• The Korean Journal of Air & Space Law and Policy
• /
• v.28 no.2
• /
• pp.223-258
• /
• 2013

1967 Outer Space Treaty(Treaty on Principles Governing the Activities of States in the Exploration and Use of Outer Space, including the Moon and Other Celestial Bodies; OST) is a treaty that forms the basis of international space law. OST is based on the 1963 Declaration of Legal Principles Governing the Activities of States in the Exploration and Use of Outer Space announced by UNGA resolution. As of May 2013, 102 countries are states parties to OST, while another 27 have signed the treaty but have not completed ratification. OST explicitly claimed that the Moon and Other Celestial Bodies are the province of all mankind. Art. II of OST states that "outer space, including the Moon and other celestial bodies, is not subject to national appropriation by claim of sovereignty, by means of use or occupation, or by any other means", thereby establishing res extra commercium in outer space like high seas. However 1979 Moon Agreement stipulates that "the moon and its natural resources are the Common Heritage of Mankind(CHM)." Because of the number of the parties to the Moon Agreement(13 parties) it does not affect OST. OST also established its specific treaties as a complementary means such as 1968 Rescue Agreement, 1972 Liability Convention, 1975 Registration Convention. OST bars states party to the treaty from placing nuclear weapons or any other weapons of mass destruction in orbit of Earth, installing them on the Moon or any other celestial body, or to otherwise station them in outer space. It exclusively limits the use of the Moon and other celestial bodies to peaceful purposes and expressly prohibits their use for testing weapons of any kind, conducting military maneuvers, or establishing military bases, installations, and fortifications. However OST does not prohibit the placement of conventional weapons in orbit. China and Russia submitted Draft Treaty on the Prevention of the Placement of Weapon in Outer Space and of the Threat or Use of Force against Outer Space Objects(PPWT) on the Conference on Disarmament in 2008. USA disregarded PPWT on the ground that there are no arms race in outer space. OST does not have some articles in relation to current problems such as space debris, mechanisms of the settlement of dispute arising from state activities in outer space in specific way. COPUOS established "UN Space Debris Mitigation Guidelines" based on "IADC Space Debris Mitigation Guidelines" and ILA proposed "International Instrument on the Protection of the Environment from Damage Caused by Space Debris" for space debris problems and Permanent Court of Arbitration(PCA) established "Optional Rules for Arbitration of Disputes Relating to Outer Space Activities" and ILA proposed "1998 Taipei Draft Convention on the Settlement of Space Law Dispute" for the settlement of dispute problems. Although OST has shortcomings in some articles, it is very meaningful in international law in considering the establishment of basic principles governing the activities of States in the exploration and use of outer space, including the Moon and Other Celestial Bodies. OST established the principles governing the activities of states in the exploration and use of outer space as customary law and jus cogens in international law as follows; the exploration and use of outer space shall be carried out for the benefit and in the interests of all countries and shall be the province of all mankind; outer space shall be free for exploration and use by all States; outer space is not subject to national appropriation by claim of sovereignty, by means of use or occupation, or by any other means. The principles of global public interest in outer space imposes international obligations erga omnes applicable to all States. This principles find significant support in legal norms dealing with following points: space activities as the "province of all mankind"; obligation to cooperate; astronauts as envoys of mankind; avoidance of harmful contamination; space activities by States, private entities and intergovernmental organisations; absolute liability for damage cauesd by certain space objects; prohibition of weapons in space and militarization of the celestial bodies; duty of openness and transparency; universal application of the international space regime.

• Tuberculosis and Respiratory Diseases
• /
• v.44 no.3
• /
• pp.479-492
• /
• 1997

