• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.35-44
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• 2004

Web contents created for desktop screens give rise to problems when they are to be displayed on the small screens of mobile terminals. While in some cases some of the objects of a page may not be displayable due to the lack of browser capability, the entire page may not be displayable due to the incompatibility with the browser in other cases. In this paper, we introduce a new mobile content adaptation approach based on web clipping, which transforms an original page into one that is optimally displayed on a mobile terminal. In this method, a source page is automatically clipped and transformed according to the clip specification made by the content provider using a clip editing tool. The clip editing tool allows the user to specify group clips, multi-level cups and dynamic clips as well as simple clips, and the presentation layout through a graphic user interface. Based on the clip specifications, each clip is transformed into an intermediate meta-language document, which in turn is transformed into a presentation page in the target markup language. Transcoding of image objects in major image file formats is also supported.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.11-23
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• 2011

The objective of this paper is to develop a daily pattern clustering algorithm using historical traffic data that can reliably detect under various traffic flow conditions in urban streets. The developed algorithm in this paper is categorized into two major parts, that is to say a macroscopic and a microscopic points of view. First of all, a macroscopic analysis process deduces a daily peak/non-peak hour and emphasis analysis time zones based on the speed time-series. A microscopic analysis process clusters a daily pattern compared with a similarity between individuals or between individual and group. The name of the developed algorithm in microscopic analysis process is called "Two-step speed clustering (TSC) algorithm". TSC algorithm improves the accuracy of a daily pattern clustering based on the time-series speed variation data. The experiments of the algorithm have been conducted with point detector data, installed at a Ansan city, and verified through comparison with a clustering techniques using SPSS. Our efforts in this study are expected to contribute to developing pattern-based information processing, operations management of daily recurrent congestion, improvement of daily signal optimization based on TOD plans.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1119-1127
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• 2012

The one of features of M2M communications, which are recently attracted attention as a future business of mobile communications, is that there is a large number of devices compared with traditional communication services. Hence, the control signal that are generated by the M2M devices may cause a significant congestion in the network and in order to solve this problem, a standardization is progressing for reducing the redundant signaling by managing M2M devices as a group in 3GPP standardization. In this paper, we propose a method of group based mobility management by managing M2M devices that have the same mobility as a group. In the proposed method, M2M devices that have the same mobility are grouped by the Mobility Management Entity (MME) and the MME elects a group header among the M2M devices in the group. Then, the group header performs the Tracking Area Update (TAU) on behalf of the group members to reduce the signaling overhead of mobility management. With the proposed method, we can achieve 80% decrease of the signaling overhead of mobility management compared with the case where each M2M device individually performs its TAU procedure.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.178-183
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• 1997

차세대 원전 경보시스템에서의 경보처리는 발전소의 과도상태 및 비정상운전시 경보필터링, 경보억제, 발전소 상태에 근거한 우선순위처리 등을 적용하여 운전원에게 경보정보를 효율적으로 처리하고자 한다. 경보표시 측면에서는 인간공학 및 인지공학적 요소를 적용하여 운전원의 인적오류를 최소화하여 기존 경보계통의 단점을 개선하고자 하였다. 본 논문에서는 차세대 경보계통설계의 구현을 위해서 COAST(Computerized Alarm System Toolbox)를 사용하여 경보처리방법 중 그룹핑기법을 구현하였다.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.713-723
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• 2017

Since the panoramic image can overcome the limitation of the viewing angle of the camera and have a wide field of view, it has been studied effectively in the fields of computer vision and stereo camera. In order to generate a panoramic image, stitching images taken by a plurality of general cameras instead of using a wide-angle camera, which is distorted, is widely used because it can reduce image distortion. The image stitching technique creates descriptors of feature points extracted from multiple images, compares the similarities of feature points, and links them together into one image. Each feature point has several hundreds of dimensions of information, and data processing time increases as more images are stitched. In particular, when a panorama is generated on the basis of an image photographed by a plurality of unspecified cameras with respect to an object, the extraction processing time of the overlapping feature points for similar images becomes longer. In this paper, we propose a preprocessing process to efficiently process stitching based on an image obtained from a number of unspecified cameras for one object or environment. In this way, the data processing time can be reduced by pre-grouping images based on camera sensor information and reducing the number of images to be stitched at one time. Later, stitching is done hierarchically to create one large panorama. Through the grouping preprocessing proposed in this paper, we confirmed that the stitching time for a large number of images is greatly reduced by experimental results.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.233-238
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• 2020

