• Title/Summary/Keyword: exchange of information

Search Result 3,560, Processing Time 0.028 seconds

An Approach of Scalable SHIF Ontology Reasoning using Spark Framework (Spark 프레임워크를 적용한 대용량 SHIF 온톨로지 추론 기법)

  • Kim, Je-Min;Park, Young-Tack
    • Journal of KIISE
    • /
    • v.42 no.10
    • /
    • pp.1195-1206
    • /
    • 2015
  • For the management of a knowledge system, systems that automatically infer and manage scalable knowledge are required. Most of these systems use ontologies in order to exchange knowledge between machines and infer new knowledge. Therefore, approaches are needed that infer new knowledge for scalable ontology. In this paper, we propose an approach to perform rule based reasoning for scalable SHIF ontologies in a spark framework which works similarly to MapReduce in distributed memories on a cluster. For performing efficient reasoning in distributed memories, we focus on three areas. First, we define a data structure for splitting scalable ontology triples into small sets according to each reasoning rule and loading these triple sets in distributed memories. Second, a rule execution order and iteration conditions based on dependencies and correlations among the SHIF rules are defined. Finally, we explain the operations that are adapted to execute the rules, and these operations are based on reasoning algorithms. In order to evaluate the suggested methods in this paper, we perform an experiment with WebPie, which is a representative ontology reasoner based on a cluster using the LUBM set, which is formal data used to evaluate ontology inference and search speed. Consequently, the proposed approach shows that the throughput is improved by 28,400% (157k/sec) from WebPie(553/sec) with LUBM.

Policy Suggestions to Improve PSS(Presidential Security Service) Education Programs for Industry-Academy-Governmental Cooperations (${\cdot}$${\cdot}$관 협력강화를 위한 대통령경호실 교육프로그램 확대 방안)

  • Cho, Kwang-Rae
    • Korean Security Journal
    • /
    • no.11
    • /
    • pp.227-243
    • /
    • 2006
  • In modern society, private securities have developed their capabilities continuously. However, despite the fact that not only security industries have been considerably expanded in quantity, but also plenty of scholars published diverse papers relating to security problems, qualitative growths of private securities have not accomplished fully. Especially, securing the President would not be guaranteed only by PSS(Presidential Security Service). In order to secure the President successfully, it is necessary for all the social parts to strive to protect the President. In this respect, improving private securities, including academic fields, might be critical so as to succeed in securing the President. Without the supports from private securities, there might be lots of security problems in national context. Therefore, this study proposes several policy suggestions for the cooperation among PSS, private security industries and academic fields: (1) Providing a lot of practical knowledge from PSS to college students, (2) Personnel exchange between academic parts and PSS to promote the efficiency of securing the President, (3) Furnishing diverse information and knowledge about security to private securities, (4) Formulating security-searching standards, (5) Expanding educational institutions under PSS.

  • PDF

Parallel Range Query processing on R-tree with Graphics Processing Units (GPU를 이용한 R-tree에서의 범위 질의의 병렬 처리)

  • Yu, Bo-Seon;Kim, Hyun-Duk;Choi, Won-Ik;Kwon, Dong-Seop
    • Journal of Korea Multimedia Society
    • /
    • v.14 no.5
    • /
    • pp.669-680
    • /
    • 2011
  • R-trees are widely used in various areas such as geographical information systems, CAD systems and spatial databases in order to efficiently index multi-dimensional data. As data sets used in these areas grow in size and complexity, however, range query operations on R-tree are needed to be further faster to meet the area-specific constraints. To address this problem, there have been various research efforts to develop strategies for acceleration query processing on R-tree by using the buffer mechanism or parallelizing the query processing on R-tree through multiple disks and processors. As a part of the strategies, approaches which parallelize query processing on R-tree through Graphics Processor Units(GPUs) have been explored. The use of GPUs may guarantee improved performances resulting from faster calculations and reduced disk accesses but may cause additional overhead costs caused by high memory access latencies and low data exchange rate between GPUs and the CPU. In this paper, to address the overhead problems and to adapt GPUs efficiently, we propose a novel approach which uses a GPU as a buffer to parallelize query processing on R-tree. The use of buffer algorithm can give improved performance by reducing the number of disk access and maximizing coalesced memory access resulting in minimizing GPU memory access latencies. Through the extensive performance studies, we observed that the proposed approach achieved up to 5 times higher query performance than the original CPU-based R-trees.

