• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.106-116
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• 2010

Sensor deployment makes an effect on not only covering of the interesting area but also reliable data acquisition and efficient resource management of sensor, so that sensors must be deployed at their better place. In traditional static wireless sensor networks, however, it is impossible to deploy the sensors manually when they are distributed in unexploited, hostile, or disaster areas. Therefore, if each sensor has locomotion capability, it can re-deploy itself using the location information of neighbor sensors. In our previous study, we showed that moving sensors to the centroids of their Voronoi polygon is efficient for extending the coverage area. In this paper, we present an improved potential-field-based sensor self-deployment scheme by combining the centroid of Voronoi polygon with the traditional potential-field scheme. Simulation results show that our scheme can achieve higher coverage in shorter time and less movement than the traditional potential-field scheme.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.266-272
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• 2021

Water friendly space refers to a place designated to plan and manage spaces for residents Water friendly activities. Efficient management of river Water friendly parks requires automated GIS data and DB construction of the water friendly facilities. Object-based classification using drone images or aerial images is attracting attention as an efficient means to acquire 3D spatial information in the country. To remove the miscellaneous image included in the extracted outline, a linear simplification of the outline is required, and it is difficult to apply manually, so various automation methods have been developed to overcome this, and among them, the most widely studied and utilized is the linear simplification method. In this study, the suitability of linear simplification algorithms such as Douglas-Peucker, Visvalingam-Whyatt, and Bend-simplify algorithms for the geometric shape of hydrophilic facilities was determined.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.33-54
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.3
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• pp.393-401
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• 2015

In the construction of a TBM tunnel, it is very important to acquire accurate information of the excavated rock mass for an efficient and safe work. In this study, we developed the prediction system of TBM tunnel face ahead using probe drilling equipment and drilled hole imaging equipment to predict rock mass conditions of the tunnel face ahead. The prediction system consists of the probe drilling equipment, drilled hole imaging equipment and analysis software. The probe drilling equipment has been developed to be applicable to both non-coring and coring. Also the probe drilling equipment can obtain the drilling parameters such as feed pressure, torque pressure, rotation speed, drilling speed and so on. The drilling index is converted to the drilling index RMR through the correlation between a drilling index and core RMR. The developed system verification was carried out through a slope and tunnel field application. From the field application result, the non-coring is four times faster than a coring and the drilling index RMR and core RMR are similar in the distribution range. This system is expected to predict the rock mass conditions of the TBM tunnel face ahead very quickly and efficiently.

• Journal of the Korean Geophysical Society
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• v.6 no.3
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• pp.155-164
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• 2003

The validity and efficiency of the roll-along technique widely used in 2-D electrical resistivity survey are analyzed in case of the dipole-dipole and the Wenner-Schlumberger arrays by numerical modelling. The shallow anomalous resistivity bodies are successfully inverted both in the dipole-dipole and in the Wenner-Schlumberger arrays because the shallow data of pseudosection are not omitted by the roll-along technique. However, the deep anomalous resistivity bodies can not be well resolved due to the skip of observed data which is more significant in the Wenner-Schlumberger array having relatively poor horizontal coverage of obtaining data. Carrying out electrical survey adopting the dipole-dipole array, the skip of data is insignificant because it is unfeasible to expand the electrodes to the maximum electrode separation coefficient($n_max$) owing to low S/N ratio. In case of the Wenner-Schlumberger array, however, because it is generally feasible to expand the electrodes $n_max$ to the owing to high S/N ratio, it is highly possible that skip of data from the roll-along technique causes significant distortion of inversion results. Therefore, adopting the Wenner-Schlumberger array having deeper median depth(Edwards, 1977) than do the dipole-dipole array on condition of the same unit electrode spacing( ($a$) ) and $n_max$, it is recommended to determine $a$ based on not $n_max$but $n_prob$free from the skip of observing data and forward electrodes with keeping overlap interval 3/4 of the survey line length in order to reduce the distortion of resistivity structure and perform resistivity survey efficiently. These results are confirmed by numerical modelling.

