• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.227-243
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• 2008

This study investigates an event detection method with the aim of generating an event-focused news summary from a set of news articles on a certain event using a multi-document summarization technique. The event detection method first classifies news articles into the event related topic categories by employing a SVM classifier and then creates event clusters containing news articles on an event by a modified single pass clustering algorithm. The clustering algorithm applies a time penalty function as well as cluster partitioning to enhance the clustering performance. It was found that the event detection method proposed in this study showed a satisfactory performance in terms of both the F-measure and the detection cost.

• Journal of Korean Society of Forest Science
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• v.99 no.5
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• pp.755-761
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• 2010

This study analyzed water quality data from a coniferous forest catchment in order to quantify the contributions of runoff components to stormflow, and to understand the effects of antecedent moisture conditions within catchment on the contributions of runoff components. Hydrograph separation by the twocomponent mixing model analysis was used to partition stormflow discharge into pre-event and event components for total 10 events in 2005 and 2008. To simplify the analysis, this study used single geochemical tracer with Na+. The result shows that the average contributions of event water and pre-event water were 34.8% and 65.2% of total stormflow of all 10 events, respectively. The event water contributions for each event varied from 18.8% to 47.9%. As the results of correlation analysis between event water contributions versus some storm event characteristics, 10 day antecedent rainfall and 1 day antecedent streamflow are significantly correlated with event water contributions. These results can provide insight which will contribute to understand the importance of antecedent moisture conditions in the generation of event water, and be used basic information to stormflow generation process in forest catchment.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1962-1967
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• 2008

A event recorder system stores a train speed and the related information for train operation in real time. Using those information, we can analysis the train operation and the reason of train accident. Currently the event recorder only manipulate the data related the train operation mechanically and electrically. In this paper we propose the event recorder to record the voice communication between the manager in the control center and train operator. By recording the voice communication in the high speed train, the correctness of analysis of train accident can be increased. The system architecture of the event recorder with voice recording is studied and interface between other equipment is proposed. And the software architecture of new event recorder is developed. We study the method of converting analog voice signal into digital data and compressing method. Also the architecture of memory to store the compressed voice data and regeneration of original analog voice are studied.

• Journal of the Korean School Mathematics Society
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• v.20 no.1
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• pp.19-42
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• 2017

This study analyzed characteristics of which a teacher asked questions in an instruction on the probability that event A and event B occur. The aim of this study based on the analysis was to deduce implications in terms of the various means which would enhance middle school students' understanding about the probability and assist teachers in designing instructions on the mathematics contents. To achieve this goal, this research firstly reviewed Morgan & Saxon(2006) which offers one classification of questioning that identifies a general intention for each category. Secondly, this study examined previous literature on teaching and learning the probability that event A and event B occur in order to identify didactical issues to teach the mathematics contents. Therefore, this study probed the questions of the instruction in the light of the framework descriptors from Morgan & Saxon(2006) and the issues to teach the probability that event A and event B occur. This research inspires the elaboration of what features have with regard to effective questioning in teaching mathematics through the analyzing process and additionally the elucidation of essential matters related to mathematics education on the basis of the analyzed results.

• Journal of KIISE:Information Networking
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• v.37 no.1
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• pp.8-15
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• 2010

In this study, we present an extended complex event model by considering both of the complex event and the aspect-oriented programming. We propose an advanced scheme for the event specification suited for the event correlation based network management systems by merging these two models. Specifically, we extend the model to support hierarchical event structures and let the model recognize point-cuts of aspect-oriented programming as events. We provide the event operators designed to specify the events on instances and handle temporal relations of the instances. Lastly, we compare the proposed model with other event models and present the benefits of it.

• Journal of the Korean Institute of Gas
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• v.27 no.1
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• pp.57-62
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• 2023

The Gas Regulator EVENT is a signal sent by the Remote Terminal Unit(RTU) installed in each local gas regulator (hereinafter referred to as "regulator"), and is an abnormal alarm that can be intuitively checked in our client server. This is an important data that enables immediate dispatch order and initial action in the situation room when a regolator abnormality occurs, and can analyze the cause of the regulator abnormality. Looking at the trend of EVENT data for regulator over the past three years, there is a clear trend of increasing unchecked EVENT data. The increase in non-checking event (actual abnormality or noise event) may mean that firstly, mechanical or pressure abnormality occurs in the actual regulator, and secondly, there is no abnormality in the actual regulator, but communication error occurred in the RTU, reset. EVENT Data may be formed as if an abnormality occurred in the static voltage due to an error, sensor error, power failure (instantaneous power failure), etc. Among them, this study analyzed the recently generated unchecked EVENT data to identify critical noise events among RTU errors, which are noise events, and reviewed ways to increase the reliability of Regulator EVENTs by reducing them.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.15-22
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• 2008

This study collected the latest 30-year (1976~2005) continuous rainfall data hourly recorded at 61 meterological observatories in Korea, and the continuous rainfall data was divided into individual rainfall events. In addition, distribution charts of average rainfall event-depth were created to facilitate the application to the overflow risk-based design of detention storage basin. This study shows that 4 hour is appropriate for SST (storm separation time) to separate individual rainfall events from the continuous rainfall data, and the one-parameter exponential distribution is suitable for the frequency distribution of rainfall event depths for the domestic rainfall data. The analysis of the domestic rainfall data using SST of 4 hour showed that the individual rainfall event was 1380 to 2031 times, the average rainfall event-depth was 19.1 to 32.4mm, and ranged between 0.877 and 0.926. Distribution charts of average rainfall event-depth were created for 4hour and 6 hour of SST, respectively. The inland Gyeongsangbuk-do, Western coastal area and inland of Jeollabuk-do had relatively lower average rainfall event-depth, whereas Southern coastal area, such as Namhae, Yeosu, and Jeju-do had relatively higher average rainfall event-depth.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.46.2-46.2
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• 2021

We present solar event auto detection using deep-learning-based object detection algorithms and DeepSDO event dataset. DeepSDO event dataset is a new detection dataset with bounding boxed as ground-truth for three solar event (coronal holes, sunspots and prominences) features using Solar Dynamics Observatory data. To access the reliability of DeepSDO event dataset, we compared to HEK data. We train two representative object detection models, the Single Shot MultiBox Detector (SSD) and the Faster Region-based Convolutional Neural Network (R-CNN) with DeepSDO event dataset. We compared the performance of the two models for three solar events and this study demonstrates that deep learning-based object detection can successfully detect multiple types of solar events. In addition, we provide DeepSDO event dataset for further achievements event detection in solar physics.

• Knowledge Management Research
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• v.20 no.2
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• pp.43-58
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• 2019

The main purpose of this study is to empirically investigate determinants affecting MICE quality, which then affects to loyalty. In particular, this study focuses on variables in the exhibition and event experiences of the MICE participants. The proposed research includes four variables representing the exhibitions and event experiences (affective, intellectual, behavioral, relational experience), two MICE qualities (commitment, satisfaction), and MICE loyalty. The results of this study reveal that four proposed variables (affective, intellectual, behavioral and relational experience) have a positive impact on two MICE qualities (commitment and satisfaction). Furthermore, the study found that commitment and satisfaction positively influence MICE loyalty. The findings of the study would provide theoretical and practical implications of exhibition and event experiences, quality and loyalty of MICE.

• Asia Marketing Journal
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• v.16 no.1
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• pp.21-33
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• 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.