SNS Effect of the negative event on the Firm Performance: Comparison between Pre and Post SNS media appearance

  • Kim, Sang Yong;Lee, Da Eun
    • Asia Marketing Journal
    • /
    • v.16 no.1
    • /
    • pp.21-33
    • /
    • 2014
  • When the negative event is published, the company tends to go through the negative impact on the firm performance. Especially, with the SNS, the negative event is instantly spread on indefinite region so the impact seems bigger than the period before the SNS media appearance. It seems that everyone considers the SNS media impact on the firm performance quite big. However, there has been no empirical study on the impact comparison on the firm performance between pre and post SNS media occurrence periods. This study tries to empirically compare the impact of the negative event on the firm performance between pre and post SNS media appearance. Our study starts fromthe basic but not verified question; Does really the negative event have more negative impact in the post-SNS-occurrence period than in the pre-SNS-occurrence period? In order to examine the impact of the negative publicity on firm performance in two eras, pre and post SNS media appearance, we used CAR (Cumulative Abnormal Resturns) model. By using this model, we could verify the statistical significance of cumulative abnormal returns in market between before and after the events. For event samples, we focused on food manufacturers and collected the negative events from 1991 to 2003 for pre-SNS occurrence period, and from 2010 to 2013 for post-SNS occurrence period. Based on the listed food companies at KOSPI, we researched Naver News Library (newslibrary.naver.com) and Naver News (news.naver.com) for all the individual negative events published for both periods. Firm returns data were collected from TS 2000 (KOCO Info) and market portfolio data were collected from KRX Exchange. Through our empirical analysis, our finding is interesting to note that the type of events differently influences on the firm performance. With the SNS, the health-related events have influence on the firm performance 'after the event day' whereas the company behavior trust events have influence 'before the event day'. Our findings have implications for management. When a negative event directly related to or threatening customers or their life such as health, it is crucial to fix up the situation right after the event occurs. On the other hand, when a negative event is not publicly available information such as company behavior trust, it is important for marketers to strengthen the firms' trust reputation and control the bad WOM before the event.

  • PDF

A Study on the Collaborative Partnership Factors between Freight Forwarders and Consignors (국제물류주선업체와 화주기업의 협력적 파트너쉽 요인에 관한 연구)

  • Jun, Kyung Sook;Jang, Hyun Mi;Kim, Sang Youl
    • Journal of Korea Port Economic Association
    • /
    • v.30 no.4
    • /
    • pp.169-198
    • /
    • 2014
  • Due to the recent worldwide economic downturn, companies are required to put more effort into their innovation and quality improvement. In particular, business relationship is increasingly emphasized to be changed from a vertical relationship to a more horizontal relationship, such as collaborative partnership based on trust. In the logistics industry, through the collaboration, consignors can gain competitive advantages by focusing on their core capabilities, and freight forwarders also take advantages of securing stable cargoes and specialist expertise in distribution. Therefore, this study aims to identify key factors for developing a collaborative partnership between freight forwarders and consignors, and further examine the differences between the two groups empirically by using questionnaire survey. Based on the results, the main factors were found as follows: 1) Trust Building, 2) Competence Improvement, 3) Business Ecosystem and 4) Government Assistance. According to the analysis on sub-factors, first, among the four main factors, it turned out that trust is the most important variable. Specifically, the sub-factor of providing regular and stable service was revealed to be most critical. Second, it was found that forwarders need to improve services on 'Information Exchange System' and 'Electronic Data Interchange'. Finally, it is necessary for both consignors and forwarders to have better understanding of partnership. Key implications for both groups are highlighted based on the results.

eMRA: Extension of MRA Considering the Relationships Between MDR Concepts (eMRA: MDR의 개념간 관계성을 고려한 MRA 확장)

  • Joo, Young-Min;Kim, Jangwon;Jeong, Dongwon;Baik, Doo-Kwon
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.2 no.3
    • /
    • pp.161-172
    • /
    • 2013
  • Metadata registry (MDR) is the international standard, developed by ISO/IEC for exchange and sharing data between databases. Many MDR systems are used in diverse domains such as medical service, bibliography, environment for sharing and integrating data. However, those systems have different physical structures individually because the MDR standard defines only the metamodel for registering and storing metadata. It causes heterogeneity between the system structures and requires additional cost to maintain interoperability. ISO/IEC 13249-8 Metadata Registry Access (MRA) is developing as an international standard to provide a consistent access facility to data stored in different metadata registries. However, MRA does not consider the relationships between the concepts (classes) defined in the MDR specification. It causes that incorrect query results returned from MDR systems. It also requires additional cost of modeling and rewriting queries to reflect each physical model. Therefore, this paper suggests eMRA which considers the relationships between the concepts in MDR. The comparative evaluations are described to show the advantages of eMRA. eMRA has superior performance in query modeling and referential integrity than MRA defined by the relationship between the concept of MDR.

