• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• The Journal of Dong Guk Oriental Medicine
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• v.8 no.2
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• pp.115-129
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• 2000

The cause that the increase of animality fat intakes, under exercise, fatness, adding the stress, advanced age etc., the occurrence rate of the circulation system disease has been increased. And the thrombosis importantly came to the front as the risk factor of these circulation system's disease. Nowadays, the ischemic disease has especially discussed, for example the angina or myocardial infarction, originated in thrombosis that came from the platelet aggregation. In the western medicine, as the cure and prevention, using the aspirin or ticlopidine for platelet aggregation suppressant. But in the , the curing method must be used properly according to the pectoralgia or heartache's kind, state, grade. The platelet do not attache to the normal hemangioendothelial cell. But when it stimulated by endothelium peronia and so on, it attache to the injury endothelium or rise aggregation between the platelet. On this time, it secrete the platelet aggregation inducer as like ADP, thromboxane A2 from the inside of platelet. So it has first defensive function through the aggregation augment that prevent the celerity consumption of blood. But the activation of abnormal platelet occur the platelet grume and thrombogenesis. So it bring up the occlusive angiosis, so to speak, cardiovascular disease, cerebrovascular disease, arterial sclerosis. In oriental medicine, the thrombosis in the category of blood stasis and this blood stasis present the generalise or local blood circulation disturbance that generated by all kinds of pathological fact or blood stream retention accompanying with a series of syndrome. As the syndrome, stabbing pain fixed at certain region, squamous and dry skin, fullness and pain of the chest and hypochondrium, firmness and fullness of the lower abdomen, black stool, dark purple tongue or with ecchymoses and petechiae etc.. has been created. And it becomes the pathopoiesis cause that the convulsion and palpitation, severe palpitatiion, tympanites, the symtom complex with a mass or swelling in the abdomen, insanity, stricken by wind etc.. Moreover, it used the drugs for invigorating blood circulation and eliminating blood stasis or drugs for removing blood stasis for all kinds of syndrome through the blood stasis. And the drugs for activating the blood circulation, such as Salviae Radix, Angelicae Sinensis Radix, Persicae Semen, Achyranthis Radix, Cnidii Rhizoma, Carthami Flos are used for that. And it is used to the herbs of insects that has strong effect about the disintergrating blood stasis such as Hirudo, Scolopendrae Corpus, Buthus, Lumbricus etc.. On this study, It used Geijibokryunghwan(GBH) and the consisting herbs to investigate the influence of platelet aggregation about drugs that used to improvement various symptoms created by the thrombosis in oriental medicine. GBH formula has as formula recorded in the , action of 'eleminating the evil and not impairment of healthy energy' and 'promoting the flow of QI and cold and heat, so used for the expel blood stasis herbs from the ancient. Therefore we investigated the restraint effect of GBH and the consisting herbs about the platelet agregation induced to the ADP, AA or collagen. The conclusion is following. 1. When it added the aggregation inducer after that it added GBH and individual consisting herbs in the PRP, GBH showed the (+) inhibition effect on the platelet aggregation and it showed the (+) inhibition effect in the individual consisting herbs as like Paeoniae Radix and Moutan Cortex Radicis. 2. It showed the (+), (+,++) inhibition effect on the platelet aggregation in Paeoniae Radix Hoelen, Paeoniae Radix Moutan Cortex Radicis, Hoelen Moutan Cortex Radicis etc. 3. In the aggregation inhibition activating on the difference of density, GBH showed strong inhibition effect to the aggregation state induced to collagen, and it showed the inhibition effect in the individual consisting herbs as like Paeoniae Radix and Moutan Cortex Radicis about the aggregation induced by the collagen. 4. It showed the strong inhibition effect about the aggregation induced by the collagen in Paeoniae Radix Hoelen, Paeoniae Radix Moutan Cortex Radicis, Hoelen Moutan Cortex Radicis etc Like this, as confirm GBH and the individual consisting herb's inhibition effect of platelet aggregation, We considerated that GBH and the individual consisting herbs have practical applicational value of clinical trial in the thrombosis caused by platelet aggregation.

