• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.36-43
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• 2005

RFID(Radio Frequency IDentification: 라디오 주파수 인식)란 라디오 주파수를 활용해서 무선으로 사물을 인식하는 것을 의미한다. RFID 기술을 구성하는 기본 요소는 태그, 안테나, 리더 등이다. 본 연구에서는 이러한 RFID 기술의 기본 요소와 더불어 인식된 사물의 정보를 광범위하게 구축되어 있는 유${\cdot}$무선 네트워크와 연결하여 활용할 수 있는 모든 기술을 RFID 기술로 정의하였다. 비록 최근에 RFID 기술이 여러 분야에서 큰 이슈로 떠오르고 있지만, 실제 RFID 기술은 오래전인 2차 세계대전에 영국군의 자국 전투기 식별을 위해 이미 활용되고 있었다. 그러나 그 당시에는 RFID 기술의 구성요소인 태그나 리더의 값이 고가였기 때문에 특정분야에 한해 RFID 기술을 적용할 수 있었다. 그 이후에 1990년대에 이르러 RFID 기술은 가축관리, 컨테이너관리, IC 카드 등 점차 다른 분야로 적용이 확대되기 시작했다. 특히 반도체 기술의 발전이 급속도로 이루어진 1990년대 말을 기점으로 RFID 기술에 대한 연구가 활발히 이루어져, 현재에는 SCM(Supply Chain Management), 국방, 의료, 교통, 환경, 동물관리, 홈 네트워크 등 다양한 분야에 적용이 가능한 기술로 평가되고 있다. 특히, SCM에 있어서 RFID 기술 도입은 큰 파급효과가 예상되고 있다. SCM을 구성하는 기업들은 RFID 기술 도입을 통해 제품의 가시성(visibility)과 추적성(traceability)을 확보할 수 있게 된다. 기업들은 자신의 제품이 현재 어디에 있으며 어떠한 경로를 통해 그 자리에 이르렀는지를 실시간(real time)으로 확인 가능하게 된다. 미국의 월마트사(社) 와 영국의 메트로사(社) 같은 선진 유통 기업들은 실증연구를 통해 RFID 기술 도입이 비용 절감과 함께 고객 서비스 향상을 도모할 것이라는 결론을 내린 바 있다. 또한 현제 초기단계이기는 하지만 실제 RFID 기술을 도입하여 운영 중에 있다. 국내에서도 정부주도 하에 RFID 기술에 대한 연구가 활발하게 이루어지고 있으며, 지난 2004년에 유통 물류 분야의 1차 시범사업을 완료하였다. 그러나, 이러한 국내${\cdot}$외의 적극적인 도입 움직임에도 불구하고 국내에서는 아직 RFID기술 도입이 SCM(Supply Chain Management)에 있어서 구체적으로 어떠한 영향을 미치는가에 대한 연구가 거의 이루어지지 못하고 있는 실정이다. 특히 RFID 기술 도입 의사결정자에게 제공될 수 있는 정량적인 ROI 분석 모형에 관한 연구는 시급한 과제로 떠오르고 있다. 따라서 본 연구에서는 SCM 차원에서 RFID 기술 도입에 따른 ROI 분석 모형을 제시하고 적용해 보고자 한다.

• Korean Journal of Construction Engineering and Management
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• v.5 no.1 s.17
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• pp.88-98
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• 2004

In recent, Information Technology(IT) is the biggest issue on the social whole including the construction industry. IT is recognized as a key strategic means to reinforce competitive power and raise the effectiveness. However, CEOs of each firm have trouble with IT investment decision-making. Because there is neither any case to measure real value of IT nor any confidence to economic effect of information system. IT evaluation is so helpful for most construction firms to make a plan of IT investment. In addition, which will eventually facilitate to achieve their management goal and have the maximum of the firms' value. Therefore, the purpose of this research is to develop IT evaluation system for monitoring IT level continually. And this will be enable a construction company to increase IT investment and improve the level of IT in the construction industry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.267-274
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• 2018

This paper introduces a smart door system composed of security system and secretary system. As ratio of single households increase, the security of household became more important. Also already there were a lot of artificial intelligence secretary system based on voice called smart home technology. But It has limits. It can not work without user's requests. That mean it is not automatic. And the voice recognition depend on user's pronounce. Thus in this paper, we design and develop smart door system that is added function of security and secretary. That can inform users that there are outsider in front of their house in real time. Also that can speak information such as user's requirements, delivery and weather information using TTS. As a result they can prevent crimes and use convenient secretary system.

