• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Korean Journal of Environmental Biology
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• v.37 no.4
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• pp.707-718
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• 2019

Ecklonia cava Kjellman, which has recently gained popularity due to the spread of farming techniques, is expected to be developed in various varieties in the future. There exist increased needs for research on the basis of natural populations and inter-regional morphological variations. We compared the morphology of the aquaculture and natural populations from 16 coastal areas in Korea. The 18 traits found suitable for distinguishing varieties were selected from 14 measurement traits and 4 ratios related to the main morphology and characteristics of primary blade, secondary blade, and stipe. In the cluster analysis, Janggil (E4) and Sorok (S7) showed significant differences from those of the same coastal region. Two groups, including Suyou (Q6, Q8, and Q10) which was the second year of farming, of the rest of the populations from East sea and southern coast were distinguished. Three populations of Jeju were divided into a regional group. In the principal component analysis (PCA), a large number of populations from East sea and Southern coast appeared in the center with aquaculture populations. PC1 and PC2 associated with traits of secondary blade index, stipe length and diameter, stipe length/primary blade length, primary blade length and width, secondary blade number, secondary blade length and width, divided E4, S7 and populations of Jeju region. As a result, the 18 characters of this study were found to be useful as criteria for discrimination of populations with significant differences in each coastal region, and these populations were expected to be candidates for new varieties.

• Journal of Animal Environmental Science
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• v.15 no.1
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• pp.9-16
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• 2009

This study, tasting 14 months, was conducted to investigate the effects of different pen size and group size on growing-fattening characteristics of Hanwoo steers. Forty-eight, 12-month-old Hanwoo steers($305.8{\pm}32.2\;kg$) were randomly assigned to three groups($35.28\;m^2$; n=4 heads, $70.56\;m^2$; n=8 heads, $105.84\;m^2$; n=12 heads) and reared in separate pens with a constant space allowance of $8.82m^2$ per head from 12 to 21 month of age and then regrouped to 4 heads per pen. A common diet including concentrate(limited) and forage(ad lib) was provided to all the animals. Images of live animal ultrasonic back fat thickness, longissimus muscle area and Marbling score were evaluated in three months interval from 12 months of age using an ultrasound equipment(HS-2000) at the 13th rib and lumber vertebra interface of left side. Significant differences of ADG was found mainly at $15{\sim}18$ month and $18{\sim}21$ month fattening stages(p<0.05). Marbling score(MS) was higher(p<0.05) in 12 heads group when compared with that of 4 and 8 heads groups after 18 months. Animals in 12 heads group had the lowest Average daily gain(ADG) but showed the highest longissimus muscle area(LMA) and marbling score(MS). In addition, Hanwoo steers in 12 heads group obtained a higher quality appearance(HQA) of 82.7% than that of other treatments. The results indicated that Hanwoo steers housed on large group size and pen size decreased their ADG but improved meat quality.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.2 no.3
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• pp.10-17
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• 1999

In order to confirm the effectiveness of the natural river improvement technique, the analysis of vegetation was carried out in Yangjae stream between 1996 and 1998. The results of this study showed the numbers of riparian plants had increased from 41 species to 53 species, and the dominant species had changed from annual and biannual(Humulus japonicus, Persicaria thunbergii, Persicaria hydropiper, Panicum dichotomiflorum, Echinochloa crus-galli) to perennials (Phragmites communis). The variation in biomass and biodiversity index were measured and calculated according to the rehabilitation method. Biomass were varied 302 to $828g/m^2$ and biodiversity index was varied 1.53 to 1.52 at point bar plots(A treatment plots) from 1996 to 1998. In conclusion, the natural river improvement technique which has operated in Yanjaecheon for three years has contributed to restoration of riparian plants. Additionally, subsequent study using this technique should be followed in the near future.

• Korean Journal of Environment and Ecology
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• v.24 no.2
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• pp.147-156
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• 2010

This study was conducted from April, 2002 to March 2006, using three urban streams(Gap Stream, Yudeung Stream and Daejeon Stream) in Daejeon Metropolitan City. 12,027 individual birds summed by the peak count in 126 species, 34 families, and 13 orders were observed from three stream sites. Dominant species were of Anas poecilorhyncha, Anas crecca, Columba livia, Passer montanus, and Egretta garzetta(in that order). The groups of birds were classified into six types. The most frequent group were the arbor birds(54 species), while the smallest group was the diving ducks(7 species). As for the number of individuals, the shrub bird group had 721 individuals while the dabbling ducks observed had 4,974 individuals. Regarding the distribution of birds appeareing in each stream, 14,885 individual numbers in 114 species were observed at Gap Stream, 6,642 individuals in 90 species at Yudeung Stream and 4,202 individuals in 69 species at Daejeon Stream. Various indices of the birds were analyzed with respects to the similarities between streams. Gap Stream had similar characteristics to Yudeung Stream, and the latter was similar to Daejeon Stream. However, Gap Stream and Daejeon Stream showed different characteristics. The dominance index of each section was calculated using ten dominant bird species top-down. Subsequently, the birds and their preferred environment were analyzed. The results showed that shrub birds and arbor birds preferred the upper stream of every stream, while herons and dabbling ducks inhabited the midstream. Dabbling ducks and some diving ducks appeared downstream.