Background : Isoniazid(INH) and rifampicin(RFP) are potent antituberculous drugs which have made tuberculous disease become decreasing. In Korea, prescribed doses of INH and RFP have been different from those recommended by American Thoracic Society. In fact they were determined by clinical experience rather than by scientific basis. Even there has been. few reports about pharmacokintic parameters of INH and RFP in healthy Koreans. Method : Oral pharmacokinetics of INH were studied in 22 healthy native Koreans after administration of 300 mg and 400mg of INH to each same person successively at least 2 weeks apart. After an overnight fast, subjects received medication and blood samples were drawn at scheduled times over a 24-hour period. Urine collection was also done for 24 hours. Pharmacokinetics of RFP were studied in 20 subjects in a same fashion with 450mg and 600mg of RFP. Plasma and urinary concentrations of INH and RFP were determined by high-performance liquid chromatography(HPLC). Results : Time to reach peak serum concentration (Tmax) of INH was $1.05{\pm}0.34\;hrs$ at 300mg dose and $0.98{\pm}0.59\;hrs$ at 400mg dose. Half-life was $2.49{\pm}0.88\;hrs$ and $2.80{\pm}0.75\;hrs$, respectively. They were not different significantly(p > 0.05). Peak serum concentration(Cmax) after administration of 400mg of INH was $7.14{\pm}1.95mcg/mL$ which was significantly higher than Cmax ($4.37{\pm}1.28mcg/mL$) by 300mg of INH(p < 0.01). Total clearance(CLtot) of INH at 300mg dose was $26.76{\pm}11.80mL/hr$. At 400mg dose it was $21.09{\pm}8.31mL/hr$ which was significantly lower(p < 0.01) than by 300mg dose. While renal clearance(CLr) was not different among two groups, nonrenal clearance(CLnr) at 400mg dose ($18.18{\pm}8.36mL/hr$) was significantly lower than CLnr ($23.71{\pm}11.52mL/hr$) by 300mg dose(p < 0.01). Tmax of RFP was $1.11{\pm}0.41\;hrs$ at 450mg dose and $1.15{\pm}0.43\;hrs$ at 600mg dose. Half-life was $4.20{\pm}0.73\;hrs$ and $4.95{\pm}2.25\;hrs$, respectively. They were not different significantly(p > 0.05). Cmax after administration of 600mg of RFP was $13.61{\pm}3.43mcg/mL$ which was significantly higher than Cmax($10.12{\pm}2.25mcg/mL$) by 450mg of RFP(p < 0.01). CLtot of RFP at 450mg dose was $7.60{\pm}1.34mL/hr$. At 600mg dose it was $7.05{\pm}1.20mL/hr$ which was significantly lower(p < 0.05) than by 450mg dose. While CLr was not different among two groups, CLnr at 600 mg dose($5.36{\pm}1.20mL/hr$) was significantly lower than CLnr($6.19{\pm}1.56mL/hr$) by 450mg dose(p < 0.01). Conclusion : Considering Cmax and CLnr, 300mg, of INH and 450mg RFP might be sufficient doses for the treatment of tuberculosis in Koreans. But it remains to be clarified in the patients with tuberculosis.

• Proceedings of the KOR-BRONCHOESO Conference
• /
• 1981.05a
• /
• pp.38.1-38
• /
• 1981

