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Density Aware Energy Efficient Clustering Protocol for Normally Distributed Sensor Networks

  • Su, Xin;Choi, Dong-Min;Moh, Sang-Man;Chung, Il-Yong
    • Journal of Korea Multimedia Society
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    • v.13 no.6
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    • pp.911-923
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    • 2010
  • In wireless sensor networks (WSNs), cluster based data routing protocols have the advantages of reducing energy consumption and link maintenance cost. Unfortunately, most of clustering protocols have been designed for uniformly distributed sensor networks. However, some urgent situations do not allow thousands of sensor nodes being deployed uniformly. For example, air vehicles or balloons may take the responsibility for deploying sensor nodes hence leading a normally distributed topology. In order to improve energy efficiency in such sensor networks, in this paper, we propose a new cluster formation algorithm named DAEEC (Density Aware Energy-Efficient Clustering). In this algorithm, we define two kinds of clusters: Low Density (LD) clusters and High Density (HD) clusters. They are determined by the number of nodes participated in one cluster. During the data routing period, the HD clusters help the neighbor LD clusters to forward the sensed data to the central base station. Thus, DAEEC can distribute the energy dissipation evenly among all sensor nodes by considering the deployment density to improve network lifetime and average energy savings. Moreover, because the HD clusters are densely deployed they can work in a manner of our former algorithm EEVAR (Energy Efficient Variable Area Routing Protocol) to save energy. According to the performance analysis result, DAEEC outperforms the conventional data routing schemes in terms of energy consumption and network lifetime.

STUDY ON 3-D VIRTUAL REALITY FOR STEREOSCOPIC VISUALIZATION ON THE WEB (웹 환경에서의 입체적 가시화를 위한 3-D 가상현실 기법의 적용)

  • Lee, J.H.;Park, Y.C.;Kim, J.H.;Kim, B.S.
    • Journal of computational fluids engineering
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    • v.16 no.1
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    • pp.30-35
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    • 2011
  • In this paper, our effort to apply 3-D Virtual Reality system for stereoscopic visualization of mesh data on the web is briefly described. This study is an extension of our previous and on-going research efforts to develop an automatic grid generation program specialized for wing mesh, named as eGWing. The program is developed by using JAVA programming language, and it can be used either as an application program on a local computer or as an applet in the network environment. In this research advancing layer method(ALM) augmented by elliptic smoothing method is used for the structured grid generation. And to achieve a stereoscopic viewing capability, two graphic windows are used to render its own viewing image for the left and right eye respectively. These two windows are merged into one image using 3D monitor and the viewers can see the mesh data visualization results with stereoscopic depth effects by using polarizing glasses. In this paper three dimensional mesh data visualization with stereoscopic technique combined with 3D monitor is demonstrated, and the current achievement would be a good start-up for further development of low-cost high-quality stereoscopic mesh data visualization system which can be shared by many users through the web.

Generation and Protection of Efficient Watermark Signals and Image Quality Preservation in Transmission Channel Using Turbo Coding (효과적인 워터마크 신호의 생성과 보호 및 터보코딩을 이용한 전송채널상에서의 화질 보존)

  • Cho, Dong-Uk;Bae, Young-Lae
    • The KIPS Transactions:PartB
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    • v.9B no.1
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    • pp.91-98
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    • 2002
  • In this paper, an implementation method of the efficient image transmission stage using watermarking and channel ceding is proposed. Usually, image communication system consists of both a transmitter part and a receiver part. The transmitter part takes charge of copyright protection of the generated image data, and image coding and compression that can deal with channel noises when transmitting. In the transmitter part, we propose a channel coding method which protects both the watermark signal and the original signal for protecting the copyright of image data and solving channel noises when transmitting. Firstly, copyright protection of image data is conducted. For this, image structure analysis is performed, and both the improvement of image quality and the generation of the watermark signal are made. Then, the histogram is constructed and the watermark signals are selected from this. At this stage, by embedding of the coefficients of curve fittness into the lower 4 bits of the image data pixels, image quality degradation due to the embedding of watermark signals are prevented. Finally, turbo coding, which has the most efficient error correction capability in error correction codes, has been conducted to protect signals of watermark and preserved original image quality against noises on the transmission channel. Particularly, a new interleaving method named "semi random inter]easer" has been proposed.

