• 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.

• Journal of Biosystems Engineering
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• v.11 no.2
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• pp.31-40
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• 1986

Cylindrical and conical types of grain-straw separation equipment which has a stationary crimped sieve drum with rotating inner rotor were constructed. The developed equipments were tested to investigate the characteristics of separating performance under various mechanical conditions and crop conditions. As increase of the inclination of equipment and decrease of pitch of cover vane, the grain recovery was increased while straw rejection was decreased. The grain recovery and overall efficiency were decreased as the rotor speed and feeding velocity were increased for both varieties of rice, moisture contents, and test equipments. Conical prototype equipment performed higher straw rejection, lower grain recovery, and lower power requirement. However, separation performance of conical type equipment was more widely varied with various test conditions compared to cylindrical one. The performance of both equipments showed relatively insensitive to crop feedrate and crop properties, such as variety, moisture content, and grain-to-straw ratio.

• Journal of the Korean Geographical Society
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• v.31 no.4
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• pp.662-671
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• 1996

Since the world's economic and political structures have changed, the term 'globlization' has shown up as a dominant power and as a necessity for regional and national development. Each nation is responding to the globalization process economically and politically in various ways. In general, however, the economic response to the globalization is economic restructuring from the Fordist industries to 'flexible specialization'. And the political response to the globalization is 'global localization' as a new type of local politics(i.e., local policy activism or growth-enhancing local development policies). The crisis of Fordism shifted the role of local governments towards more involovement with local economic development. Local governments are mobilizing for loca economic development, they are taken into a process of institutional change that tends to redefine their responsibilities inside the state. Local governments thus tend to act as an entrepreneur in order to restructure theiir local economies and to compete with other national and international regions. State restructuring towards enerepreneurialism and efficient regional policy pursuing a pro-growth coalition trategy is chosen as a new mode of regulation for the post-Fordism at the local level. The flexible specialization as the post-Fordist economy and the local government as an entrepreneur are the global choice for globalization and a post-Fordist society. The paper focuses on the regulation theory which comprises the political economic perspective on resturcturing. Economic restructuring and state restructuring will be discussed in detail. And the paper tries to combine the economic globalization and the global localization as economic and political responses to globalization.

• Journal of the Korea Organic Resources Recycling Association
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• v.19 no.1
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• pp.86-92
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• 2011

In order to reduce dependence on the fossil fuels and $CO_2$ gas emission in farming activities, the government has pushed ahead with making the self-sufficiency of farming energy up 40% level in green villages. The objectives of this study are to survey the energy consumption of horticultural facilities or agricultural machineries, and to analyze the reduced $CO_2$ gas emission level from fossil fuel to bio-diesel fuel. For the implement of this study, it is necessary to analyze the energy consumption level in the various sector of farming activities, and available renewable energy sources should be selected. Annual total $CO_2$ gas emission in the tillage farming sector was analyzed as $5,667,258\;t-CO_2$ and that in the horticultural facilities occupied $4,932,607\;t-CO_2$, while the $CO_2$ gas emission level of diesel fuel was $3,105,707\;t-CO_2$, and that of the heavy oil showed $1,370,578\;t-CO_2$. The average $CO_2$ gas emission level of horticultural facilities in the country was analyzed as $29,418\;t-CO_2/ha$. Among the total energy consumption of agricultural machineries, tractor used 284,763kL, power tiller spent 221,314 kL, grain drier consumed 145,524kL and combine tractor expend 72,537kL. From the comparison of $CO_2$ gas emission level between fossil fuel and bio-diesel fuel for the horticultural facilities or agricultural machinery in G-City, Jeonbuk Province, the $CO_2$ gas emission level can be reduced by 7% through replacing the fuel from fossil to biodiesel.