Currently in the otologic field, there are various methods of special audiometric examinations, such as, tone decay, SISI, and impedance audiometry and only a few studies has been done in these fields sporadically in Korea. The purpose of this paper is to establish norms of various special audiometric tests, so we have performed the special audiometric tests on 100 male medical students in good physical condition and the follow results were obtained. 1. All cases showed over 90% of PB scores. The mean and its 2 S.D. were 98$\pm$4.9% in the right ear and 97$\pm$5.6% in the left ear. 2. The mean and its 2 S.D. of MCL(most comfortable level) were 45$\pm$15.4 dB in the right ear and 46$\pm$17.9 dB in the left ear, and its range was 12$\pm$12.2 dB in the right ear and 13$\pm$12.6 dB in the left ear. 3. The mean and its 2 S.D. of UCL (uncomfortable level) were 102$\pm$7.9 dB in the right ear and 102$\pm$7.9 dB in the left ear and about an half in cases showed over 106 dB of UCL. 4. In 95% of cases, SISIs(short increment sensitivity index) at 1, 000 Hz and 4000 Hz was below 45% in the right ear in both frequencies and below 55% and 75% in the left ear, respectively. 5. In 95% of cases, tone decays at 2, 000 Hz and 4, 000 Hz was below 10 dB in both ears. 6. The difference between SRT and PTA (speech reception threshold minus pure tone average) was 4$\pm$9.2 dB in the right ear and 4$\pm$10.0 dB in the left ear. 7. The dynamic range(uncomfortable level minus speech reception threshold) was 98$\pm$13.5 dB in the right ear and 99$\pm$13.5 dB in the left ear. We had trouble in estimating the dynamic range in about an half in cases, in which we couldn't estimate the UCL with our conventional audiometry. 8. The results of impedance audiometric tests were as follow: A. In the tympanogram, all cases were of A type with one exception of B type in the left ear. The mean and its 2 S.D. of its peak level were 22.8$\pm$32.94mm $H_2O$ in the right ear and 23.9$\pm$29. 81mm $H_2O$ in the left ear. B. The mean and its 2 S.D. of the compliance were 0.6$\pm$0.54cc in the right ear and 0.6$\pm$0.53cc in the left ear. C. The results of stapedial reflex: a. The mean and its 2 S.D. of the controlateral stapedial reflex at 500Hz, 1, 000Hz, 2, 000Hz, 4, 000Hz were 99$\pm$17.7 dB, 87$\pm$14.4 dB, 79$\pm$13.7 dB, 77$\pm$20.0 dB in the right ear and 99$\pm$15.9 dB, 88$\pm$13.9 dB, 79$\pm$13.7 dB, 77$\pm$21.3 dB in the left ear. Depending on the tested frequencies, the stapedial reflex wasn't generated in 6 cases in the right ear and 11 cases in the left ear. b. The mean and its 2 S.D. of the ipsilateral stapedial reflex at 1, 000Hz, and 2, 000Hz were 89$\pm$16.3 dB, 82$\pm$15.9 dB in the right ear and 89$\pm$18.0 dB, 83$\pm$18.9 dB in the left ear. Depending on the tested frequencies, the stapedial reflex wans't generated in 1 case in the right ear and 2 cases in the left ear. 9. Eustachian tube function using with impedance audiometry was malfunctioned in21 cases depending on the tested pressure and the range of peak level of tympanogram was 14$\pm$26.9mm $H_2O$(tested pressure:+250mm $H_2O$), 8$\pm$21.9mm $H_2O$ (tested pressure:-250mm $H_2O$) in the right ear and 11 cases depending on the tested pressure and the range of the peak level of tympanogram was 12$\pm$22.5mm $H_2O$ (tested pressure: +250 mm $H_2O$, 9$\pm$17.3mm $H_2O$(tested pressure: -250mm $H_2O$) in the left ear.

• The Korean Journal of Air & Space Law and Policy
• /
• v.24 no.1
• /
• pp.59-89
• /
• 2009