Role of the Observation Planning in Three-dimensional Environment for Autonomous Reconstruction

  • Moon, Jung-Hyun;You, Bum-Jae;Kim, Hag-Bae;Oh, Sang-Rok
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.37-42
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    • 2005
  • This paper presents an autonomous system for reconstruction of three-dimensional indoor environments using a mobile robot. The system is composed of a mobile robot, a three-dimensional scanning system, and a notebook computer for registration, observation planning and real-time three-dimensional data transferring. Three-dimensional scanning system obtains three-dimensional environmental data and performs filtering of dynamic objects. Then, it registers multiple three-dimensional scans into one coordinate system and performs observation planning which finds the next scanning position by using the layered hexahedral-map and topological-map. Then, the mobile robot moves to the next scanning position, and repeats all procedures until there is no scanning tree in topological-map. In concurrence with data scanning, three-dimensional data can be transferred through wireless-LAN in real-time. This system is experimented successfully by using a mobile robot named KARA.

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Vulnerable Path Attack and its Detection

  • She, Chuyu;Wen, Wushao;Ye, Quanqi;Zheng, Kesong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.4
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    • pp.2149-2170
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    • 2017
  • Application-layer Distributed Denial-of-Service (DDoS) attack is one of the leading security problems in the Internet. In recent years, the attack strategies of application-layer DDoS have rapidly developed. This paper introduces a new attack strategy named Path Vulnerabilities-Based (PVB) attack. In this attack strategy, an attacker first analyzes the contents of web pages and subsequently measures the actual response time of each webpage to build a web-resource-weighted-directed graph. The attacker uses a Top M Longest Path algorithm to find M DDoS vulnerable paths that consume considerable resources when sequentially accessing the pages following any of those paths. A detection mechanism for such attack is also proposed and discussed. A finite-state machine is used to model the dynamical processes for the state of the user's session and monitor the PVB attacks. Numerical results based on real-traffic simulations reveal the efficiency of the attack strategy and the detection mechanism.

Open set Object Detection combining Multi-branch Tree and ASSL (다중 분기 트리와 ASSL을 결합한 오픈 셋 물체 검출)

  • Shin, Dong-Kyun;Ahmed, Minhaz Uddin;Kim, JinWoo;Rhee, Phill-Kyu
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.5
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    • pp.171-177
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    • 2018
  • Recently there are many image datasets which has variety of data class and point to extract general features. But in order to this variety data class and point, deep learning model trained this dataset has not good performance in heterogeneous data feature local area. In this paper, we propose the structure which use sub-category and openset object detection methods to train more robust model, named multi-branch tree using ASSL. By using this structure, we can have more robust object detection deep learning model in heterogeneous data feature environment.

Magneto-Optical Recording in Near-Field using Elliptic Solid Immersion Lens (타원형 고체잠입렌즈를 이용한 근접장 광자기 기록)

  • 박재혁;이문도;박노철;박영필
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.678-681
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    • 2003
  • In conventional optical data storage numerical aperture (NA) cannot be over 1 because of diffraction limit. To overcome this limitation. solid immersion lens(SIL) have produced a great interest in near-field optical data storage. In conventional optical recording method, the dual lens system using object lens and SIL had been studied generally. But the conventional SIL system has some critical problems that must be solved. The problems are heat, contamination. alignment of optical components and so on. To solve these problems. this work proposes enhanced SIL which has several advantages for mechanical and optical issues. This new SIL system named elliptic SIL(ESIL) can use evanescent energy in near-field more effectively. In addition. because of applying the inside recording unlike previous surface recording, ESIL can clear up the problems. The design and analysis of ESIL art executed by using CODE V. Also, in this paper we composed actual data recording system and achieved recording experiment by applying ESIL to magneto-optical recording. In conclusion. we analyze the improvement of aerial density and the reasonability of application to real data storage system.

