• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.449-458
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• 2018

As the usage of social network services increases, event information occurring offline is spreading more rapidly. Therefore, studies have been conducted to detect events by analyzing social data. In this paper, we propose a graph based event detection scheme considering user interest in social networks. The proposed scheme constructs a keyword graph by analyzing tweets posted by users. We calculates the interest measure from users' social activities and uses it to identify events by considering changes in interest. Therefore, it is possible to eliminate events that are repeatedly posted without meaning and improve the reliability of the results. We conduct various performance evaluations to demonstrate the superiority of the proposed event detection scheme.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.40.4-41
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• 2018

We introduce a coordinate catalog for photometry of the KMTNet Galactic bulge observation program and how to find the microlensing event candidates in the photometry result. Basically, the KMTNet bulge program is monitoring a total of 27 target fields (108 deg2) with four different cadences of 0.5, 1.0, 2.5, and 5.0 hours. In order to measure the stellar flux of each target, we made a 'observation coordinate catalog' by using the 'OGLE-III catalog' and 'DoPhot package'. The catalog contains approximately 0.3 billion stars in the bulge fields. We also search for a microlensing event candidates by means of the 'Event Finder algorithm' which calculates the restricted single-lens fitting (t0, teff, u0; u0 = 0 or 1) model. As a result, we found more than 2,000 microlensing event candidates per each year including about 700 events from the other survey groups such as OGLE and MOA. In this year, we will improve our current pipeline system, e.g. upgrading the catalog and applying real-time photometry.

• The Journal of Information Technology
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• v.9 no.4
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• pp.75-85
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• 2006

This study is to test the influence of stock option granting information on the firm's performance. The important issue in stock option is that agent cost is the important determinant factor for the long term performance. The agent cost arises between the manager and shareholders. So many study are concentrated in diminishing the agent cost, and develop some substitute tools to measure the agent cost. The event study about stock option analyzes returns around event date at a time. Event study provides estimation periods and cumulative returns. Announcements about stock option are generally associated with positive abnormal returns in short term period, but not showing positive effect in long term period. It is important to investigate the responses of stocks to new information contained in the announcements of stock option. Therefore it is important to study the long term performance in the case of stock option. The event time portfolio approach exists the CAR model, BHAR model and WR model. And the calendar time portfolio approach has the 3 factor model, 4 factor model, CTAR model, and RATS model. This study is forced to develop and arrange two approach method in evaluating the performance, the event time portfolio approach and calendar time portfolio approach.

• Knowledge Management Research
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• v.20 no.4
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• pp.39-55
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• 2019

Although Firms have been increasing their information security significantly to handle increased security risks, the effects of information security were not well understood. This study aims to investigate the market value of information security by employing the event study methodology. Our research also explores how market responses vary depending on the type of information security announcements. We collected 177 firm-level information security announcements between 2001 and 2017 in South Korea. For all samples, our results indicate that the stock market positively reacts to information security announcements. We also conducted subsample analysis and found that while information security certification announcement has a positive impact on the stock market, information security activities (e.g. award, information security system) announcement had no impact on the stock market. Our study adopted a novel approach (i.e. event study) for investigating the effects of information security and found that information security investment positively affects firm value. Our results allow managers to measure the effects of information security investment and help them make right decisions on information security investment.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.61.2-61.2
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• 2017

We report a fine scale transient brightening event near a pore boundary with the Fast Imaging Solar Spectrograph (FISS) of the 1.6m Goode Solar Telescope (GST), the Atmospheric Imaging Assembly (AIA) aboard the Solar Dynamics Observatory (SDO), and Helioseismic and Magnetic Imager (HMI) aboard SDO. The event appears in all AIA extreme ultraviolet bands, also in the two FISS lines, $H{\alpha}$ and Ca II $8542{\AA}$, and lasted for a minute. The brightening occurred at a footpoint of a loop. The conjugate brightening occurred at the other foot point outside the FISS field of view. The brightening near the pore exhibit a redshift of 4.3 km s-1 in the $H{\alpha}$ and about 2.3 km s-1 in Ca II line. Differential emission measure derived from 6 AIA EUV passbands and cloud model fitting of the two FISS lines indicate the temperature increase of between 10,000 and 20 MK at the main event. After the brightening, the upward mass motion appears in the AIA images. We discuss the physical implication of this brightening in the context of magnetic reconnection and coronal heating.

• Ocean Systems Engineering
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• v.8 no.1
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• pp.41-55
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• 2018

Accidental oil and gas leak is a critical concern for the offshore industry because it can lead to severe consequences and as a result, it is imperative to evaluate the probabilities of occurrence of the consequences of the leakage in order to assess the risk. Event Tree Analysis (ETA) is a technique to identify the consequences that can result from the occurrence of a hazardous event. The probability of occurrence of the consequences is evaluated by the ETA, based on the failure probabilities of the sequential events. Conventional ETA deals with events with crisp failure probabilities. In offshore applications, it is often difficult to arrive at a single probability measure due to lack of data or imprecision in data. In such a scenario, fuzzy set theory can be applied to handle imprecision and data uncertainty. This paper presents fuzzy ETA (FETA) methodology to compute the probability of the outcomes initiated due to oil/gas leak in an actual offshore-onshore installation. Post FETA, sensitivity analysis by Fuzzy Weighted Index (FWI) method is performed to find the event that has the maximum contribution to the severe sequences. It is found that events of 'ignition', spreading of fire to 'equipment' and 'other areas' are the highest contributors to the severe consequences, followed by failure of 'leak detection' and 'fire detection' and 'fire water not being effective'. It is also found that the frequency of severe consequences that are catastrophic in nature obtained by ETA is one order less than that obtained by FETA, thereby implying that in ETA, the uncertainty does not propagate through the event tree. The ranking of severe sequences based on their probability, however, are identical in both ETA and FETA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.792-793
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• 2016