The objectives of the 1963 Tokyo Convention cover a variety of subjects, with the intention of providing safety in aircraft, protection of life and property on board, and promoting the security of civil aviation. These objectives will be treated as follows: first, the unification of rules on jurisdiction; second, the question of filling the gap in jurisdiction; third, the scheme of maintaining law and order on board aircraft; fourth, the protection of persons acting in accordance with the Convention; fifth, the protection of the interests of disembarked persons; sixth, the question of hijacking of aircraft; and finally some general remarks on the objectives of the Convention. The Tokyo Convention mainly deals with general crimes such as murder, violence, robbery on board aircraft rather than aviation terrorism. The Article 11 of the Convention deals with hijacking in a simple way. As far as aviation terrorism is concerned 1970 Hague Convention and 1971 Montreal Convention cover the hijacking and sabotage respectively. The Problem of national jurisdiction over the offence and the offender was as tangled at the Hague and Montreal Convention, as under the Tokyo Convention. Under the Tokyo Convention the prime base of jurisdiction is the law of the flag (Article 3), but concurrent jurisdiction is also allowed on grounds of: territorial principle, active nationality and passive personality principle, security of the state, breach of flight rules, and exercise of jurisdiction necessary for the performance of obligations under multilateral agreements (Article 4). No Criminal jurisdiction exercised in accordance with national law is excluded [Article 3(2)]. However, Article 4 of the Hague Convention(hereafter Hague Article 4) and Article 5 of the Montreal Convention(hereafter Montreal Article 5), dealing with jurisdiction have moved a step further, inasmuch as the opening part of both paragraphs 1 and 2 of the Hague Article 4 and the Montreal Article 5 impose an obligation on all contracting states to take measures to establish jurisdiction over the offence (i.e., to ensure that their law is such that their courts will have jurisdiction to try offender in all the circumstances covered by Hague Article 4 and Montreal Article 5). The state of registration and the state where the aircraft lands with the hijacker still on board will have the most interest, and would be in the best position to prosecute him; the paragraphs 1(a) and (b) of the Hague Article 4 and paragraphs 1(b) and (c) of the Montreal Article 5 deal with it, respectively. However, paragraph 1(b) of the Hague Article 4 and paragraph 1(c) of the Montreal Article 5 do not specify if the aircraft is still under the control of the hijacker or if the hijacker has been overpowered by the aircraft commander, or if the offence has at all occurred in the airspace of the state of landing. The language of the paragraph would probably cover all these cases. The weaknesses of Hague Article 4 and Montreal Article 5 are however, patent. The Jurisdictions of the state of registration, the state of landing, the state of the lessee and the state where the offender is present, are concurrent. No priorities have been fixed despite a proposal to this effect in the Legal Committee and the Diplomatic Conference, and despite the fact that it was pointed out that the difficulty in accepting the Tokyo Convention has been the question of multiple jurisdiction, for the reason that it would be too difficult to determine the priorities. Disputes over the exercise of jurisdiction can be endemic, more so when Article 8(4) of the Hague Convention and the Montreal Convention give every state mentioned in Hague Article 4(1) and Montreal Article 5(1) the right to seek extradition of the offender. A solution to the problem should not have been given up only because it was difficult. Hague Article 4(3) and Montreal Article 5(3) provide that they do not exclude any criminal jurisdiction exercised in accordance with national law. Thus the provisions of the two Conventions create additional obligations on the state, and do not exclude those already existing under national laws. Although the two Conventions do not require a state to establish jurisdiction over, for example, hijacking or sabotage committed by its own nationals in a foreign aircraft anywhere in the world, they do not preclude any contracting state from doing so. However, it has be noted that any jurisdiction established merely under the national law would not make the offence an extraditable one under Article 8 of the Hague and Montreal Convention. As far as international aviation terrorism is concerned 1988 Montreal Protocol and 1991 Convention on Marking of Plastic Explosives for the Purpose of Detention are added. The former deals with airport terrorism and the latter plastic explosives. Compared to the other International Terrorism Conventions, the International Aviation Terrorism Conventions do not have clauses of the passive personality principle. If the International Aviation Terrorism Conventions need to be revised in the future, those clauses containing the passive personality principle have to be inserted for the suppression of the international aviation terrorism more effectively. Article 3 of the 1973 Convention on the Prevention and Punishment of Crimes Against Internationally Protected Persons, Including Diplomatic Agents, Article 5 of the 1979 International Convention against the Taking of Hostages and Article 6 of the 1988 Convention for the Suppression of Unlawful Acts Against the Safety of Maritime Navigation would be models that the revised International Aviation Terrorism Conventions could follow in the future.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.3
• /
• pp.89-98
• /
• 1965