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Detection of API(Anomaly Process Instance) Based on Distance for Process Mining (프로세스 마이닝을 위한 거리 기반의 API(Anomaly Process Instance) 탐지법)

  • Jeon, Daeuk;Bae, Hyerim
    • Journal of Korean Institute of Industrial Engineers
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    • v.41 no.6
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    • pp.540-550
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    • 2015
  • There have been many attempts to find knowledge from data using conventional statistics, data mining, artificial intelligence, machine learning and pattern recognition. In those research areas, knowledge is approached in two ways. Firstly, researchers discover knowledge represented in general features for universal recognition, and secondly, they discover exceptional and distinctive features. In process mining, an instance is sequential information bounded by case ID, known as process instance. Here, an exceptional process instance can cause a problem in the analysis and discovery algorithm. Hence, in this paper we develop a method to detect the knowledge of exceptional and distinctive features when performing process mining. We propose a method for anomaly detection named Distance-based Anomaly Process Instance Detection (DAPID) which utilizes distance between process instances. DAPID contributes to a discovery of distinctive characteristic of process instance. For verifying the suggested methodology, we discovered characteristics of exceptional situations from log data. Additionally, we experiment on real data from a domestic port terminal to demonstrate our proposed methodology.

Development of the Korea Ocean Prediction System

  • Suk, Moon-Sik;Chang, Kyung-Il;Nam, Soo-Yong;Park, Sung-Hyea
    • Ocean and Polar Research
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    • v.23 no.2
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    • pp.181-188
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    • 2001
  • We describe here the Korea ocean prediction system that closely resembles operational numerical weather prediction systems. This prediction system will be served for real-time forecasts. The core of the system is a three-dimensional primitive equation numerical circulation model, based on ${\sigma}$-coordinate. Remotely sensed multi-channel sea surface temperature (MCSST) is imposed at the surface. Residual subsurface temperature is assimilated through the relationship between vertical temperature structure function and residual of sea surface height (RSSH) using an optimal interpolation scheme. A unified grid system, named as [K-E-Y], that covers the entire seas around Korea is used. We present and compare hindcasting results during 1990-1999 from a model forced by MCSST without incorporating RSSH data assimilation and the one with both MCSST and RSSH assimilated. The data assimilation is applied only in the East Sea, hence the comparison focuses principally on the mesoscale features prevalent in the East Sea. It is shown that the model with the data assimilation exhibits considerable skill in simulating both the permanent and transient mesoscale features in the East Sea.

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Dynamic data-base Typhoon Track Prediction (DYTRAP) (동적 데이터베이스 기반 태풍 진로 예측)

  • Lee, Yunje;Kwon, H. Joe;Joo, Dong-Chan
    • Atmosphere
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    • v.21 no.2
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    • pp.209-220
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    • 2011
  • A new consensus algorithm for the prediction of tropical cyclone track has been developed. Conventional consensus is a simple average of a few fixed models that showed the good performance in track prediction for the past few years. Meanwhile, the consensus in this study is a weighted average of a few models that may change for every individual forecast time. The models are selected as follows. The first step is to find the analogous past tropical cyclone tracks to the current track. The next step is to evaluate the model performances for those past tracks. Finally, we take the weighted average of the selected models. More weight is given to the higher performance model. This new algorithm has been named as DYTRAP (DYnamic data-base Typhoon tRAck Prediction) in the sense that the data base is used to find the analogous past tracks and the effective models for every individual track prediction case. DYTRAP has been applied to all 2009 tropical cyclone track prediction. The results outperforms those of all models as well as all the official forecasts of the typhoon centers. In order to prove the real usefulness of DYTRAP, it is necessary to apply the DYTRAP system to the real time prediction because the forecast in typhoon centers usually uses 6-hour or 12-hour-old model guidances.