Recent studies on a fusion of health care system and the information and communication technology of wearable is being developed Anytime and anywhere without being constrained to measure the biological information of the user. However existing wearable monitors the measured biological information. If the user is hard to deal with for the event of dangerous situations. In this paper, it proposes a system that identifies the status of a user to correct the problem it utilizes sensors and algorithms to measure the biological information. This enables the user will be able to respond quickly to dangerous situations. In the event of a dangerous situation, such as falling or stumbling sends an emergency alert to a designated guardian.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.41.1-41.1
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• 2018

We introduce a current status and future plans of Korea Microlensing Telescope Network (KMTNet) microlensing experiments, which include an observational strategy, pipeline, event-finder, and collaborations with Spitzer. The KMTNet experiments were initiated in 2015. From 2016, KMTNet observes 27 fields including 6 main fields and 21 subfields. In 2017, we have finished the DIA photometry for all 2016 and 2017 data. Thus, it is possible to do a real-time DIA photometry from 2018. The DIA photometric data is used for finding events from the KMTNet event-finder. The KMTNet event-finder has been improved relative to the previous version, which already found 857 events in 4 main fields of 2015. We have applied the improved version to all 2016 data. As a result, we find that 2597 events are found, and out of them, 265 are found in KMTNet-K2C9 overlapping fields. For increasing the detection efficiency of event-finder, we are working on filtering false events out by machine-learning method. In 2018, we plan to measure event detection efficiency of KMTNet by injecting fake events into the pipeline near the image level. Thanks to high-cadence observations, KMTNet found fruitful interesting events including exoplanets and brown dwarfs, which were not found by other groups. Masses of such exoplanets and brown dwarfs are measured from collaborations with Spitzer and other groups. Especially, KMTNet has been closely cooperating with Spitzer from 2015. Thus, KMTNet observes Spitzer fields. As a result, we could measure the microlens parallaxes for many events. Also, the automated KMTNet PySIS pipeline was developed before the 2017 Spitzer season and it played a very important role in selecting the Spitzer target. For the 2018 Spitzer season, we will improve the PySIS pipeline to obtain better photometric results.

• Journal of muscle and joint health
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• v.5 no.1
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• pp.7-25
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• 1998

Rheumatoid arthritis, unlike other chronic diseases, causes the patients to experience uncertainty in their daily lives and thus to feel threat on their emotional comfort because of inconsistent and unpredictable symptoms such as pain. Therefore, a theoretical framework is needed for explanation of uncertainty in patients having rheumatoid arthritis. A hypothetical model was constructed on the basis of Mishel's Uncertainty Theory and other literature review. The model included 9 theoretical concepts and 19 paths. Subjects of the study constituted 330 partients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. Self report questionnaires were used to measure the variables affecting uncertainty. Reliability coefficients of these instruments were found Cronbach's Alpha=$.70{\sim}.94$. In data analysis, SAS program and PC-LISREL 8.03 computer program were utilized for descriptive statistics and covariance structure analysis. The results of covariance structure analysis for model fitness were as follows : 1) Hypothetical model showed a good fit to the empirical data : Chi-square($X^2$)=41.81 (df=11, P=.000), Goodness of Fit Index=.974, Root Mean Square Residual=.049, Normed Fit Index=.928, Non Normed Fit Index=.814. 2) For the validity and the parcimony of model, a modified model was constructed by appending 2 paths and deleting 5 paths according to the criteria of statistical significance and meaningfulness. 3) The results of hypothesis testing were as follows : (1) Educational level, event familiarity and severity of illness had a direct effect on uncertainty : Event congruency had both direct and indirect effect on uncertainty : Credible authority and symptom consistency had a nonsignificant direct effect on uncertainty, (2) Illness duration, symptom consistency, and event congruency had a direct effect on severity of illness ; Credible authority had a both direct and indirect effect on severity of illness ; Event congruency had the greatest effect on severity of illness, and event familiarity had a nonsignificant direct effect on severity of illness.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2544-2552
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• 1997

This paper presents three multiprocess models for parallel protocol implementation, that is, (1)channel communication model, (2)fork-join model, and (3)event polling model. For the specification of parallelism for each model, a parallel programming language, Par. C System, is used. to measure the performance of multiprocess models, we implemented the Internet Protocol Suite(IPS) Internet Protocol (IP) for each model by writing the parallel language on the Transputer. After decomposing the IP functions into two parts, that is, the sending side and the receiving side, the parallelism in both sides is exploited in the form of Multiple Instruction Single Data (MISD). Three models are evaluated and compared on the basis of various run-time overheads, such as an event sending via channels in the parallel channel communication model, process creating in the fork-join model and context switching in the event polling model, at the sending side and the receiving side. The event polling model has lower processing delays as about 77% and 9% in comparison with the channel communication model and the fork-join model at the sending side, respectively. At the receiving side, the fork-join model has lower processing delays as about 55% and 107% in comparison with the channel communication model and the event polling model, respectively.