• Journal of Information Processing Systems
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• 제11권2호
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• pp.248-265
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• 2015

In this paper, we propose a maximum entropy-based model, which can mathematically explain the bio-molecular event extraction problem. The proposed model generates an event table, which can represent the relationship between an event trigger and its arguments. The complex sentences with distinctive event structures can be also represented by the event table. Previous approaches intuitively designed a pipeline system, which sequentially performs trigger detection and arguments recognition, and thus, did not clearly explain the relationship between identified triggers and arguments. On the other hand, the proposed model generates an event table that can represent triggers, their arguments, and their relationships. The desired events can be easily extracted from the event table. Experimental results show that the proposed model can cover 91.36% of events in the training dataset and that it can achieve a 50.44% recall in the test dataset by using the event table.

• 대한안전경영과학회지
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• 제11권4호
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• pp.221-228
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• 2009

Electronic Product Code Information Services(EPCIS) is an EPCglobal standard for sharing EPC related information between trading partners. EPCIS provides a new important capability to improve efficiency, security, and visibility in the global supply chain. EPCIS data are classified into two categories, master data (static data) and event data (dynamic data). Master data are static and constant for objects, for example, the name and code of product and the manufacturer, etc. Event data refer to things that happen dynamically with the passing of time, for example, the date of manufacture, the period and the route of circulation, the date of storage in warehouse, etc. There are four kinds of event data which are Object Event data, Aggregation Event data, Quantity Event data, and Transaction Event data. This thesis we propose an event-based data model for EPC Information Service repository in RFID based integrated logistics center. This data model can reduce the data volume and handle well all kinds of entity relationships. From the point of aspect of data quantity, we propose a formula model that can explain how many EPCIS events data are created per one business activity. Using this formula model, we can estimate the size of EPCIS events data of RFID based integrated logistics center for a one day under the assumed scenario.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4307-4325
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• 2016

With the aim of solving the problems of long processing times, high memory consumption and low event throughput in the current processing approaches in out-of-order RFID event streams, an efficient complex event processing method based on INFA-HTS (Improved Nondeterministic Finite Automaton-Hash Table Structure) is presented in this paper. The contribution of this paper lies in the fact that we use INFA and HTS to successfully realize the detection of complex events for out-of-order RFID event streams. Specifically, in our scheme, to detect the disorder of out-of-order event streams, we expand the traditional NFA model into a new INFA model to capture the related RFID primitive events from the out-of-order event stream. To high-efficiently manage the large intermediate capturing results, we use the HTS to store and process them. As a result, these problems in the existing methods can be effectively solved by our scheme. The simulation results of our experiments show that our proposed method in this paper outperforms some of the current general processing approaches used to process out-of-order RFID event streams.

• 정보처리학회논문지D
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• 제16D권5호
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• pp.691-700
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• 2009

이벤트는 환자의 증상과 같이 시간 속성을 갖는 하나의 흐름을 의미하며 인터벌 이벤트는 시작과 종료 시점에 대한 시간 간격을 갖는다. 그리고 시간 데이터마이닝에 대한 많은 연구가 있었지만 환자 이력, 구매자 이력, 로그 이력과 같은 인터벌 이벤트에 대한 지식 탐사 방법에 대한 연구는 미흡하다. 이 논문에서는 이벤트들의 인과 관계에 대한 연관 규칙을 탐사하고 이 규칙에 기반하여 결과 이벤트 발생을 예측하는 시간 데이터마이닝 방법을 제안한다. 제안 방법은 이벤트 시간 속성을 사용하여 인터벌 이벤트로 요약하고 이벤트들의 인과 관계를 탐사하여 이벤트 발생을 예측한다. 성능평가를 통하여 제안 방법은 다양한 지지도를 적용하여 발생 빈도에 상관없이 이벤트 발생에 높은 영향을 주는 의미있는 희소 관계를 발견함으로써 기존의 데이터마이닝 기법에 비하여 보다 우수한 정보를 탐사할 수 있다.