• Journal of IKEEE
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• v.14 no.3
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• pp.224-231
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• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.1-7
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• 2013

Big data management is becoming increasingly important in both industry and academia of information science community. One of the important categories of big data generated from software systems is log data. Log data is generally used for better services in various service providers and can also be used as information for qualification. This paper presents a big data management architecture specialized for log data. Specifically, it provides the aggregation of log messages sent from multiple clients and provides intelligent functionalities such as analyzing log data. The proposed architecture supports an asynchronous process in client-server architectures to prevent the potential bottleneck of accessing data. Accordingly, it does not affect the client performance although using remote data store. We implement the proposed architecture and show that it works well for processing big log data. All components are implemented based on open source software and the developed prototypes are now publicly available.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.281-292
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• 2004

As the logistic environment of digital contents is rapidly changing, the protection of the digital rights for digital content has been recognized as one of critical Issues. Digital Right Management(DRM) has taken much interest Internet Service Provider(ISP), authors and publishers of digital content as an interested approach to create a trusted environment for access and use of digital resources. This paper propose an interested digital rights protection scheme using license agent to address problems facing contemporary DRM approached : static digital rights management, and limited application to on-line environment. We introduce a dynamic mission control technology to realize dynamic digital rights management. And we incorporate license agent to on- and off-line monitoring and tracking. The proposed system prevent illegal access and use by using PKI security method, real time action monitoring for user, data security for itself.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12B
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• pp.805-810
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• 2005

According to the user requirements for continuous and real-time multimedia information, the concept of Quality of Service (QoS) has emerged as a main issue in mobile ad-hoc networks. QoS routing is to find the route that meets the QoS requirements of the users. In this paper, we propose a routing protocol that is based on AODV over TDMA, one of the typical routing protocols for mobile ad-hoc networks, by making a bandwidth reservation for QoS guarantee. While the existing schemes calculate the maximum available bandwidth for each candidate path, our scheme is to check only if the bandwidth of a given path satisfies the end-to-end QoS requirement and then to make a reservation by allocating time slots efficiently in the wireless environment. In order to evaluate the performance of the proposed QoS routing protocol, some simulations are carried out in the ad-hoc environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10B
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• pp.883-890
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• 2006

The study of sensor network database is beginning to liven up as we are interested in Ubiquitous Computing technology in hardware, communication, database and so on. Especially, as new smart sensors have capabilities of real-time information gathering and analysis of each sensor node, data processing becomes an important issue in Ubiquitous Computing. In thesis, we have applied TinyDB(query processing system) to carry sensor node with line tracer which can follow the fixed path. After we gathered data around path, we have processed data in TinyDB GUI, gathered data, displayed data on a web server. Also we have a web browser on an embedded board for convenient user interface and implemented touch screen such that users can operate with a finger.

• Journal of Internet Computing and Services
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• v.8 no.2
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• pp.43-54
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• 2007

The effective power consumption is the primary issue in a sensor network which consists of the sensor nodes with limited battery power. So, most of the MAC protocols in sensor networks have been designed with the consideration of energy efficiency. Generally, these protocols make use of the listen and sleep mode periodically. However, this approach inevitably causes a long transmission delay on the data forwarding path, which is mainly resulted from the sleep time of the receiver node. This paper deals with a design of DT-MAC(Data Transmission centric MAC) protocol, with minimizes the data transmission delay while it forces each node to consume its energy efficiently. Thus, a node received a packet converts its remained sleep time to the pseudo_listen time, in which the node is able to transmit a packet. With benefit of the pseudo_listen period, the data transmission delay along with the data forwarding path will be shortened as much as it possible. Therefore, DT-MAC protocol is very suitable to the various applications which require a real time sensing data such as disaster and fire alarm.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.136-141
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a neural-network-based drowsiness detection system using Linear Predictive Coding (LPC) coefficients as feature vectors and Multi-Layer Perceptron (MLP) as a classifier. Samples of EEG data from each predefined state were used to train the MLP program by using the proposed feature extraction algorithms. The trained MLP program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.