• Title/Summary/Keyword: event data

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A Deep Space Orbit Determination Software: Overview and Event Prediction Capability

  • Kim, Youngkwang;Park, Sang-Young;Lee, Eunji;Kim, Minsik
    • Journal of Astronomy and Space Sciences
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    • v.34 no.2
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    • pp.139-151
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    • 2017
  • This paper presents an overview of deep space orbit determination software (DSODS), as well as validation and verification results on its event prediction capabilities. DSODS was developed in the MATLAB object-oriented programming environment to support the Korea Pathfinder Lunar Orbiter (KPLO) mission. DSODS has three major capabilities: celestial event prediction for spacecraft, orbit determination with deep space network (DSN) tracking data, and DSN tracking data simulation. To achieve its functionality requirements, DSODS consists of four modules: orbit propagation (OP), event prediction (EP), data simulation (DS), and orbit determination (OD) modules. This paper explains the highest-level data flows between modules in event prediction, orbit determination, and tracking data simulation processes. Furthermore, to address the event prediction capability of DSODS, this paper introduces OP and EP modules. The role of the OP module is to handle time and coordinate system conversions, to propagate spacecraft trajectories, and to handle the ephemerides of spacecraft and celestial bodies. Currently, the OP module utilizes the General Mission Analysis Tool (GMAT) as a third-party software component for high-fidelity deep space propagation, as well as time and coordinate system conversions. The role of the EP module is to predict celestial events, including eclipses, and ground station visibilities, and this paper presents the functionality requirements of the EP module. The validation and verification results show that, for most cases, event prediction errors were less than 10 millisec when compared with flight proven mission analysis tools such as GMAT and Systems Tool Kit (STK). Thus, we conclude that DSODS is capable of predicting events for the KPLO in real mission applications.

Time-Deterministic Event Processing in Terabit Optical-Circuit-Packet Converged Switching Systems (테라비트 광-회선-패킷 통합 스위칭 시스템에서 시간결정성 높은 이벤트 처리에 관한 연구)

  • Kim, Bup-Joong;Ryoo, Jeong-dong;Cho, Kyoungrok
    • Korean Journal of Optics and Photonics
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    • v.27 no.6
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    • pp.212-217
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    • 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.

A Study on the Structures for Efficient Event Queues (효율적인 이벤트 큐의 구조에 관한 연구)

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

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XML-based Windows Event Log Forensic tool design and implementation (XML기반 Windows Event Log Forensic 도구 설계 및 구현)

  • Kim, Jongmin;Lee, DongHwi
    • Convergence Security Journal
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    • v.20 no.5
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    • pp.27-32
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    • 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.

Reliability Assessment of Railway Power System by using Tree Architecture (Tree 구조를 이용한 전철급전시스템의 신뢰도 평가)

  • Cha, Jun-Min;Ku, Bon-Hui
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.1
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    • pp.9-15
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    • 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.

A GGQS-based hybrid algorithm for inter-cloud time-critical event dissemination

  • Bae, Ihn-Han
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1259-1269
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    • 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.

Initiating Event Selection and Analysis for Probabilistic Safety Assessment of Korea Research Reactor (국내 연구용원자로 PSA 수행을 위한 초기사건 선정 및 빈도 분석)

  • Lee, Yoon-Hwan
    • Journal of the Korean Society of Safety
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    • v.36 no.2
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    • pp.101-110
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    • 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.

Epicenter Estimation Using Real-Time Event Packet of Quanterra digitizer (Quanterra 기록계의 실시간 이벤트 패킷을 이용한 진앙 추정)

  • Lim, In-Seub;Sheen, Dong-Hoon;Shin, Jin-Soo;Jung, Soon-Key
    • Geophysics and Geophysical Exploration
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    • v.12 no.4
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    • pp.316-327
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    • 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.

Lessons Learned and Challenges Encountered in Retail Sales Forecast

  • Song, Qiang
    • Industrial Engineering and Management Systems
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    • v.14 no.2
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    • pp.196-209
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    • 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.

A Method for Mining Interval Event Association Rules from a Set of Events Having Time Property (시간 속성을 갖는 이벤트 집합에서 인터벌 연관 규칙 마이닝 기법)

  • Han, Dae-Young;Kim, Dae-In;Kim, Jae-In;Na, Chol-Su;Hwang, Bu-Hyun
    • The KIPS Transactions:PartD
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    • v.16D no.2
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    • pp.185-190
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    • 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.