• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.2
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• pp.35-45
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• 2023

First, The spatial distribution characteristics of old big trees were analyzed using ArcGIS figures by combining basic information such as species and ages of old big trees in Handan City, which were compiled by the local bureau of landscaping. The types of species, distribution by ages of trees, ownership status, growth status, and diversity status were comprehensively analyzed. Statistically, Styphnolobium, Acacia, Gleditsia, and Albizia of Fabaceae accounted for the majority, of which Sophora japonica accounted for the highest proportion. Sophora japonica is widely and intensively distributed to each prefecture and district in Handan city. According to the age and distribution, the old big trees over 1000 years old were mainly Sophora japonica, Zelkova serrata, Juniperus chinensis, Morus australis Koidz., Dalbergia hupeana Hance, Ceratonia siliqua L., and Pistacia chinensis, and Platycladus orientalis. Second, as found in each type of old big tree status, various types of old big tree status were investigated, the protection management system, protection management process, and protection management benefits were studied, and the protection of old big tree was closely related to the growth environment. Currently, the main driving force behind the protection of old big trees is the worship of old big trees. By depositing its sacredness to the old big tree and sublimating the natural character that nature gave to the old big tree into a guiding consciousness of social activities, nature's "beauty" and personality's "goodness" are well combined. The protection state of the old big tree is closely related to the degree of interaction with the surrounding environment and the participation of various cultures and subjects. In the process of continuously interacting with the surrounding environment during the long-term growth of old big trees, it seems that a natural sanctuary was formed around old big trees in the process of voluntarily establishing a "natural-cultural-scape" system involving bottom-up and top-down cross-regions, multicultural and multi-subjects. Third, China focused on protecting and recovering old big trees, but the protection management system is poor due to a lack of comprehensive consideration of historical and cultural values, plant diversity significance, and social values of old big trees in the management process. Three indicators of space's regional characteristics, property and protection characteristics, and value characteristics can be found in the evaluation of the natural characteristics of old giant trees, which are highly valuable in terms of traditional consciousness management, resource protection practice, faith system construction, and realization of life community values. A systematic management system should be supported as to whether they can be protected and developed for a long time. Fourth, as the perception of protected areas is not yet mature in China, "natural sanctuary" should be treated as an important research content in the process of establishing a nature reserve system. The form of natural sanctuary management, which focuses on bottom-up community participation, is a strong supplement to the current type of top-down nature reserve management in China. Based on this, the protection of old giant trees should be included in the form of a nature reserve called a natural monument in the nature reserve system. In addition, residents of the area around the nature reserve should be one of the main agents of biodiversity conservation.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.3
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• pp.195-207
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• 2000

Organic and inorganic characteristics including bacterial cell number, enzyme activity, nutrients, and heavy metals have been monitored in twelve acrylic experimental tanks for two weeks to estimate and compare self-purification capacities in two Korean wet-land environments, tidal flat and rice field, which are possibly different with the environments in other countries because of their own climatic conditions. FW tanks, filled with rice field soils and fresh water, consist of FW1&2 (with paddy), FW3&4 (without paddy), and FW5&6 (newly reclaimed, without paddy). SW tanks, filled with tidal flat sediments and salt water, are SW1&2 (with anoxic silty mud), SW3&4 (anoxic mud), and SW5&6 (suboxic mud). Contaminated solution, which is formulated with the salts of Cu, Cd, As, Cr, Pb, Hg, and glucose+glutamic acid, was spiked into the supernatent waters in the tanks. Nitrate concentrations in supernatent waters as well as bacterial cell numbers and enzyme activities of soils in the FW tanks (except FW5&6) are clearly higher than those in the SW tanks. Phosphate concentrations in the SW1 tank increase highly with time compared to those in the other SW tanks. Removal rates of Cu, Cd, and As in supematent waters of the FW5&6 tanks are most slow in the FW tanks, while the rates in SW1&2 are most fast in the SW tanks. The rate for Pb in the SW1&2 tanks is most fast in the SW tanks, and the rate for Hg in the FW5&6 tanks is most slow in the FW tanks. Cr concentrations decrease generally with time in the FW tanks. In the SW tanks, however, the Cr concentrations decrease rapidly at first, then increase, and then remain nearly constant. These results imply that labile organic materials are depleted in the FW5&6 tanks compared to the FW1&2 and FW3&4 tanks. Removal of Cu, Cd, As from the supernatent waters as well as slow removal rates of the elements (including Hg) are likely due to the combining of the elements with organic ligands on the suspended particles and subsequent removal to the bottom sediments. Fast removal rates of the metal ions (Cu, Cd, As) and rapid increase of phosphate concentrations in the SW1&2 tanks are possibly due to the relatively porous anoxic sediments in the SW1&2 tanks compared to those in the SW3&4 tanks, efficient supply of phosphate and hydrogen sulfide ions in pore wates to the upper water body, complexing of the metal ions with the sulfide ions, and subsequent removal to the bottom sediments. Organic materials on the particles and sulfide ions from the pore waters are the major factors constraining the behaviors of organic/inorganic elements in the supernatent waters of the experimental tanks. This study needs more consideration on more diverse organic and inorganic elements and experimental conditions such as tidal action, temperature variation, activities of benthic animals, etc.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• 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.