The Analysis of the Current Status of Medical Accidents and Disputes Researched in the Korean Web Sites (인터넷 사이트를 통해 살펴본 의료사고 및 의료분쟁의 현황에 관한 분석)

  • Cha, Yu-Rim;Kwon, Jeong-Seung;Choi, Jong-Hoon;Kim, Chong-Youl
    • Journal of Oral Medicine and Pain
    • /
    • v.31 no.4
    • /
    • pp.297-316
    • /
    • 2006
  • The increasing tendency of medical disputes is one of the remarkable social phenomena. Especially we must not overlook the phenomenon that production and circulation of information related to medical accidents is increasing rapidly through the internet. In this research, we evaluated the web sites which provide the information related to medical accidents using the keyword "medical accidents" in March 2006, and classified the 28 web sites according to the kinds of establishers. We also analyzed the contents of the sites, and checked and compared the current status of the web sites and problems that have to be improved. Finally, we suggested the possible solutions to prevent medical accidents. The detailed results were listed below. 1. Medical practitioners, general public, and lawyers were all familiar with and prefer the term "medical accidents" mainly. 2. In the number of sites searched by the keyword "medical accidents", lawyer had the most sites and medical practitioners had the least ones. 3. Many sites by general public and lawyers had their own medical record analysts but there was little professional analysts for dentistry. 4. General public were more interested in the prevention of medical accidents but the lawyers were more interested in the process after medical accidents. The sites by medical practitioners dealt with the least remedies of medical accidents, compared with other sites. 5. General public wanted the third party such as government intervention into the disputes including the medical dispute arbitration law or/and the establishment of independent medical dispute judgment institution. 6. In the comparison among the establishers of web sites, medical practitioners dealt with the least examples of medical accidents. 7. The suggestion of cases in counseling articles related to dental accidents were considered less importantly than the reality. 8. Whereas there were many articles about domestic cases related to the bloody dental treatment, in the open counseling articles the number of dental treatment regarding to non insurance treatment was large. 9. In comparing offered information of medical accidents based on the establishers, general public offered vocabularies, lawyers offered related laws and medical practitioners offered medical knowledge relatively. 10. They all cited the news pressed by the media to offer the current status of domestic medical accidents. Especially among the web sites by general public, NGOs provided the plentiful statistical data related to medical accidents. 11. The web sites that collect the medical accidents were only two. As a result of our research, we found out that, in the flood of information, medical disputes can be occurred by the wrong information from third party, and the medical practitioners have the most passive attitudes on the medical accidents. Thus, it is crucial to have the mutual interchange and exchange of information between lawyer, patients and medical practitioners, so that based on clear mutual comprehension we can solve the accidents and disputes more positively and actively.

VKOSPI Forecasting and Option Trading Application Using SVM (SVM을 이용한 VKOSPI 일 중 변화 예측과 실제 옵션 매매에의 적용)

  • Ra, Yun Seon;Choi, Heung Sik;Kim, Sun Woong
    • Journal of Intelligence and Information Systems
    • /
    • v.22 no.4
    • /
    • pp.177-192
    • /
    • 2016
  • Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

An Analysis of Growth Conditions of old Trees in Yangdong Villages (양동마을의 노거수 생육실태 분석)