• Radiation Oncology Journal
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• v.26 no.4
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• pp.195-203
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• 2008

Purpose: To investigate the treatment outcome and failure patterns after definitive chemoradiation therapy in locally advanced, unresectable esophageal cancer. Materials and Methods: From February 1994 to December 2002, 168 patients with locally advanced unresectable or medically inoperable esophageal cancer were treated by definitive chemoradiation therapy. External beam radiation therapy (EBRT) ($42{\sim}46\;Gy$) was delivered to the region encompassing the primary tumor and involved lymph nodes, while the supraclavicular fossa and celiac area were included in the treatment area as a function of disease location. The administered cone-down radiation dose to the gross tumor went up to $54{\sim}66\;Gy$, while the fraction size of the EBRT was 1.8-2.0 Gy/fraction qd or 1.2 Gy/fraction bid. An optional high dose rate (HDR) intraluminal brachytherapy (BT) boost was also administered (Ir-192, $9{\sim}12\;Gy/3{\sim}4\;fx$). Two cycles of concurrent FP chemotherapy (5-FU $1,000\;mg/m^2$/day, days $2{\sim}6$, $30{\sim}34$, cisplatin $60\;mg/m^2$/day, days 1, 29) were delivered during radiotherapy with the addition of two more cycles. Results: One hundred sixty patients were analyzable for this review [median follow-up time: 10 months (range $1{\sim}149$ months)). The number of patients within AJCC stages I, II, III, and IV was 5 (3.1%), 38 (23.8%), 68 (42.5%), and 49 (30.6%), respectively. A HDR intraluminal BT was performed in 26 patients. The 160 patients had a median EBRT radiation dose of 59.4 Gy (range $44.4{\sim}66$) and a total radiation dose, including BT, of 60 Gy (range $44.4{\sim}72$), while 144 patients received a dose higher than 40 Gy. Despite the treatment, the disease recurrence rate was 101/160 (63.1%). Of these, the patterns of recurrence were local in 20 patients (12.5%), persistent disease and local progression in 61 (38.1%), distant metastasis in 15 (9.4%), and concomitant local and distant failure in 5 (3.1%). The overall survival rate was 31.8% at 2 years and 14.2% at 5 years (median 11.1 months). Disease-free survival was 29.0% at 2 years and 22.7% at 5 years (median 10.4 months). The response to treatment and N-stage were significant factors affecting overall survival. In addition, total radiation dose (${\geq}50\;Gy$ vs. < 50 Gy), BT and fractionation scheme (qd. vs. bid.) were not significant factors for overall survival and disease-free survival. Conclusion: Survival outcome after definitive chemoradiation therapy in unresectable esophageal cancer was comparable to those of other series. The main failure pattern was local recurrence. Survival rate did not improve with increased radiation dose over 50 Gy or the use of brachytherapy or hyperfractionation.

• Journal of Preventive Medicine and Public Health
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• v.30 no.2 s.57
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• pp.437-461
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• 1997