• Journal of Korean Society of Forest Science
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• v.54 no.1
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• pp.1-24
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• 1981

Kangweon-Do is rich in sightseeing resources. There are three sightseeing areas;first, mountain area including Seolak and Ohdae National Parks, and chiak Provincial Park; second eastern coastal area; third lake area including the watersheds of North Han River. In this paper, several methods of forestation were studied for landscaping the North Han River watersheds centering around Chounchon. In Chunchon lake complex, there are four lakes; Uiam, Chunchon, Soyang and Paro from down to upper stream. The total surface area of the above four lakes is $14.4km^2$ the total pondage of them 4,155 million $m^3$, the total generation of electric power of them 410 thousand Kw, and the total forest area bordering on them $1,208km^2$. The bordering forest consists of planned management forest ($745km^2$) and non-planned management forest ($463km^2$). The latter is divided into green belt zone, natural conservation area, and protection forest. The forest in green belt amounts to $177km^2$ and centers around the 10km radios from Chunchon. The forest in natural conservation area amounts to $165km^2$, which is established within 2km sight range from the Soyang-lake sides. Protection forest surrounding the lakes is $121km^2$ There are many scenic places, recreation gardens, cultural goods and ruins in this lake complex, which are the same good tourist resources as lakes and forest. The forest encirelng the lakes has the poor average growing stock of $15m^3/ha$, because 70% of the forest consists of the young plantation of 1 to 2 age class. The ration of the needle-leaved forest, the broad-leaved forest and the mixed forest in 35:37:28. From the standpoint of ownership, the forest consists of national forest (36%), provincial forest (14%), Gun forest (5%) and private forest(45%). The greater part of the forest soil, originated from granite and gneiss, is much liable to weathering. Because the surface soil is mostly sterile, the fertilization for improving the soil quality is strongly urged. Considering the above-mentioned, the forestation methods for improving landscape of the North Han River Watersheds are suggested as follows: 1) The mature-stage forest should be induced by means of fertilizing and tendering, as the forest in this area is the young plantation with poor soil. 2) The bare land should be afforested by planting the rapid growing species, such as rigida pine, alder, and etc. 3) The bare land in the canyon with moderate moist and comparatively rich soil should be planted with Korean-pine, larch, ro fir. 4) Japaness-pine stand should be changed into Korean-pine, fir, spruce or hemlock stand from ravine to top gradually, because the Japanese-pine has poor capacity of water conservation and great liability to pine gall midge. 5) Present hard-wood forest, consisting of miscellaneous trees comparatively less valuable from the point of wood quality and scenerity, should be change into oak, maple, fraxinus-rhynchophylla, birch or juglan stand which is comparatively more valuable. 6) In the mountain foot within the sight-range, stands should be established with such species as cherry, weeping willow, white poplar, machilus, maiden-hair tree, juniper, chestnut or apricot. 7) The regeneration of some broad-leaved forests should be induced to the middle forest type, leading to the harmonious arrangement of the two storied forest and the coppice. 8) For the preservation of scenery, the reproduction of the soft-wood forest should be done under the selection method or the shelter-wood system. 9) Mixed forest should be regenerated under the middle forest system with upper needle-leaved forest and lower broad-leaved forest. In brief, the nature's mysteriousness should be conserved by combining the womanly elegance of the lakes and the manly grandeur of the forest.