• Journal of Digital Convergence
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• v.11 no.3
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• pp.243-253
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• 2013

As global competition is more intensive, SCM is becoming more and more important in order to achieve competitiveness. It is necessary for firms to understand weak points among the integrated supply chain through supply chain assessment in order to implement SCM successfully and cost-effectively. In this paper, we review previous studies of SCM performance measurements and propose a supply chain assessment framework for shipbuilding industry, which is one of the major ETO industry. Based on 3 supply chain domains which are demand, supply, and product management, we decompose the whole supply chain process into 3 level lower processes and propose capability measurement matric for shipbuilding firms. A case study has been conducted to validate the proposed framework and results are presented at the end.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06d
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• pp.514-519
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• 2007

본 논문에서는 기존의 TCP 변종들을 바탕으로 종단간 네트워크 환경에 가장 적응이 잘 이루어진 변종의 알고리즘을 선택하는 TCP 프레임워크를 제안한다. 프로토콜 선택의 문제가 중요한 이유는 모든 네트워크 환경에 적합한 단일 버전의 프로토콜이 존재하지 않기 때문이며, 이것은 각 네트워크마다 TCP의 성능 저하 원인이 서로 다르기 때문이다. 이러한 판단 및 프로토콜의 적응이 가능하게 하기 위해 본 논문에서는 기존에 연구되어온 여러 가지 네트워크 측정 기법들과 TCP 변종들을 하나로 합치는 과정을 거쳤으며, 여기에 각 TCP들의 성능 정보들을 제공하여 세션 중간에 적절한 전송 알고리즘을 선택하여 사용할 수 있도록 하였다. 실험을 통해 우리는 end-to-end로 여러 환경 하에서 높은 성능을 이끌어낼 수 있다는 것을 보였으며, 제안한 방법이 지금까지 연구되어온 여러 TCP 변종들이 실제로 적절하게 활용될 수 있도록 하는데 중요한 역할을 할 것으로 믿는다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.396-398
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• 2023

Statista 통계 조사에 따르면 데이터의 규모는 매년 증가할 것으로 예상하고 빅데이터 처리 프레임워크의 관심이 높아지고 있다. 빅데이터 처리 프레임워크 Spark는 Shuffle 과정에서 노드 간 데이터 전송이 일어난다. 이때 분산 처리한 데이터를 네트워크로 전송하기 위해 객체를 바이트 스트림으로 변환하여 메모리 buffer에 담는 직렬화 작업이 필요하다. 그러나 바이트 스트림을 buffer에 담는 과정에서 바이트 스트림의 크기가 메모리 buffer보다 클 경우, 메모리 할당 과정이 추가로 발생하여 전체적이 Spark의 성능 저하로 이어질 수 있다. 이에 본 논문에서는 Spark 환경에서 분산 처리 성능 향상을 위한 직렬화 buffer 최적화 시스템을 제안한다. 제안하는 방법은 Spark Driver가 Executor에게 작업을 할당하기 전 직렬화된 데이터 크기 측정과 직렬화 옵션 설정을 통해 Executor에게 적절한 buffer를 할당할 수 있다. 향후 제안하는 방법의 검증을 위해 실제 Spark 클러스터 환경에서 성능 평가가 필요하다.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.71-77
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• 2015

This paper suggested dynamic application framework based data collecting and monitoring technique using wireless sensor network. The development of application for wireless measurement node firmware program integrates with various sensors and performs control. Collecting data of the user application is downloaded from the node onboard process wirelessly. In addition, the user application can change the temperature initial value of the nodes, which enables dynamic sampling of the measurement nodes. Therefore, dynamic sampling control of the nodes can reduce the power consumptions of sensors compared to existing wired data monitoring.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.121-129
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• 2009