• Korean Journal of Heritage: History & Science
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• v.36
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• pp.347-377
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• 2003

China is a country with large agricultural areas and subject to frequent calamities. Drought is the top of them. It has been a key problem for development of agriculture in the country. In the long struggle against drought, Chinese have accumulated many rational and irrational experiences. The Dragon Kings Belief, which is popular in North China and discussed in a thesis, is one of their irrational experiences. The belief was passed together with Buddhism from India to China in the Tang Dynasty. After it settled down, it was incorporated with the local five dragons belief and a set of beliefs in dragon kings came into existence. The emergence of the dragon kings belief ended the history that the title of rain got was not clear in China and Dragon kings finally got the status. Irrigation is the lifeblood of agriculture in China. In a Chinese mind, Dragon kings are the most important gods who take charge of rain and thus offer the lifeblood. In understanding the nature and characteristics of Chinese traditional culture, it is important for us to make clear the origin and evolution of the belief, find out its nature, function and operation. In the every year beginning of February of the Fanzhuang calendar in the people of Hebeisheng Zhaoxian, would all hold a festival to offer sacrifices to the $^{{\circ}TM}^{\prime}longpai$. Longpai was regarded as the core of the temple fair, thus the native sons came to call this festival; "longpaihui". In this region the'Fanzhuang longpaihui'developed into a well knownand grand temple fair. It was able to attract numerous pilgrims with its special magic power, occupying a place in $China^{{\circ}TM}$ 'eryueer'festival with festive dragon activities. The dragon is a common totem among Chinese nationals. The belief worship of the dragon dates from the start time of primitive societies. Dragon oneself the ancients worship's thunder lightning. In the worship of the great universe, at first afterwards this belief with the tribe's totem worships to combine to become the animal spirit. In ancient myths legends, along with folk religion and beliefs all hold a very important position. The longpaihui is a temple fair without a temple; this characteristic is a distinction between longpaihui and other temple fairs. As for longpaihui must of the early historical records are unclear. The originator of a huitou system has a kind of organized form of the special features rather, originator of a huitou not fix constant, everything follows voluntarily principle, can become member with the freedom, also can back at any time the meeting. There is a longpaihui for 'dangjiaren', is total representative director in the originator of a huitou will. 'banghui' scope particularly for extensive, come apparently every kind of buildup that help can return into the banghui, where is the person of this village or outside village of, the general cent in banghui work is clear and definite, for longpaihui would various businesses open smoothly the exhibition provides to guarantees powerfully. Fanzhuang longpaihui from the beginning of February to beginning six proceed six days totally. The longpai is used as the ancestry absolute being to exsits with the community absolute being at the same time in fanzhuang first took civil faith, in reality is a kind of method to support social machine in native folks realize together that local community that important function, it provided a space, a kind of a view to take with a relation, rising contact, communication, solidify the community contents small village, formation with fanzhuang. The fanzhuang is used as supplies for gathering town, by luck too is this local community trade exchanges center at the same time therefore can say the faith of the longpai, in addition to its people's custom, religious meaning, still have got the important and social function. Moreover matter worthy of mentioning, Longpai would in organize process, from prepare and plan the producing of meeting every kind of meeting a longpeng of the matter do, all letting person feeling is to adjust the popular support of, get the mass approbation with positive participate. Apart from the originator of a huitou excluding, those although not originator of a huitou, however enthusiasm participate the banghui of its business, also is too much for the number.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.175-183
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• 2021