In the cloud environment, IoT devices using sensors and wearable devices are being applied in various environments, and technologies that accurately determine the information generated by IoT devices are being actively studied. However, due to limitations in the IoT environment such as power and security, information generated by IoT devices is very weak, so financial damage and human casualties are increasing. To accurately collect and analyze IoT information, this paper proposes a topographic information-based key management technique that considers IoT information errors. The proposed technique allows IoT layout errors and groups topographic information into groups of dogs in order to secure connectivity of IoT devices in the event of arbitrary deployment of IoT devices in the cloud environment. In particular, each grouped terrain information is assigned random selected keys from the entire key pool, and the key of the terrain information contained in the IoT information and the probability-high key values are secured with the connectivity of the IoT device. In particular, the proposed technique can reduce information errors about IoT devices because the key of IoT terrain information is extracted by seed using probabilistic deep learning.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.209-210
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• 2010

오래된 영상에는 여러 가지 물리적 요인에 의하여 스크래치가 발생하고 이 스크래치는 화질의 열화를 야기한다. 이러한 스크래치는 다양한 길이, 다양한 너비로 발생하므로, 이를 반영하기 위하여 본 논문에서는 스크래치를 리지로 간주하고 scale space에서 리지를 검출한다. 검출된 리지는 영상의 화질이 좋지 않아 조각난 채로 검출되므로 본 논문에서는 검출된 리지를 수직 방향으로 그룹핑하여 최종적으로 스크래치를 검출한다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.487-494
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• 2004

Resizing techniques have been recognized as practical methods for drift design of high-rise building since sensitivity analysis and iterative structural analysis are not required in implementation. In the techniques, the amount of material of a memberin a building for resizing is determined in terms of cross-sectional areas and sectional inertia moments as design variables. In this study, five drift design methods are developed by considering design variable linking strategy and fomulating resizing algorithm in terms of material properties of shear walls as a design variable. The developed methods are applied to the drift design of 20-story frame-RC shear wall structure, and then evaluated in the view points of practicality and efficiency.

• The KIPS Transactions:PartC
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• v.8C no.2
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• pp.164-172
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• 2001

최근 인터넷의 확산과 더불어 디지털 비디오 라이브러리(DVL : Digital Video Library) 서비스에 대한 관심이 고조되고 있다. 그러나 현재의 통신망 대역폭과 스위칭 환경 하에서는 종단간 QoS 보장하는데 많은 제약사항이 존재한다. 따라서 본 논문에서는 비디오 스트림 처리를 효율적으로 수행하여, 지연-처리율 특성을 만족할 수 있는 스트림 스위칭 구조를 제안하고 이에 대한 성능을 분석하였다. 제안된 ATM-기반 스트림 스위치는 각각 다중화되는 CBR(Constant Bit Rate) 및 VBR(Variable Bit Rate) 스트림의 QoS(Quality of Service)를 보장해야만 한다. 성능분석 결과는 제안된 스위치의 처리율이 r=4일 때 약 0.996의 값을 보였으며, 지연시간도 부하가 0.7 이하일 때 2미만으로 특정되었다. 이 결과는 제안된 구조가 적당한 입력 스트림의 그룹핑을 통하여 비디오 응용을 위한 처리율 및 지연 요구사항 QoS를 보장할 수 있음을 보여준다.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.69-87
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• 2006

This paper proposes an effective approach for the part-machine grouping(PMG) based on the non-binary part-machine incidence matrix in which real manufacturing factors such as the operation sequences with multiple visits to the same machine and production volumes of parts are incorporated and each entry represents actual moves due to different operation sequences. The proposed approach adopts Fuzzy ART neural network to quickly create the Initial part families and their machine cells. A new performance measure to evaluate and compare the goodness of non-binary block diagonal solution is suggested. To enhance the poor solution due to category proliferation inherent to most artificial neural networks, a supplementary procedure reassigning parts and machines is added. To show effectiveness of the proposed approach to large-size PMG problems, a psuedo-replicated clustering procedure is designed. Experimental results with intermediate to large-size data sets show effectiveness of the proposed approach.