Because of a significant improvement in the economic situation and development of scientific techniques in Korea during the last 30 years, the life expectancy of the Korean people has lengthened considerably and as a result, the number of the elderly has markedly increased. Such an increase of the number of aged population brought about many social, economic, and medical problems which were never seriously considered before. This study was conducted to assess the trend of medical care utilization and medical expenditure of the elderly. The data of each patient in the study were taken from computer database maintained for administrative purpose by the Korea Medical Insurance Corporation. The study population was 132,670 who were 60 years old or more and registered in Korean Medical Insurance Corporation from 1989 to 1993. The study subjects were predominantly female(56.3%) and 10,000-20,000 Won premium group(50.6%). The following are summaries of findings : The total increase of the number of inpatient cases was 40.5% from 1989 through 1993. The average annual increase was 3.7% in inpatient medical expenditures per case, 4.4% in inpatient medical expenditures per day and 0.08% in length of stay per case from 1989 through 1993. Cataract was the most prevalent disease of 10 leading frequent diseases in all ages from 1989 through 1993. The case mix in 1993 compared to 1989 revealed that cataract and ischemic cerebral disease were increased whereas essential hypertension and pulmonary tuberculosis were decreased . The average annual increase of medical expenditures was 3.8% in general hospitals, 6.3% in hospitals and 2.4% in clinics. From 1989 through 1993, medical expenditures used by high-cost patients accounted for about 14% to 20% of all expenditures for inpatient care, while they represented less than 2.5% of the elderly population. Time series analysis revealed that total medical expenditures and doctor's fee for inpatient will be progressively increased whereas drug expenditures for inpatient will be decreased. And there will be no change in length of stay. Based on the above results, the factors increasing medical cost and utilization should be identified and the method of cost containment for the elderly health care should be developed systematically.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• MISULJARYO - National Museum of Korea Art Journal
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• v.98
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• pp.176-199
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• 2020

In 2018, the National Museum of Korea purchased a pair of Japanese folding screens, respectively entitled Gathering on the Year's First "Day of the Rat" and Boating on the Oi River. Both of these two screens (hereinafter collectively referred to as the "NMK edition") have a gold background that bears the seal and ink inscription of Tosa Mitsuyoshi (1700-1772), who served as edokoro azukari, a painter in the court of Kyoto. According to the seller in New York, the screens were brought from Japan to the United States in the early twentieth century, but no other details are known. Each folding screen has six panels. The screen on the right (i.e., Gathering…) depicts "nenohi no asobi," an annual event conducted on the first "day of the rat" (according to the Asian zodiacal calendar), wherein the Kyoto imperial court ventured to the woods to gather pine seedlings. The left screen (i.e., Boating…) shows three boats traveling down the Oi River in Kyoto, representing the ritual known as "mifune" (literally, "three boats"), which involves three boats representing Chinese classical poetry (kansi), Japanese classical poetry (waka), and Japanese imperial music and dance (gagaku). Notably, these two screens are identical in theme and iconography to two screens with the same respective titles that were commissioned by Emperor Komei (1831-1867) and painted by Ukita Ikkei (1795-1859), an artist of the Yamato-e Revivalist School (fukko yamato-e), now in the collection of Sennyu-ji Temple in Kyoto (hereinafter collectively referred to as the "Sennyu edition"). While both of these themes have been painted independently numerous times, the NMK edition and Sennyu edition are the only known cases of the themes being painted as a single set. According to Diary of Official Business Between the Court and Shogunate (the journal of a court official named Hirohashi Kanetane, 1715-1781), Tosa Mitsuyoshi was commissioned in 1760 to replace the fusuma (rectangular sliding panels) of Tsunegoten, one of the buildings of the Kyoto Imperial Palace, which had been built in 1709. Notably, records show that Tsunegoten once contained a series of fusuma painted by an artist of the Kano school on the themes "Outdoor Procession on a Spring Day" and "Three Boats Cruising on the Oi River." Hence, it seems probable that Tosa Mitsuyoshi was influenced by the theme and iconography of the existing fusuma in producing his own folding screens depicting the court's visit to the forest and a cruise on the Oi River. While the practice of collecting pine seedlings on the first "rat day" of the year was an auspicious event to pray for longevity, the mifune ritual was intended to honor the greatest talents of the three aforementioned arts, which were of crucial importance to the court of Kyoto. Folding screens with such auspicious themes were commonly featured at the ceremony to enthrone the emperor or empress. Significantly, the Diary of Official Business Between the Court and Shogunate also records that Tosa Mitsuyoshi, while working as a court artist, produced two pairs of folding screens for the coronation of Empress Go Sakuramachi (1762-1771), which was held in 1763. Hence, research suggests that the NMK edition is one of the pairs of royal folding screens produced at that time.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• The Korean Journal of Petroleum Geology
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• v.8 no.1_2 s.9
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• pp.1-43
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• 2000