Gongjae Yoon DuSeo(1668~1715), from Haenam in the late Joseon Dynasty, is a scholar-born painter who was active during King Sukjong. He is the person who created the foundation as a pioneer of realist paintings in the late Joseon period during the transition from the middle to the latter period. He was born in Namin's prestigious family, but he ended his career as part of a partisan fight and immersed himself in painting and learning. 18C, the beginning of the late Joseon Dynasty, was a period when Silhak emerged and the Jinkyung era opened with awareness of nationalism. At this time, by incorporating the Silhak thought into the art world, the real reformed aesthetic consciousness was demonstrated to pioneer common people's customs, the application of Western painting methods, the pursuit of realist techniques, and the introduction of Namjongmuninhwa. His view of painting, who thoroughly learned the old things and pursued change, must have both the form and spirit that he can achieve 'HwaDo' only when it has the science of 'learning and knowledge' and the technical elements of 'practice and quality' emphasized. He has worked in a variety of reconciliations. In particular, portrait paintings are characterized by ihyeongsasin's realistic expressions of aesthetics. His masterpiece, 「Self-portrait」, excels in extreme-realistic depiction and innovation in composition, and stands out with an unconventional experimentation spirit that expresses his mind and thoughts in a painting with a sense of resentment. His landscape paintings combine to express the form as it is and mental notions, and beautifully embodied Do as a form, thus achieving ihyeongmido, which reached the level of'joyfulness forgotten even the heart of joy'. On the other hand, the generalization of the common people using various common people's lives as the subject of an open-mindedness aimed at gaining the facts of ihyeongsajin, a passive protest against corrupt power and an expression of a spirit of love. Since then, his painting style has been passed down from generation to generation to his eldest son Yoon Deok-hee and his grandson Yoon Yong, leading the change and revival of calligraphy art in the late Joseon Dynasty.

• (The) Research of the performance art and culture
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• no.32
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• pp.489-524
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• 2016

This study examines the birth of a genre, the $Sekky{\bar{o}}bushi$ Misemono Opera, focusing on how it accepted and modernized Katarimono $Sekky{\bar{o}}bushi$. Unlike earlier studies, it argues that Terayama was clearly different from other first-generation Angura artists, in that he rebirthed the medieval story $Sekky{\bar{o}}bushi$ as a modern Misemono Opera. Shintokumaru (1978) was directed by Terayama $Sh{\bar{u}}ji$, a member of the first generation of Japan's 1960s Angura Theatre Movement. It takes as its subject the Katarimono $Sekky{\bar{o}}bushi$ Shintokumaru, a story set to music that can be considered an example of the modern heritage of East Asian storytelling. $Sekky{\bar{o}}$ Shintokumaru is set in Tennoji, Japan. The title character Shintoku develops leprosy as a result of his stepmother's curse and is saved through his fiancee Otohime's devoted love and the spiritual power of the Bodhisattva Avalokitesvara. In this work, Terayama combined the narrative style of $Sekky{\bar{o}}bushi$ with J.A. Caesar's shamanistic rock music and gave it the subtitle 'Misemono Opera by $Sekky{\bar{o}}bushi$'. He transforms its underlying theme, the principle of goddesses and their offspring in a medieval religious world and the modori (return) instinct, into a world of mother-son-incest. Also, the pedestrian revenge scene from $Sekky{\bar{o}}bushi$ is altered to represent Shintokumaru as a drag queen, wearing his stepmother's clothes and mask, and he unites sexually with Sensaku, his stepbrother, and ends up killing him. The play follows the cause and effect structure of $Sekky{\bar{o}}bushi$. The appearance of katarite, a storyteller, propelling the narrative throughout and Dr. Yanagida Kunio is significant as an example of the modern use of self-introduction as a narrative device and chorus. Terayama $Sh{\bar{u}}ji^{\prime}s$ memories of desperate childhood, especially the absence of his father and the Aomori air raids, are depicted and deepened in structure. However, seventeen years after Terayama's death, the version of the play directed by Ninagawa Yukio-based on a revised edition by Kishida Rio, who had been Terayama's writing partner since the play's premier-is the today the better-known version. All the theatrical elements implied by Terayama's subtitle were removed, and as a result, the Rio production misses the essence of the diverse experimental theatre of Terayama's theatre company, $Tenj{\bar{o}}$ Sajiki. Shintokumaru has the narrative structure characteristic of aphorism. That is, each part of the story can stand alone, but it is possible to combine all the parts organically.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.