized in this study. The sample was selected from 411 housewives living in Seoul from 1st of September through 20th of September, 1993. Frequency, Percentage, Mean, Factor analysis, One-way ANOVA, Duncan's multiple range test, t-Test, Correlation, Multiple regression analysis and Path analysis were measured. Major results are as follows: 1. Purchasing motivation of the organic foods were in order of the health care, nutritive value and taste care. 2. The major informations source for the knowledge of organic foods were in order of TV/radio, newspaper/magazine, recommendations informations and advice through a family/friends/acquaintances. 3. Evalution criteria in shopping of organic foods, the total degree of consideration over the purchasing factors of organic foods was fairly high level: consumers thought much of the sanitation/freshness, nutritive value and the food safety. In this regard opinion leaders was dominantly mass media. Consumers have a tendency to purchase organic foods in consideration of their children and husband. 4. Major place to purchase organic foods are super markets and department stores. And When shopping organic foods, housewives by all means confirm the check points in their own mind, which were expiry date, manufactured date and packing condition, but unexpectedly manufactured company was out of concern. 5. Housewives usually satisfy with decision after purchasing organic foods, while they were fairly unsatisfied with the price, quality, incomplete description for ingredients and manufactured date. 6. The variables influencing to the sincerity when selecting the most desired organic foods is how be cares about the natural freshness of the foods and the types of residents in order. Another interesting tendency is the richer they are very considerate to decide. It is to say the people who cares more about the natural freshness is the sincerer when making decision and also the class who lives in the apartment house enjoying high income do not easily accept the product quality.

• Journal of Korean Society of Forest Science
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• v.37 no.1
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• pp.1-16
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• 1978

The study describes on the identification and morphological characteristics of each species, ecological characteristics and propagation techniques, and developing utilization measures of the Parthenocissus plants for environment conservation and revegetation of the babe rock-slopes. The following species and varieties are disscussed in this study; Parthenocissus tricuspidata (S. et Z.) Planch. var. veitchii Rehd. var. lowii Rehd. var. pupurea Hort. Parthenocissus quiquefolia (L.) Planch. var. engelmanni Rehd. var. saint-pauli Rehd. var. hirsuta Planch. Parthenocissus henryana Diels et Gilg. Parthenocissus thomsoni Planch. Parthenocissus heptaphylla Small. Parthenocissus inserta (Kern.) K. Fritsch. Parthenocissus laetevirens Rehd. Parthenocissus himalayana Planch. These are, in general, all vigorous self-clinging climbers that will quickly cover a wall and bare rock surfaces with a dense network of branch growths and beautiful green leaves which change to shades of scarlet and crimson before they fall in Autumn. Parthenocissus tricuspidata out of 8 species in the genus Parthenocissus is the most useful plant for the environment conservation including the bare rock-slope revegetation and for the production of food and shelter for wildlifes. This native of Korea clings by means of small rootlike holdfasts (adhesive discs) and holds (tendrils) to stone work or any other solid support, tenaciously.

• Economic and Environmental Geology
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• v.51 no.1
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• pp.67-76
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• 2018

This study reviews three eco-friendly energy towns with hybrid thermal energy supply systems and borehole thermal energy storage (BTES) in Canada and Denmark. The district heating and cooling systems were designed by using multi-source energy for the higher efficiency and reliability as well as environment. ADEU (Alexandra District Energy Utility) located at the developing area in the city of Richmond, Canada was designed to supply district energy with the installation of 726 borehole heat exchangers (BHEs) and a backup boiler using natural gas. DLSC (Drake Landing Solar Community) located in the town of Okotoks, Canada is a district system to store solar thermal energy underground during the summer season by seasonal BTES with 144 BHEs. Brædstrup Solpark district heating system located in Denmark has been conducted energy supply from multiple energy sources of solar thermal, heat pump, boiler plants and seasonal BTES with 48 BHEs. These systems are designed based on social and economic benefits as well as nature-friendly living space according to the city based energy perspective. Each system has the energy center which distribute the stored thermal energy to each house for heating during the winter season. The BHE depth and ground thermal storage volume are designed by the heating and cooling load as well as the condition of ground water flow and thermophysical properties of the ground. These systems have been proved the reliance and economic benefits by providing consistent energy supply with competitive energy price for many years. In addition, the several expansions of the service area in ADEU and Brædstrup Solpark have been processed based on energy supply master plan. In order to implement this kind of project in our country, the regulation and policy support of government or related federal organization are required. As well as the government have to make a energy management agency associated with long-term supply energy plan.