• Journal of Korean Classical Literature and Education
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• no.34
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• pp.75-113
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• 2017

The purpose of fusion education is to acquire educational contents efficiently and gain a new worldview. To realize this purpose, I point out that it is urgent to provide common educational content and suggest "place experience" as common content for literature and geography. Local legends present a concrete space and a sharp confrontation with the human world, while shaping the tradition of a place's name. Place experience as common educational content enables a three-dimensional experience of a place that utilizes the characteristics of these local legends. The physical condition, human activity, and implied meaning of a place mediate the student's empirical understanding of folktales. The common area of "place experience" allows us to expect a stereotypical understanding of a learner's place by providing a literary context to learning contents that can flow from the existing geography subject to the simple provision of information. In addition, it facilitates learners' empirical understanding by providing actual and specific objects to learning contents, which can flow abstractly in the existing literature subject. Through this discussion, convergence education demonstrates educational significance by achieving educational efficiency through common educational content and enabling the formation of new thinking.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.765-771
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• 2019

Noise in skull X-ray imaging is inevitable, which reduces imaging quality and diagnostic accuracy and increases errors due to the nature of digital imaging devices. Increasing the dose can attenuate noise, but that could lead to big problems with higher exposure dose received by patients. Thus, noise reduction algorithms are actively being studied at low doses to solve dose problems and reduce noise at the same time. Wiener filter and median filter have been widely used, with the disadvantages of poor noise reduction efficiency and loss of much information about imaging boundary. The purpose of this study is to apply total variation (TV) algorithm to skull X-ray imaging that can compensate for the problems of previous noise reduction efficiency to assess quantitatively and compare them. For this study, skull X-ray imaging is obtained using various kVp and mAs using the skull phantom using the X-ray device of Siemens. In addition, contrast to noise ratio (CNR) and coefficient of variation (COV) are compared and measured when noisy image, median filter, Wiener filter and TV algorithm were applied to each phantom imaging. Experiments showed that when TV algorithms were applied, CNR and COV characteristics were excellent under all conditions. In conclusion, we've been able to see if we can use TV algorithm to improve image quality and CNR could be seen to increase due to the decrease in noise as the amount of increased mAs. On the other hand, COV decreased as the amount of increased mAs, and when kVp increased, noise was reduced and the transmittance was increased, so COV was reduced.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.171-183
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• 1995