A comparison study for understanding a stratigraphic response to tectonic evolution of sedimentary basins in the Yellow Sea and adjacent areas was carried out by using an integrated stratigraphic technology. As an interim result, we propose a stratigraphic framework that allows temporal and spatial correlation of the sedimentary successions in the basins. This stratigraphic framework will use as a new stratigraphic paradigm for hydrocarbon exploration in the Yellow Sea and adjacent areas. Integrated stratigraphic analysis in conjunction with sequence-keyed biostratigraphy allows us to define nine stratigraphic units in the basins: Cambro-Ordovician, Carboniferous-Triassic, early to middle Jurassic, late Jurassic-early Cretaceous, late Cretaceous, Paleocene-Eocene, Oligocene, early Miocene, and middle Miocene-Pliocene. They are tectono-stratigraphic units that provide time-sliced information on basin-forming tectonics, sedimentation, and basin-modifying tectonics of sedimentary basins in the Yellow Sea and adjacent area. In the Paleozoic, the South Yellow Sea basin was initiated as a marginal sag basin in the northern margin of the South China Block. Siliciclastic and carbonate sediments were deposited in the basin, showing cyclic fashions due to relative sea-level fluctuations. During the Devonian, however, the basin was once uplifted and deformed due to the Caledonian Orogeny, which resulted in an unconformity between the Cambro-Ordovician and the Carboniferous-Triassic units. The second orogenic event, Indosinian Orogeny, occurred in the late Permian-late Triassic, when the North China block began to collide with the South China block. Collision of the North and South China blocks produced the Qinling-Dabie-Sulu-Imjin foldbelts and led to the uplift and deformation of the Paleozoic strata. Subsequent rapid subsidence of the foreland parallel to the foldbelts formed the Bohai and the West Korean Bay basins where infilled with the early to middle Jurassic molasse sediments. Also Piggyback basins locally developed along the thrust. The later intensive Yanshanian (first) Orogeny modified these foreland and Piggyback basins in the late Jurassic. The South Yellow Sea basin, however, was likely to be a continental interior sag basin during the early to middle Jurassic. The early to middle Jurassic unit in the South Yellow Sea basin is characterized by fluvial to lacustrine sandstone and shale with a thick basal quartz conglomerate that contains well-sorted and well-rounded gravels. Meanwhile, the Tan-Lu fault system underwent a sinistrai strike-slip wrench movement in the late Triassic and continued into the Jurassic and Cretaceous until the early Tertiary. In the late Jurassic, development of second- or third-order wrench faults along the Tan-Lu fault system probably initiated a series of small-scale strike-slip extensional basins. Continued sinistral movement of the Tan-Lu fault until the late Eocene caused a megashear in the South Yellow Sea basin, forming a large-scale pull-apart basin. However, the Bohai basin was uplifted and severely modified during this period. h pronounced Yanshanian Orogeny (second and third) was marked by the unconformity between the early Cretaceous and late Eocene in the Bohai basin. In the late Eocene, the Indian Plate began to collide with the Eurasian Plate, forming a megasuture zone. This orogenic event, namely the Himalayan Orogeny, was probably responsible for the change of motion of the Tan-Lu fault system from left-lateral to right-lateral. The right-lateral strike-slip movement of the Tan-Lu fault caused the tectonic inversion of the South Yellow Sea basin and the pull-apart opening of the Bohai basin. Thus, the Oligocene was the main period of sedimentation in the Bohai basin as well as severe tectonic modification of the South Yellow Sea basin. After the Oligocene, the Yellow Sea and Bohai basins have maintained thermal subsidence up to the present with short periods of marine transgressions extending into the land part of the present basins.