• Korean Journal of Optics and Photonics
• /
• v.27 no.6
• /
• pp.212-217
• /
• 2016

In connection-oriented data-transport services, data loss can occur when the service experiences a problem on its end-to-end path. To promptly resolve this problem, the data-switching systems providing the service should quickly modify their internal configurations distributed among different places in each system. This is performed through a sequence of problem (event) recognition, sharing, and handling procedures among multiple control processors in the system. This paper proposes a method for event sharing and messaging between control processors, to improve the time determinacy of event processing. This method simplifies runtime event sharing and minimizes the time variability caused by the event data, resulting in a decrease in the latency time in processing global events. The proposed method lessens the latency time of global event processing by about 40%, compared to general methods, for 738 internal path changes.

• Journal of the Korea Society for Simulation
• /
• v.4 no.2
• /
• pp.61-68
• /
• 1995

The performance of event-driven logic simulation frequently used for VLSI design verification depends on the data structures for event queues. This paper improves the existing Timing Wheel as a data structure for an event queue. In case of the use of B+ tree, an efficient node degree is also presented based on the experiment results. A new Timing Wheel index structure, which eliminates the insertion and deletion overhead of B+ tree, is proposed and analyzed.

• Convergence Security Journal
• /
• v.20 no.5
• /
• pp.27-32
• /
• 2020

The Windows Event Log is a Log that defines the overall behavior of the system, and these files contain data that can detect various user behaviors and signs of anomalies. However, since the Event Log is generated for each action, it takes a considerable amount of time to analyze the log. Therefore, in this study, we designed and implemented an XML-based Event Log analysis tool based on the main Event Log list of "Spotting the Adversary with Windows Event Log Monitoring" presented at the NSA.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.1
• /
• pp.9-15
• /
• 2010

As catenary supply electric power directly to the railway system, it is very important to prevent an accident of a catenary for appropriate train operation. This paper proposed the assessment the outage data for "British Catenary Safety Analysis Report" and Korean data to compare the reliability of the railway system. The analyzed data were applied to Event Tree and Fault Tree algorithm to calculate the reliability indices of railway system. Event tree is created and gate results of fault tree analysis are used as the source of event tree probabilities. Fault tree represents the interaction of failures and basic events within a system. Event Tree and Fault Tree analysis result is helpful to assess the reliability to interpreted. The reliability indices can be used to determine the equipment to be replaced for the entire system reliability improvement.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.6
• /
• pp.1259-1269
• /
• 2012

Cloud computing has rapidly become a new infrastructure for organizations to reduce their capital cost in IT investment and to develop planetary-scale distributed applications. One of the fundamental challenges in geographically distributed clouds is to provide efficient algorithms for supporting inter-cloud data management and dissemination. In this paper, we propose a geographic group quorum system (GGQS)-based hybrid algorithm for improving the interoperability of inter-cloud in time-critical event dissemination service, such as computing policy updating, message sharing, event notification and so forth. The proposed algorithm first organizes these distributed clouds into a geographic group quorum overlay to support a constant event dissemination latency. Then it uses a hybrid protocol that combines geographic group-based broad-cast with quorum-based multicast. Our numerical results show that the GGQS-based hybrid algorithm improves the efficiency as compared with Chord-based, Plume an GQS-based algorithms.

• Journal of the Korean Society of Safety
• /
• v.36 no.2
• /
• pp.101-110
• /
• 2021

This paper presents the results of an initiating event analysis as part of a Level 1 probabilistic safety assessment (PSA) for at-power internal events for the Korea Research Reactor (KRR). The PSA methodology is widely used to quantitatively assess the safety of research reactors (RRs) in the domestic nuclear industry. Initiating event frequencies are required to conduct a PSA, and they considerably affect the PSA results. Because there is no domestic database for domestic trip events, the safety of RRs is usually assessed using foreign databases. In this paper, operating experience data from the KRR for trip events were collected and analyzed in order to determine the frequency of specific initiating events. These frequencies were calculated using two approaches according to the event characteristics and data availability: (1) based on KRR operating experience or (2) using generic data.

• Industrial Engineering and Management Systems
• /
• v.14 no.2
• /
• pp.196-209
• /
• 2015

Retail sales forecast is a special area of forecasting. Its unique characteristics call for unique data models and treatment, and unique forecasting processes. In this paper, we will address lessons learned and challenges encountered in retail sales forecast from a practical and technical perspective. In particular, starting with the data models of retail sales data, we proceed to address issues existing in estimating and processing each component in the data model. We will discuss how to estimate the multi-seasonal cycles in retail sales data, and the limitations of the existing methodologies. In addition, we will talk about the distinction between business events and forecast events, the methodologies used in event detection and event effect estimation, and the difficulties in compound event detection and effect estimation. For each of the issues and challenges, we will present our solution strategy. Some of the solution strategies can be generalized and could be helpful in solving similar forecast problems in different areas.

• Geophysics and Geophysical Exploration
• /
• v.12 no.4
• /
• pp.316-327
• /
• 2009

A standard for national seismological observatory was proposed on 1999. Since then, Quanterra digitizer has been installed and is operating on almost all of seismic stations which belong to major seismic monitoring organizations. Quanterra digitizer produce and transmit real-time event packet and data packet. Characteristics of event packet and arrival time of each channel's data packet on data center were investigated. Packet selection criteria using signal to noise ratio (hereafter SNR) and signal period from real-time event packet based on 100 samples per second (hereafter sps) velocity data were developed. Estimation of epicenter using time information of the selected event packet were performed and tested. A series of experiment show that event packets were received approximately 3~4 second earlier than data packets and the number of event packet was only 0.3% compare to data packets. Just about 5% against all of event packets were selected as event packet were related P wave of real earthquake. Using the selected event packets we can estimate an epicenter with misfit less than 10 km within 20 sec for local earthquake over magnitude 2.5.

• The KIPS Transactions:PartD
• /
• v.16D no.2
• /
• pp.185-190
• /
• 2009

The event sequence of the same type from a set of events having time property can be summarized in one event. But if the event sequence having an interval, It is reasonable to be summarized more than one in independent sub event sequence of each other. In this paper, we suggest a method of temporal data mining that summarizes the interval events based on Allen's interval algebra and finds out interval event association rule from interval events. It provides better knowledge than others by using concept of an independent sub sequence and finding interval event association rules.

• The KIPS Transactions:PartD
• /
• v.18D no.4
• /
• pp.215-224
• /
• 2011

U-Health collects patient information with various kinds of sensor. Stream data can be summarized as an interval event which has aninterval between start-time-point and end-time-point. Most of temporal mining techniques consider only the event occurrence-time-point and ignore stream data change of state. In this paper, we propose the temporal mining technique considering the event change of state in U-Health. Our method overcomes the restrictions of the environment by sending a significant event in U-Health from sensors to a server. We define four event states of stream data and perform the temporal data mining considered the event change of state. Finally, we can remove an ambiguity of discovered rules by describing cause-and-effect relations among events in temporal relation sequences.