• Title/Summary/Keyword: Network Split

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An Improved Split Algorithm for Indexing of Moving Object Trajectories (이동 객체 궤적의 색인을 위한 개선된 분할 알고리즘)

  • Jeon, Hyun-Jun;Park, Ju-Hyun;Park, Hee-Suk;Cho, Woo-Hyun
    • The KIPS Transactions:PartD
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    • v.16D no.2
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    • pp.161-168
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    • 2009
  • Recently, use of various position base servicesthat collect position information for moving object and utilize in real life is increasing by the development of wireless network technology. Accordingly, new index structures are required to efficiently retrieve the consecutive positions of moving objects. This paper addresses an improved trajectory split algorithm for the purpose of efficiently supporting spatio-temporal range queries using index structures that use Minimum Bounding Rectangles(MBR) as trajectory approximations. We consider volume of Extended Minimum Bounding Rectangles (EMBR) to be determined by average size of range queries. Also, Use a priority queue to speed up our process. This algorithm gives in general sub-optimal solutions with respect to search space. Our improved trajectory split algorithm is going to derive minimizing volume of EMBRs better than previously proposed split algorithm.

Design, fabrication and performance characteristics of a 50kHz tonpilz type transducer with a half-wavelength diameter (반파장 직경을 갖는 50kHz tonpilz형 음향 변환기의 설계, 제작 및 성능특성)

  • Lee, Dae-Jae;Lee, Won-Sub
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.46 no.2
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    • pp.173-183
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    • 2010
  • In a split beam echo sounder, the transducer design needs to have minimal side lobes because the angular position and level of the side lobes establishes the usable signal level and phase angle limits for determining target strength. In order to suppress effectively the generation of unwanted side lobes in the directivity pattern of split beam transducer, the spacing and size of the transducer elements need to be controlled less than half of a wavelength. With this purpose, a 50 kHz tonpilz type transducer with a half-wavelength diameter in relation to the development of a split beam transducer was designed using the equivalent circuit model, and the underwater performance characteristics were measured and analyzed. From the in-air and in-water impedance responses, the measured value of the electro-acoustic conversion efficiency for the designed transducer was 51.6%. A maximum transmitting voltage response (TVR) value of 172.25dB re $1{\mu}Pa/V$ at 1m was achieved at 52.92kHz with a specially designed matching network and the quality factor was 10.3 with the transmitting bandwidth of 5.14kHz. A maximum receiving sensitivity (SRT) of -183.57dB re $1V/{\mu}Pa$ was measured at 51.45kHz and the receiving bandwidth at -3dB was 1.71kHz. These results suggest that the designed tonpilz type transducer can be effectively used in the development of a split beam transducer for a 50kHz fish sizing echo sounder.

Recognition of English Calling Cards by Using Projection Method and Enhanced RBE Network

  • Kim, Kwang-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.4
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    • pp.474-479
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    • 2003
  • In this paper, we proposed the novel method for the recognition of English calling cards by using the projection method and the enhanced RBF (Radial Basis Function) network. The recognition of calling cards consists of the extraction phase of character areas and the recognition phase of extracted characters. In the extraction phase, first of all, noises are removed from the images of calling cards, and the feature areas including character strings are separated from the calling card images by using the horizontal smearing method and the 8-directional contour tracking method. And using the image projection method, the feature areas are split into the areas of individual characters. We also proposed the enhanced RBF network that organizes the middle layer effectively by using the enhanced ART1 neural network adjusting the vigilance threshold dynamically according to the homogeneity between patterns. In the recognition phase, the proposed neural network is applied to recognize individual characters. Our experiment result showed that the proposed recognition algorithm has higher success rate of recognition and faster learning time than the existing neural network based recognition.

Hierarchical network management based on MA+SNMP (MA+SNMP 기반의 계층적인 네트워크 관리구조)

  • Na, Ho-Jin;Cho, Kyung-San
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.5
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    • pp.93-101
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    • 2010
  • Although various network management architectures such as centralized, distributed, and hybrid have been presented, any one is not always efficient in all the environment. In this paper, we propose a hierarchical and split network management architecture based on MA+SNMP in order to manage a network of many small NEs distributed over the wide area. Our hierarchical architecture has MA-based proxy management nodes for the flexibility and overhead reduction in NMS as well as SNMP-based NEs considering NE's capacity. Through the analysis with real experiments, we show that our proposal improves some drawbacks and the processing delay of the existing architectures in the given environment.