• Journal of the Korean Institute of Landscape Architecture
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• v.17 no.1
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• pp.43-54
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• 1989

In recent years plants have increasingly become in inferior part of the interior designing of large buildings. In 28 large buildings selected at random in Seoul City have been subjected to studies on utilization status of fille interior landscape plants. The results obtained were as follows. 1. Plant class found in Interior of large buildings were 59 class, especially Dracaena were the most predominent plants among them, and then comes Monstera, Phiodendron, Schefflera, and Washingtonia in that order. 2. The most abundant ornamental plant cultivars were Monstera adansoii(Monstera perutusa cv.), and then comes Schefflera arboricora(Schefflera Hong Kong cv.), Washingionia rubusta (Washingtonia palm). Rhapis excelsa, and Diffenbachia(Hawaii Snow cv.) in that order. 3. Foliage plants among the interior landscape plants showed 99.5 percent and Woody plants and Bonsai plants showed each 0.4, 0.1 percent. 4. Climbing foliage plants found in 28 large building observed For the present study were 9 cultivar, and the most abundant plants were Hedera (pittsburgh cv.) and Epipremnum (Marble Queen cv.) pl anted to clustered planting. 5. A majority of plants used to plastic pot, and most of 71an1s place on the floor. 6. Height of plants ranging less then 50cm were more frequently found, but ranging from 50cm to 2.0m were 4.3 percent and the most predominent height of plants were Canariensis showed 4m in the large buildings. 7. Interior light intensity in large building were shortage, therefore artificial lamp for formal growing needed to be equipped. 8. Purpose growth of interior plants were to in order visitors. 9. 7he superintendents prefered to used pot-stand. 10. The most important environment factor for plant growing were light, humidity, and water.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.3
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• pp.228-239
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• 1995

A model experiment on the pair midwater trawl net which is prevailing in Denmark is carried out to get the basic data available for Korean pair bottom trawlers. The model net was made in 1/30 scale considering the Tauti's Similarity law of fishing gear and the dimension of experimental tank. The vertical opening, horizontal opening, towing tension and net working depth of the model net were determined in the tank within the towing velocity 0.46~1.15m/sec, front weight 15.5~62.0g and distance between paired boats 5~8m(which correpond to 2~5k't in towing velocity, 70~280kg in weight and 150~240m in distance respectively in the prototype net). The results got from the model experiment can be converted into the full scale net as follows; 1. Vertical opening showed the largest value of 32m at the condition of 2k't in towing velocity, 280kg in front weight and 150m in the distance between paired boats, and the smallest value of 6m at the condition of 5k't in towing velocity, 70kg in front weight and 240m in the distance between paired boats. 2. Horizontal opening showed the largest value of 45m at the condition of 5k't in towing velocity, 70kg in front weight and 240m in the distance between paired boats, and the smallest value of 33m at the condition of 2k't in towing velocity, 280kg in front weight and 150m in the distance between paired boats. 3. Towing tension showed the largest value of 10, 000kg at the condition of 5k't in towing velocity, 280kg in front weight and 240m in the distance between paired boats, and the smallest value of 1, 600kg at the condition of 2k't in towing velocity, 70kg in front weight and 150m in the distance between paired boats. 4. Net working depth showed the largest value of 38m at the condition of 2k't in towing velocity, 280kg in front weight and 150m in the distance between paired boats, and the smallest value of 6m at the condition of 5k't in towing velocity, 70kg in front weight and 240m in the distance between paired boats. 5. Net opening area showed the largest value of 1, 100m super(2) at the condition of 2k't in towing velocity, 280kg in front weight and 180m in the distance between paired boats, and the smallest value of 250m super(2) at the condition of 5k't in towing velocity, 70kg in front weight and 240m in the distance between paired boats.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.39-53
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• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

• Korea journal of population studies
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• v.19 no.2
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• pp.77-105
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• 1996

The rural problems which we are facing start from the extremely small sized population and the skewed population structure by age and sex. Thus we analyzed the change of the rural population. And we analyzed the recent return migration to the rural areas by comparing the recent in-migrants with out-migrants to rural areas. And by analyzing the rural village survey data which was to show the current characteristics of rural population, we found out the effects of the in-migrants to the rural areas and predicted the futures of rural villages by characteristics. The changes of rural population composition by age was very clear. As the out-migrants towards cities carried on, the population composition of young children aged 0~4 years was low and the aged became thick. The proportion of the population aged 0~4 years was 45.1% of the total population in 1970 and dropped down to 20.4% in 1995, which is predicted to become under 20% from now on. In the same period(1970~1995), the population aged 65 years and over rose from 4.2% to 11.9%. In 1960, before industrialization, the proportion of the population aged 0~4 years in rural areas was higher than that of cities. As the rural young population continuously moves to cities it became lower than that in urban areas from 1975 and the gap grew till 1990. But the proportion of rural population aged 0~4 years in 1995 became 6.2% and the gap reduced. We can say this is the change of the characteristics of in-migrants and out-migrants in the rural areas. Also considering the composition of the population by age group moving from urban to rural area in the late 1980s, 51.8% of the total migrants concentrates upon age group of 20~34 years and these people's educational level was higher than that of out-migrants to urban areas. This fact predicted the changes of the rural population, and the results will turn out as a change in the rural society. However, after comparing the population structure between the pure rural village of Boeun-gun and suburban village of Paju-gun which was agriculture centered village but recently changed rapidly, the recent change of the rural population structure which the in-migrants to rural areas becomes younger is just a phenomenon in the suburban rural areas, not the change of the total rural areas in general. From the characteristics of the population structure of rural village from the field survey on these villages, we can see that in the pure rural villages without any effects from cities the regidents are highly aged, while industrialization and urbanization are making a progress in suburban villages. Therefore, the recent partial change of the rural population structure and the change of characteristics of the in-migrants toward rural areas is effecting and being effected by the population change of areas like suburban rural villages. Although there are return migrants to rural areas to change their jobs into agriculture, this is too minor to appear as a statistic effect.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.