Inspection of an Electrical Meter is an action of measuring power usage to charge electricity rates and Electricity AMR(Automatic Meter Reading) is a system to automatize the action. AMR has been highlighted because it can reduce metering cost by substituting an automatic system for personnel and strengthen customer service. In this paper, we proposed and developed a smart card based AMR framework SCEMS as an alternative to other current AMR Models. This proposed SCEMS uses a java card based multi-application smart card and supports customer service such as various meter rates according to electricity consumption pattern data per household and transaction data that are accumulated in a smart card. This research can be a solution to the problems such as diversity, heterogeneity, and complexity that environmental changes will cause soon to the power supply industry.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.134-143
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• 2010

This paper proposes a framework for classifying metric-based software quality prediction models, especially case of software criticality, into four types. Models are classified along two vectors: input metric forms and the necessity of past project data. Each type has its own characteristics and its strength and weakness are compared with those of other types using newly defined criteria. Through this qualitative evaluation each organization can choose a proper model to suit its environment. My earlier studies of criticality prediction model implemented specific models in each type and evaluated their prediction performances. In this paper I analyze the experimental results and show that the characteristics of a model type is the another key of successful model selection.

• Journal of IKEEE
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• v.18 no.1
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• pp.1-7
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• 2014

In this paper, we suggest an improved Viola-Jones detection framework for the efficient feature selection and the fast rejection method of the sub-window. Our object detector has low computational complexity because it rejects sub-windows until specific threshold. Owing to using same framework, detection performance is same with the existing Viola-Jones detector. We measure the number of average feature calculation about MIT-CMU test set. As a result of the experiment, the number of average feature calculation is reduced to 45.5% and the detection speed is improved about 58.5% compared with the previous algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.1-10
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• 2017

The functions of various systems inside the naval ships have been improved and diversified to prepare for the future battlefield and satisfy new requirements. The number of missions and operating displays with which a crew has to deal has increased. In this paper, Integrated Service Framework for Naval Ships is proposed. The proposed framework is based on REST architecture and it interfaces the networks of each systems in the ship. The connected data and functions are rebuilt as an object and they are provided as HTTP and JSON based APIs. The prototype of the framework was implemented in a combat system test-bed and its feasibility was proved with performance tests. With the proposed framework, operational efficiency for a naval ship can be achieved by designing new integrated displays and HCI which utilize whole ship's capabilities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.779-782
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• 2017

OpenBR is a framework for researching new facial recognition methods, improving existing algorithms, interacting with commercial systems, measuring perceived performance, and deploying automated biometric systems. Designed to facilitate rapid algorithm prototyping, it features a mature core framework, flexible plug-in system, and open and closed source development support. The established algorithms can be used for specific forms such as face recognition, age estimation, and gender estimation. In this paper, we describe the framework of OpenBR and implement facial recognition, gender estimation, and age estimation using supported programs.

• Annual Conference on Human and Language Technology
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• 2015.10a
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• pp.174-177
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• 2015

자가 지식 학습 프레임워크는 자연어 텍스트에서 지식 트리플을 생성하기 위한 방법 중 하나로, 문장의 의존 관계 트리 상에서 주어 개체와 목적어 개체 사이의 관계를 패턴으로 학습해 이 패턴을 바탕으로 새로운 지식 트리플을 생성한다. 그러나 이 방법은 의존 관계 트리를 생성하는 도구의 성능에 영향을 받을 뿐만 아니라 생성된 지식 트리플을 반복적으로 사용하는 자가 지식 학습의 특성상 오류가 누적될 가능성이 있다. 이러한 문제점을 해결하기 위해서 본 논문에서는 자가 지식 학습 프레임워크에서 생성된 지식 트리플을 TransR 신뢰도 함수를 사용해 신뢰도 값을 측정하여 그 값에 따라 지식 트리플을 필터링하는 방법을 제안한다. 실험 결과에 따르면 필터링 된 지식 트리플들이 그렇지 않은 지식 트리플들에 비하여 더 높은 정확률을 보여주어, 제안한 방법이 자가 지식 학습 프레임워크의 정확률 향상에 효과적임을 증명하였다.