  • Kim, Young-Hun;Deng, Bei-Jia;You, Ju-Han
    • Journal of the Korean Institute of Traditional Landscape Architecture
    • /
    • v.38 no.2
    • /
    • pp.95-107
    • /
    • 2020
  • The purpose of this study is to provide the basic data by analyzing and analysing the Growth Conditions of old Trees in Yangdong village. This study investigated about the conducted on tree information, soil information, and tree health. The result are as follows. The trees information in Yangdong Village consists of Juniperus chinensis, Salix chaenomeloides, Salix pseudolasiogyne, Celtis sinensis, Zelkova serrata, Gleditsia japonica, and Gleditsia sinensis trees, The range of height was 4.0~17.0m, and the diameter was 0.51~1.34m, Juniperus chinensis trees of No.17 was most large. In the results of soil analysis, there showed that acidity was pH4.1~6.3, hardness of 5~48mm, organic matter content of 21.2~29.1g/kg, electrical conductivity(EC) of 0.34~1.76dS/m, available P2O5 of 79.8~451.6mg/kg, exchangeable K of 0.22~1.71cmol+/kg, exchangeable Ca of 4.98~7.44cmol+/kg, exchangeable Mg of 0.67~2.19cmol+/kg, exchangeable Na of 0.19~1.04cmol+/kg and cation exchange capacity(C.E.C) of 7.23~13.02cmol+/kg. As a result, the highest number of tree health levels is 8 of 11trees of Celtis sinensis, 2 of 7trees of Zelkova serrata, and 3 of Gleditsia sinensis, and 13 of 30 trees of health levels, The Older trees with high infection, spoil and hollowed part were the remaining trees except for the healthy part. Relatively, more than half of the number of targets is infected, decay, and the hollowed site, and it is necessary to perform surgery on the damaged area. In addition, preservation and protection measures should be implemented by supplying root nutrients for trees, controlling nutrients in the body to prevent secondary and tertiary damages that cause the infection site to metastasize to the health site, In order to continually monitor the trees, measures to improve the location environment and management of the trees should be sought.

The Gains To Bidding Firms' Stock Returns From Merger (기업합병의 성과에 영향을 주는 요인에 대한 실증적 연구)

  • Kim, Yong-Kap
    • Management & Information Systems Review
    • /
    • v.23
    • /
    • pp.41-74
    • /
    • 2007
  • In Korea, corporate merger activities were activated since 1980, and nowadays(particuarly since 1986) the changes in domestic and international economic circumstances have made corporate managers have strong interests in merger. Korea and America have different business environments and it is easily conceivable that there exists many differences in motives, methods, and effects of mergers between the two countries. According to recent studies on takeover bids in America, takeover bids have information effects, tax implications, and co-insurance effects, and the form of payment(cash versus securities), the relative size of target and bidder, the leverage effect, Tobin's q, number of bidders(single versus multiple bidder), the time period (before 1968, 1968-1980, 1981 and later), and the target firm reaction (hostile versus friendly) are important determinants of the magnitude of takeover gains and their distribution between targets and bidders at the announcement of takeover bids. This study examines the theory of takeover bids, the status quo and problems of merger in Korea, and then investigates how the announcement of merger are reflected in common stock returns of bidding firms, finally explores empirically the factors influencing abnormal returns of bidding firms' stock price. The hypotheses of this study are as follows ; Shareholders of bidding firms benefit from mergers. And common stock returns of bidding firms at the announcement of takeover bids, shows significant differences according to the condition of the ratio of target size relative to bidding firm, whether the target being a member of the conglomerate to which bidding firm belongs, whether the target being a listed company, the time period(before 1986, 1986, and later), the number of bidding firm's stock in exchange for a stock of the target, whether the merger being a horizontal and vertical merger or a conglomerate merger, and the ratios of debt to equity capital of target and bidding firm. The data analyzed in this study were drawn from public announcements of proposals to acquire a target firm by means of merger. The sample contains all bidding firms which were listed in the stock market and also engaged in successful mergers in the period 1980 through 1992 for which there are daily stock returns. A merger bid was considered successful if it resulted in a completed merger and the target firm disappeared as a separate entity. The final sample contains 113 acquiring firms. The research hypotheses examined in this study are tested by applying an event-type methodology similar to that described in Dodd and Warner. The ordinary-least-squares coefficients of the market-model regression were estimated over the period t=-135 to t=-16 relative to the date of the proposal's initial announcement, t=0. Daily abnormal common stock returns were calculated for each firm i over the interval t=-15 to t=+15. A daily average abnormal return(AR) for each day t was computed. Average cumulative abnormal returns($CART_{T_1,T_2}$) were also derived by summing the $AR_t's$ over various intervals. The expected values of $AR_t$ and $CART_{T_1,T_2}$ are zero in the absence of abnormal performance. The test statistics of $AR_t$ and $CAR_{T_1,T_2}$ are based on the average standardized abnormal return($ASAR_t$) and the average standardized cumulative abnormal return ($ASCAR_{T_1,T_2}$), respectively. Assuming that the individual abnormal returns are normal and independent across t and across securities, the statistics $Z_t$ and $Z_{T_1,T_2}$ which follow a unit-normal distribution(Dodd and Warner), are used to test the hypotheses that the average standardized abnormal returns and the average cumulative standardized abnormal returns equal zero.

  • PDF