PREDICTION OF RESIDUAL STRESS FOR DISSIMILAR METALS WELDING AT NUCLEAR POWER PLANTS USING FUZZY NEURAL NETWORK MODELS

  • Na, Man-Gyun;Kim, Jin-Weon;Lim, Dong-Hyuk
    • Nuclear Engineering and Technology
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    • v.39 no.4
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    • pp.337-348
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    • 2007
  • A fuzzy neural network model is presented to predict residual stress for dissimilar metal welding under various welding conditions. The fuzzy neural network model, which consists of a fuzzy inference system and a neuronal training system, is optimized by a hybrid learning method that combines a genetic algorithm to optimize the membership function parameters and a least squares method to solve the consequent parameters. The data of finite element analysis are divided into four data groups, which are split according to two end-section constraints and two prediction paths. Four fuzzy neural network models were therefore applied to the numerical data obtained from the finite element analysis for the two end-section constraints and the two prediction paths. The fuzzy neural network models were trained with the aid of a data set prepared for training (training data), optimized by means of an optimization data set and verified by means of a test data set that was different (independent) from the training data and the optimization data. The accuracy of fuzzy neural network models is known to be sufficiently accurate for use in an integrity evaluation by predicting the residual stress of dissimilar metal welding zones.

GRID BASED ENERGY EFFICIENT AND SECURED DATA TRANSACTION FOR CLOUD ASSISTED WSN-IOT

  • L. SASIREGA;C. SHANTHI
    • Journal of applied mathematics & informatics
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    • v.41 no.1
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    • pp.95-105
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    • 2023
  • To make the network energy efficient and to protect the network from malignant user's energy efficient grid based secret key sharing scheme is proposed. The cost function is evaluated to select the optimal nodes for carrying out the data transaction process. The network is split into equal number of grids and each grid is placed with certain number of nodes. The node cost function is estimated for all the nodes present in the network. Once the optimal energy proficient nodes are selected then the data transaction process is carried out in a secured way using malicious nodes filtration process. Therefore, the message is transmitted in a secret sharing method to the end user and this process makes the network more efficient. The proposed work is evaluated in network simulated and the performance of the work are analysed in terms of energy, delay, packet delivery ratio, and false detection ratio. From the result, we observed that the work outperforms the other works and achieves better energy and reduced packet rate.

The Clustering Scheme for Load-Balancing in Mobile Ad-hoc Network (이동 애드혹 네트워크에서 로드 밸런싱을 위한 클러스터링 기법)

  • Lim, Won-Taek;Kim, Gu-Su;Kim, Moon-Jeong;Eom, Young-Ik
    • The KIPS Transactions:PartC
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    • v.13C no.6 s.109
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    • pp.757-766
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    • 2006
  • Mobile Ad-hoc Network(MANET) is an autonomous network consisted of mobile hosts. A considerable number of studies have been conducted on the MANET with studies of ubiquitous computing. Several studies have been made on the clustering schemes which manage network hierarchically to Improve flat architecture of MANET. But the conventional schemes have the lack of multi-hop clustering and load balancing. This paper proposes a clustering scheme to support multi-hop clustering and to consider load balancing between cluster heads. We define the split of clusters and states of cluster, and propose join, merge, divide, and election of cluster head schemes for load balancing of between cluster heads

A Continuous Network Design Model for Target-Oriented Transport Mode Choice Problem (목표지향 교통수단선택을 위한 연속형 교통망설계모형)

  • Im, Yong-Taek
    • Journal of Korean Society of Transportation
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    • v.27 no.6
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    • pp.157-166
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    • 2009
  • A network design problem (NDP) is to find a design parameter to optimize the performance of transportation system. This paper presents a modified NDP, called target-oriented NDP, which contains a target that we try to arrive in real world, and also proposes a solution algorithm. Unlike general NDP which seeks an optimal value to minimize or to maximize objective function of the system, in target-oriented NDP traffic manager or operator can set a target level prior and then try to find an optimal design variable to attain this goal. A simple example for mode choice problem is given to test the model.

Machine Learning Based Hybrid Approach to Detect Intrusion in Cyber Communication

  • Neha Pathak;Bobby Sharma
    • International Journal of Computer Science & Network Security
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    • v.23 no.11
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    • pp.190-194
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    • 2023
  • By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

Fast Acting Load Shedding and Network Split System Using PLC (PLC를 이용한 고속동작 부하차단 및 계통분리 시스템)

  • Yu, Young-Sik;Oh, Seok-Bong;Lee, Kang-Wan
    • Proceedings of the KIEE Conference
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    • 2005.07a
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    • pp.27-29
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    • 2005
  • 자가디젤발전기를 운전하고 있는 산업체 전력계통에서 전력공급의 신뢰성을 높이기 위해 전력치사와의 연계선 분리에 따른 수급 불균형과 전력회사 계통 동요로 인한 계통 불안정 상태에 대처하기 위한 부하차단 및 계통분리 안정화 시스템을 고속동작이 보장되는 PLC로 구축하여 현장에 적용한 연구 사례이다.

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