이 논문은 특정 기기산업의 기술적 구조와 현황의 분석 및 파악을 위한 제 품.기술 관련도라는 새로운 개념을 제시한다. 제품.기술 관련도란 분석대상산 업의 주요 제품들을 도출하고 각각의 제품에 관련된 기술들을 부품기술을 중심으로 파악하여 매트릭스의 형태로 도시한 것을 의미한다. 제품. 기술 관 련도상의 제품에 대해서는 전문가의 의견에 의해 측정된 기술수준과 주된 획득방법(국산화율)을 파악한다. 한편, 제품에 관련되는 기술은 기본적인 기능을 발휘하는 제품의 생산에 소요되는 기본기술과 제품의 성능향상을 위하여 필요한 성능관련기술 등으로 구분하여 분석된다. 이러한 제품.기술 관련도는 국내 기기산업의 각 분야별 기술수준, 부품군의 기술수준 등을 도출하고 상호관련성을 파악하는데 유용한 방법으로 활용될수 있다. 특히 제품군과 부품군간의 관계 도출, 기술수준 혹은 구산화율이 낮은 제품에 관련된 부품 및 기술의 파악, 국내의 기술수준이 낮은 부품에 관련되는 제품 및 제품군, 제품의 성능이 향상에 관련된 기술등의 파악이 용이하다. 본 논문에서는 제품.기술 관련도를 한국의 정보통신기기산업에 시험적으로 적용하여 정보통신 기기분야의 제품 및 기술 구조, 그리고 경쟁력을 분석하여 보았다. 국내 정보통신기기산업의 전체적인 기술수준은 자체적으로 기술을 보유하고 있으나 성능면에서 매우 미약한 소화 및 모방 단계의 수준이라고 해석할수 있다. 한편 부품기술은 아직도 소화및 모방단계에 머무르고 있으며, 개별소자와 수동부품의 기술수준이 매우 낮게 나타났다. 분야별로 볼 때 무선통신기기, 방송기기, 정보기기의 순으로 기술수준이 낮으며, 무선통신기기분야이 발전을 위해서는 고주파 부품의 기술 발전이 선행되어야 할것으로 보인다.라 제시된 외주위탁 전략과 현재의 외주위 탁 전략이 일치할 때 정보 시스템에 대한 사용자 만족도가 보다 높은 것으 로 나타났다. 할 수 있는 효율적인 distributed system를 개발하는 것을 제시하였다. 본 논문은 데이타베이스론의 입장에서 아직 정립되어 있지 않은 분산 환경하에서의 관계형 데이타베이스의 데이타관리의 분류체계를 나름대로 정립하였다는데 그 의의가 있다. 또한 이것의 응용은 현재 분산데이타베이스 구축에 있어 나타나는 기술적인 문제점들을 어느정도 보완할 수 있다는 점에서 그 중요성이 있다.ence of a small(IxEpc),hot(Tex> SOK) core which contains two tempegatlue peaks at -15" east and north of MDS. The column density of HCaN is (1-3):n1014cm-2. Column density at distant position from MD5 is larger than that in the (:entral region. We have deduced that this hot-core has a mass of 10sR1 which i:s about an order of magnitude larger those obtained by previous studies.previous studies.업순서들의 상관관계를 고려하여 보다 개선된 해를 구하기 위한 연구가 요구된다. 또한, 준비작업비용을 발생시키는 작업장의 작업순서결정에 대해서도 연구를 행하여, 보완작업비용과 준비비용을 고려한 GMMAL 작업순서문제를 해결하기 위한 연구가 수행되어야 할 것이다.로 이루어 져야 할 것이다.태를 보다 효율

• Journal of Animal Environmental Science
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• v.8 no.3
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• pp.199-208
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• 2002

This paper introduces the method to make management network about milking cow farm tasks. The object of this research was to design of biological measuring system and managing network system in a livestock farm. This auto-management system provides informations about individual cows' temperature, conductivity of milk and weight for efficient management of feeding, and milking works by a micro-processor and RS -485 type serial COM. ports. And measured bio-data which are basic informations for remote raising management are saved to user PC by serial communication between the PLC and user PC. Milking cow farm is divided into three working place to each measurement work and feed. The first working place is milking station which has two thermometers, a conduct meter and a scale set. The second working place is feeding station, and the third place is cattle cage. These are combined by network system and the PLC which is used to drive network and sub-modules. Sub-modules have a micro-process to control the sensor and to interface with network. The PLC which drive network and control sequence has two serial communication port to be linked with user PC for sending the measured data and for receiving data. Above all, in this study tells the sequence operating method by the driving scenario of breeding milk cow for livestock auto-management using the PLC and network system.

• Information Systems Review
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• v.7 no.2
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• pp.23-40
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• 2005

Discovering customers' behavioral patterns from large data set and providing them with corresponding services or products are critical components in managing a current business. However, the diversity of customer needs coupled with the limited resources suggests that companies should make more efforts on understanding and managing specific groups of customers, not the whole customers. The key issue of this paper is based on the fact that the behavioral patterns extracted from the specific groups of customers shall be different from those from the whole customers. This paper proposes the idea of pre-segmentation before developing customer classification models. We collected three customers' demographic and transactional data sets from a credit card, a tele-communication, and an insurance company in Korea, and then segmented customers by major variables. Different churn prediction models were developed from each segments and the whole data set, respectively, using the decision tree induction approach, and compared in terms of the hit ratio and the simplicity of generated rules.