The experimental studies were intended to clarify the effects of selection, and also aimed at estimating the heritabilities, the genotypic correlations among some agronomic characters, and at calculating the selection index on some selective characters for the selection of desirable lines, under different climatic conditions. Finally practical implications of these studies, especially on the selection index, were discussed. Twenty-two varieties, determinate growing habit type, were selected at random from the 138 soybean varieties cultivated the year before, were grown in a randomized block design with three replicates at Chinju, Korea, under May and June sowing conditions. The method of estimating heritabilities for the eleven agronomic characters-flowering date, maturity date, stem length, branch numbers per plant, stem diameter, plant weight, pod numbers per plant, grain numbers per plant and 100 grain weight, shown in Table 3, was the variance components procedures in a replicated trial for the varieties. The analysis of covariance was used to obtain the genotypic correlations and phenotypic correlations among the eight characters, and the selection indexes for some agronomic characters were calculated by Robinson's method. The results are summarized as follows: Heritabilities : The experiment on the genotype-environment interaction revealed that in almost all of the characters investigated the interaction was too large to be neglected and materially affected the estimates of various genotypic parameters. The variation in heritability due to the change of environments was larger in the characters of low heritability than in those of high heritability. Heritability values of flowering date, fruiting period (days from flowering to maturity), stem length and 100 grain weight were the highest in both environments, those of yield(grain weight) and other characters were showed the lower values(Table 3). These heritability values showed a decreasing trend with the delayed sowing in the experiments. Further, all calculated heritability values were higher than anticipated. This was expected since these values, which were the broad sense heritability, contain the variance due to dominance and epistasisf in addition to the additive genetic variance. Genotypic correlations : Genotypic correlations were slightly higher than the corresponding phenotypic correlations in both environments, but the variation in values due to the change of environment appeared between grain weight and some other characters, especially an increase between grain weight and flowering date, and the total growing period(Table 6). Genotypic correlations between grain weight and other characters indicated that high seed yield was genetically correlated with late flowering, late maturity, and the other five characters namely branch numbers per plant, stem diameter, plant weight, pod numbers per plant and grain numbers per plant, but not with 100 grain weight of soybeans. Pod numbers and grain numbers per plant were more closely correlated with seed yields than with other characters. Selection index : For the comparison and the use of selection indexes in the selection, two kinds of selection indexes were calculated, the former was called selection index A and the later selection index B as shown in Table 7. Selection index A was calculated by the values of grain weight per plant as the character of yield(character Y), but the other, selection index B, was calculated by the values of pod numbers per plant, instead of grain weight per plant, as the character of yield'(character Y'). These results suggest that selection index technique is useful in soybean breeding. In reality, however, as the selection index varies with population and environment, it must be calculated in each population to which selection is applied and in each environment in which the population is located. In spite of the expected usefulness of selection index technique in soybean breeding, unsolved problems such as the expense, time and labor involved in calculating the selection index remain. For these reasons and from these experimental studies, it was recognized that in the breeding of self-fertilized soybean plants the selection for yield should be based on a more simple selection index such as selection index B of these experiments rather than on the complex selection index such as selection index A. Furthermore, it was realized that the selection index for the selection should be calculated on the basis of the data of some 3-4 agronomic characters-maturity date(X$_1$), branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant etc. It must be noted that it should be successful in selection to select for maturity date(X$_1$) which has high heritability, and the selection index should be calculated easily on the basis of the data of branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant, directly after the harvest before drying and threshing. These characters should be very useful agronomic characters in the selection of Korean soybeans, determinate growing habit type, as they could be measured or counted easily thus saving time and expense in the duration from harvest to drying and threshing, and are affected more in soybean yields than the other agronomic characters.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.1-20
• /
• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Asia pacific journal of information systems
• /
• v.24 no.4
• /
• pp.443-472
• /
• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Journal of Intelligence and Information Systems
• /
• v.19 no.1
• /
• pp.57-77
• /
• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.

• Korean Journal of Soil Science and Fertilizer
• /
• v.40 no.5
• /
• pp.418-428
• /
• 2007

Physical and chemical properties of the aggregate by-products including sludge and crushed dust samples collected from the 21 private companies throughout the country were analyzed to evaluate possible usage of the by-products as artificial soil materials for plantation. The pH of the materials ranged from 8.0 to 11.0. The organic matter content was $2.85g\;kg^{-1}$, and the total nitrogen content and available phosphate content were low as 0.7 percents and $12.98mg\;kg^{-1}$, respectively. Exchangeable $Ca^{2+}$, $Mg^{2+}$, $K^+$, and $Na^+$ were 2.29, 0.47, 0.02 and $0.05cmol\;kg^{-1}$, respectively. Heavy metal contents were lower than the limits regulated by environmental law of Korea. Textural analysis showed that most of the materials were silt loam with low water holding capacity ranged from 0.67 to 7.41 percents, and with low hydraulic conductivity ranged from 0.4 to $2.8m\;s^{-1}$. Mineralogical analysis showed that the aggregate by product materials were mostly composed of silicate, alumina and ferric oxides except calcium oxide dominant materials derived from limestones. The primary minerals were quartz, feldspars and dolomites derived from granite and granitic gneiss materials. Some samples derived from limestone material showed calcite and graphite together with the above minerals. According to the result, it can be concluded that the materials could be used as the artificial soil material for plantation after proper improvement of the physico-chemical properties and fertility.

• Journal of Intelligence and Information Systems
• /
• v.26 no.4
• /
• pp.127-148
• /
• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.