• Korean Journal of Environmental Agriculture
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• v.27 no.1
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• pp.1-9
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• 2008

The main purpose of this study is to accumulate the fundamental data representing groundwater of plastic film houses by means of water quality and its multivariate statistical analysis. Groundwater samples were collected in every two years since 2000 to 2004 from total 211 sites. According to the result of water quality analysis, ground water quality was suitable for irrigation purpose averagely. Correlation analysis showed that EC was highest positively correlated with $Mg^{2+}$ to 0.810(p<0.01), 0.776(p<0.01) in April and July, respectively. $NO_3-N$ was highest positively correlated with T-N to 0.794(p<0.01) in October. This result shows that it can lead to a different result even in similar case sometimes. Four factors were extracted through factor analysis in April and July, but five factors were extracted in October. The proportions of cumulative variance by the factor were 64.9, 60.2, and 70.7 in April, July, and October, respectively. The first factor was highly related to anions and cations such as $Ca^{2+},\;Mg^{2+},\;Cl^-,\;{SO_4}^{2-}$, and EC in contrast to that of stream water. According to the cluster analysis, 211 sites are classified into four groups. Common type of ground water quality was shown in group A. The pH and $PO_4-P$ were highest in Group B. The anions and cations were highest in Group C. $COD_{Cr}$ was highest in Group D.

• Journal of agriculture & life science
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• v.50 no.1
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• pp.105-115
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• 2016

This study was carried out to establish the optimum forest management plan for the Cryptomeria japonica plantations in southern inland and Jeju island in Korea. Sixty seven circular sample plots of 0.04ha were established and we surveyed vegetation structure and growth characteristics from three layers(upper, middle, and lower). As a result of cluster analysis obtained by importance values of each tree species, the community type of C. japonica stands were classified into C. japonica group(C1) and C. japonica-C obtusa group. C. obtusa community were also sbudivided into P. thunbergii-Q. serrata group(C2) and Q. serrata-C obtusa group(C3). In tree layers importance value(IV) of C. japonica were 97.2% in C1, 80.7% in C2, and 47.6% in C3 and in sub-tree layers IV were 8.9% in C1, 15.2% in C2, and 5.7% in C3. Especially in C3 there are bamboo species (Smilacina japonica var. lutecarpa and Pseudosasa japonica) it is necessary for us to control them. In shrub layers C. japonica were found in C1(9.2%) and C2(7.0%), but except for C3. In tree layer species diversity indices of each community ranged from the lowest 0.059 in C1 to the highest 0.548 in C3. Dominance ranged from 0.958 in C1 to 0.393 in C3 which may caused by interspecific competition. Current annual increment of diameter growth ranged from 7.01mm/yr to 8.04mm/yr. As a result of our study we recommend the application of proper thinning and pruning for C1 and C2.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.779-793
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• 2023

Intensive and long-term aquaculture activities in Korea have generated considerable amounts of organic matter, deteriorating the sedimentary environment and ecosystem. The Korean government enacted the Fishery Management Act to preserve and manage the environment of fish farms. Based on this, a fisheries environment assessment has been conducted on fish cage farms since 2014, necessitating the development of a scientific and objective evaluation method suitable for the domestic environment. Therefore, a benthic health index (BHI) was developed using the relationship between benthic polychaete communities and organic matter, a major source of pollution in fish farms. In this study, the development process and calculation method of the BHI have been introduced. The BHI was calculated by classifying 225 species of polychaetes appearing in domestic coastal and aquaculture areas into four groups by linking the concentration gradient of the total organic carbon in the sediment and the distributional characteristics of each species and assigning differential weights to each group. Using BHI, the benthic fauna communities were assigned to one of the four ecological classes (Grade 1: Normal, Grade 2: Slightly polluted, Grade 3: Moderately polluted, and Grade 4: Heavily polluted). The application of the developed index in the field enabled effective evaluation of the Korean environment, being relatively more accurate and less affected by the season compared with the existing evaluation methods like the diversity index or AZTI's Marine Biotic Index developed overseas. In addition, using BHI will be useful in the environmental management of fish farms, as the environment can be graded in quantified figures.

• 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.

• Korean Journal of Environment and Ecology
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• v.26 no.3
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• pp.348-361
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• 2012

Altitude is a factor that plays an important role in the diversity, richness and composition of species. Recently, much attention has been paid to the distribution of butterflies and insects according to altitude. The purpose of this article is to propose a method to preserve and manage species efficiently by reviewing the distribution of butterflies according to different altitudes in Mt. Gyeryong National Park. This study found that the number of species and individuals decreased as the altitude increased, possibly due to the increased amount of shade caused by the crown density. When analyzing the factors influencing the distribution of species other than altitude, it was found that the slope, vegetative colonies and hydrosphere distance were correlated with the change in species distribution. As these species are closely related to food plants, it may save time and reduce the cost as well as allow an efficient evaluation of the bio-diversity if these species are selected as biological indicator species suitable for detecting the changes in the forest. It is judged to be a more efficient means of species preservation to accumulate and quantify the materials regarding environmental elements such as the climate, microclimate and food plants, as this would allow the butterfly distribution to be estimated.