• 한국환경과학회지
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• 제29권12호
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• pp.1223-1237
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• 2020

This study focused on comparing the meteorological conditions in the Atmospheric Boundary Layer (ABL) on high-event days and non-event days in the Seoul Metropolitan Area (SMA). We utilized observed PM10 and meteorological variables at the surface as well as at the upper heights. The results showed that high-event days were consistently associated with lower wind speed, whereas wind direction showed no particular difference between high-event and non-event days with frequent westerlies and northwesterlies for both cases. During high-event days, the temperature was much warmer than the monthly normal values with a sharp increasing trend, and Relative Humidity (RH) was higher than the monthly normal, especially on high-event days in February. During high-event days in spring, a double inversion layer was present at surface and upper heights. This indicates that stability in the multi-layer is an important indicator of higher PM10 concentrations. Net radiation in spring and winter is also closely associated with higher PM10 concentrations. Strong net radiation resulted in large sensible heat, which in turn facilitated a deeper mixing height with diluted PM10 concentrations; in contrast, PM10 concentrations were higher when sensible heat in spring and winter was very low. We also confirmed that convective and friction velocity was higher on non-event days than on high-event days, and this was especially obvious in spring and winter. This indicated that thermal turbulence was dominant in spring, whereas in winter, mechanical turbulence was dominant over the SMA.

• 한국산림과학회지
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• 제99권5호
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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.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제21권12호
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• pp.751-755
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• 2015

자바스크립트 프로그램의 많은 경우가 이벤트 중심의 프로그램(event-driven program)으로, 사용자의 입력을 받아 실행하는 이벤트 함수를 매우 많이 사용한다. 따라서, 이벤트 중심의 자바스크립트 프로그램을 정적으로 분석하려면 이벤트가 어떻게 발생하고 동작하는 지를 분석할 수 있어야 한다. 본 논문에서는 자바스크립트 프로그램에서 이벤트의 발생과 동작을 정적으로 정확하게 분석하기 어려운 이유를 확인하고, 이벤트 중심 프로그램을 효과적으로 분석하기 위해 이벤트를 효율적이고 정확하게 나타낼 수 있는 이벤트 모델 기법을 제시한다.

• ETRI Journal
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• 제39권1호
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• pp.41-50
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• 2017

In connection-oriented data transport services, data loss can occur when a service experiences a problem in its end-to-end path. To resolve the problem promptly, the data transport systems providing the service must quickly modify their internal configurations, which are distributed among different locations within each system. The configurations are modified through a series of problem (event) handling procedures, which are carried out by multiple control processors in the system. This paper proposes a provisioning-to-signaling method for inter-control-processor messaging to improve the time efficiency of event processing. This method simplifies the sharing of the runtime event, and minimizes the time variability caused by the amount of event data, which results in a decrease in the latency time and an increase in the time determinacy when processing global events. The proposed method was tested for an event that required 4,000 internal path changes, and was found to lessen the latency time of global event processing by about 50% compared with the time required for general methods to do the same; in addition, it reduced the impact of the event data on the event processing time to about 30%.

• 대한안전경영과학회지
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• 제11권2호
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• pp.137-144
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• 2009

EPCIS(EPC Information Services) system is a core component of EPCglobal Architecture Framework offering information of the freights, the time of awareness and the location of awareness on the EPCglobal Network. The role of EPCIS is to exchange information based on EPC. There are four kinds of event data which are object event data, aggregation event data, quantity event data, and transaction event data. These EPCIS events data are stored and managed in EPCIS repository. This study suggest the quantitative modeling about total number of EPCIS event data under the assumption to aware the RFID tags of items, cases(boxes), vehicles(carriers, forklifts, auto guided vehicles, rolltainers) at a time on the reading points. We also estimate the number of created EPCIS event data by the suggested quantitative modeling under scenario of process in the integrated logistics center based on RFID system And this study compare the TO-BE model with the AS-IS model about the total sizes of created EPCIS event data using the simulation, in which we suggested the TO-BE model as the development of the repository by skipping the overlapped records.

• The Journal of Asian Finance, Economics and Business
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• 제7권5호
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• pp.9-18
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• 2020

The research paper examines the influence of elections on the stock market. The study analyses whether the market reaction would be the same when a party wins and comes to power for the second consecutive time. The study employs Market Model Event study methodology. The sample period taken for the study is 2014 to 2019. A sample of 31 companies listed in Bombay Stock Exchange is selected at random for the purpose of the study. For the elections held in 2014, an event window of 82 days was taken with 39 days prior to the event and 42 days post event. The event (t0) being the declaration of the election results. For the elections held in 2019 an event window of 83 days was taken with 41 days prior to the event and 41 days post event. The results indicate that the market reacts positively with significantly positive Average Abnormal Returns. The findings of the study reveal that the impact on the market is not the same between any two elections even when the same party comes to power for the second time. The semi-strong form of efficient market hypothesis holds true in the context of emerging markets like India.