• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2105-2112
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• 2013

In this paper we implemented a web-based performance monitoring system for web mail server. For this system we derived performance monitoring items and fixed its threshold values for each measuring items. We used the SCOM 2007 server monitoring tool for collecting the performance data of web mail server and Exchange server management pack and server monitoring rules of SCOM 2007 to set the performance analysis parameters. We implemented this performance monitoring system using C# programming based on the ASP.NET framework. This system supports web-based performance report, failure report and resource availability report from the performance analysis results. Therefore the manager can easily detect the failures of web mail server in advance and decrease the number of failure over 60%. Also this system helps manager to minimize the recovery time when the failure occurs.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.576-577
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• 2012

본 연구에서는 자동차 납축전지를 위한 지능형 배터리 센서(Intelligent Battery Sensor; IBS) 모듈 기능검사장비를 개발한다. 이를 위해 IBS 모듈에 대한 기능 및 특성평가를 위한 기능 검사 시스템을 구축하고 LABVIEW를 이용한 기능검사 프로그램을 개발한다. IBS를 이용한 감시 제어 시스템은 배터리의 상태를 모니터링하여 최적의 조건을 유지하고 문제 발생 시에 미리 조치할 수 있다. 배터리의 상태 파라미터로는 전압, 전류, 온도를 사용한다. 감시 제어 시스템은 PC를 이용하여 환경을 구축하였으며 LabView를 이용한 GUI(Graphic User Interface)를 구축하여 배터리 데이터를 모니터링하고 저장, 관리가 편리한 장점을 가진다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.56-63
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• 2009

The IEEE 802.11 standard has been used for wireless data networks such as wireless LAN, ad-hoc network, and vehicular ad-hoc network. Thus, the performance analysis of the IEEE 802.11 specification has been one of the hottest issues for network optimization and resource management. Most of the analysis studies were performed in a data plane of the IEEE 802.11 unicast. However, IEEE 802.11 broadcast is widely used for topology management, path management, and data dissemination. Thus, it is important to understand the performance of the broadcast scheme for the design of efficient wireless data network. In this contort, we analyze the IEEE 802.11 broadcast scheme in terms of the broadcast frame reception probability according to the distance from a sending node. Unlike the other works, our analysis framework includes not only the system parameters of the IEEE 802.11 specification such as transmission range, data rate, minimum contention window but also the networking environments such as the number of nodes, network load, and the radio propagation environments. Therefore, our analysis framework is expected to be used for the development of protocols and algorithms in a dynamic wireless data network.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.62-65
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• 2006

센서 네트워크는 라디오 통신으로 인해 생기는 예상치 못한 문제점을 비롯하여 제한적인 리소스 때문에 응용 개발에 어려움이 많다. 센서 네트워크가 구성된 후의 내부적인 데이터 흐름이나 네트워크에 참여하는 각 노드의 상태는 네트워크의 정보 수집을 통해 알 수 있다. 본 논문은 네트워크의 상태를 모니터링하고 실시간으로 네트워크 파라미터들을 효율적으로 설정할 수 있는 센서 네트워크 관리 시스템을 제안한다. Sensor Network Manager는 Multi-thread와 동적으로 할당 가능한 Kernel Module 기법을 지원하는 RETOS 운영체제를 기반으로 개발 되었다. 간단한 플러딩 기법을 적용하여 센서 네트워크의 상태를 모니터링 한 결과 Sensor Network Manager가 개발자에게 전반적인 네트워크에 대한 통제와 모니터링이 가능하다는 것을 검증하였다.

• Journal of the Korean Society for information Management
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• v.8 no.1
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• pp.16-32
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• 1991

This paper described the general concept of shared cataloging system and discussed the KORMARC format in the view of shared cataloging system format, including control number, copy statement, holdings statement, modifying information, transcribing MARC, character code of cataloging, nonfiling characters, delimiter codes, report number processing.

• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.51-61
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• 2017

Hadoop platform is a representative storing and managing platform for big data. Hadoop consists of distributed computing system called MapReduce and distributed file system called HDFS. It is important to analyse the effectiveness according to the change of cluster constructions and several parameters. However, since it is hard to construct thousands of clusters and analyse the constructed system, simulation method is required to analyse the system. This paper proposes Hadoop simulator based on DEVS formalism which provides hierarchical and modular modeling. Hadoop simulator provides a retargetable experimental environment that is possible to change of various parameters, algorithms and models. It is also possible to design input models reflecting the characteristics of Hadoop applications. To maximize the user's convenience, the user interface, real-time model viewer, and input scenario editor are also provided. In this paper, we validate Hadoop Simulator through the comparison with the Hadoop execution results and perform various experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.8-15
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• 2020

A forecasting method using deep learning does not have consistent results due to the differences in the characteristics of the dataset, even though they have the same forecasting models and parameters. For example, the forecasting model X optimized with dataset A would not produce the optimized result with another dataset B. The forecasting model with the characteristics of the dataset needs to be optimized to increase the accuracy of the forecasting model. Therefore, this paper proposes novel optimization steps for outlier removal, dataset classification, and a CNN-LSTM-based hyperparameter tuning process to forecast the daily power usage of a university campus based on the hourly interval. The proposing model produces high forecasting accuracy with a 2% of MAPE with a single power input variable. The proposing model can be used in EMS to suggest improved strategies to users and consequently to improve the power efficiency.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.107-119
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• 2023

The technology that recognizes a soldier's motion and movement status has recently attracted large attention as a combination of wearable technology and artificial intelligence, which is expected to upend the paradigm of troop management. The accuracy of state determination should be maintained at a high-end level to make sure of the expected vital functions both in a training situation; an evaluation and solution provision for each individual's motion, and in a combat situation; overall enhancement in managing troops. However, when input data is given as a timer series or sequence, existing feedforward networks would show overt limitations in maximizing classification performance. Since human behavior data (3-axis accelerations and 3-axis angular velocities) handled for military motion recognition requires the process of analyzing its time-dependent characteristics, this study proposes a high-performance data-driven classifier which utilizes the long-short term memory to identify the order dependence of acquired data, learning to classify eight representative military operations (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). Since the accuracy is highly dependent on a network's learning conditions and variables, manual adjustment may neither be cost-effective nor guarantee optimal results during learning. Therefore, in this study, we optimized hyperparameters using Bayesian optimization for maximized generalization performance. As a result, the final architecture could reduce the error rate by 62.56% compared to the existing network with a similar number of learnable parameters, with the final accuracy of 98.39% for various military operations.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.705-708
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• 2023

다중밀집 사고를 사전에 방지하기 위해 군중 밀집도를 정확하게 파악하는 것은 중요하다. 기존 방법 중 일부는 군중 계수를 기반으로 군중 밀집도를 추정하거나 원근 왜곡이 있는 데이터를 그대로 학습한다. 이 방식은 물체의 거리에 따라 크기가 달라지는 원근 왜곡에 큰 영향을 받는다. 본 연구는 보행자 깊이 정보를 이용한 군중 밀집도 알고리즘을 제안한다. 보행자의 깊이 정보를 계산하기 위해 편차가 적은 머리 크기를 이용한다. 머리를 탐지하기 위해 OC-Sort를 학습모델로 사용한다. 탐지된 머리의 경계박스 좌표, 실제 머리 크기, 카메라 파라미터 등을 이용하여 보행자의 깊이 정보를 추정한다. 이후 깊이 정보를 기반으로 밀도 맵을 추정한다. 제안 알고리즘은 혼잡한 환경에서 객체의 위치와 밀집도를 정확하게 분석하여 군중밀집 사고를 사전에 방지하는 지능형 CCTV시스템의 기반 기술로 활용될 수 있으며, 더불어 보안 및 교통 관리 시스템의 효율성을 향상하는 데 중요한 역할을 할 것으로 기대한다.

• Journal of IKEEE
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• v.18 no.1
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• pp.140-145
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• 2014

OPC UA(IEC62541) is a communication protocol for SG(Smart Grid) application platform. It was standardized by IEC TC57 group in December 2012. The IEC61850 has been used in Digital Substation Systems and Smart Distributed Systems. The DNP3.0 has been used for device's data collection/control in Distributed Systems. The DLMS/COSEM has been used to control metering and collect information in the Smart Metering. The top-level SG management platform needs an independent middleware to manage transparently the Power Information Technology, including the IEC61850, DNP3.0, DLMS/COSEM. In this paper, we propose the SDG(Scada Data Gateway) platform. It manages Power Information Technology based Digital Substation Systems and Smart Distributed systems, Smart Metering through OPC UA.