• Title/Summary/Keyword: 슬라이딩 알고리즘

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Hardware Architecture of Timing Synchronization for IEEE 802.11n Wireless LAN Systems (IEEE 802.11n 무선 LAN 시스템의 시간 동기화 하드웨어 구조)

  • Cho, Jong-Min;Kim, Jin-Sang;Cho, Won-Kyung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.11A
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    • pp.1124-1131
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    • 2008
  • In this paper, we propose a timing synchronization scheme and its hardware architecture of the next generation IEEE 802.11n wireless LAN standard which is based on MIMO-OFDM technique. Proposed timing synchronization method takes two steps which consist of two modified auto-correlators. For coarse timing synchronization, a sliding window differentiator is used after a conventional auto-correlation in order to avoid plateau problem. The conjugate symmetry property of L-LTS is utilized for the simplification of fine timing synchronization. Since cross-correlation based methods are not required, the computational complexity and the number of multipliers can be reduced. In order to reduce the hardware complexity, we have used sign multipliers. Based on simulation results, the proposed method outperforms a conventional method. The proposed scheme can be applied to IEEE 802.11n systems and can easily be expanded to frequency synchronization scheme.

Efficient Skyline Computation on Time-Interval Data Streams (유효시간 데이터 스트림에서의 스카이라인 질의 알고리즘)

  • Park, Nam-Hun;Chang, Joong-Hyuk
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.1
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    • pp.370-381
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    • 2012
  • Multi-criteria result extraction is crucial in many scientific applications that support real-time stream processing, such as habitat research and disaster monitoring. Skyline evaluation is computational intensive especially over continuous time-interval data streams where each object has its own customized expiration time. In this work, we propose TI-Sky - a continuous skyline evaluation framework. To ensure correctness, the result space needs to be continuously maintained as new objects arrive and older objects expire. TI-Sky strikes a perfect balance between the costs of continuously maintaining the result space and the costs of computing the final skyline result from this space whenever a pull-based user query is received. Our key principle is to incrementally maintain a partially precomputed skyline result space - however doing so efficiently by working at a higher level of abstraction. TI-Sky's algorithms for insertion, deletion, purging and result retrieval exploit both layers of granularity. Our experimental study demonstrates the superiority of TI-Sky over existing techniques to handle a wide variety of data sets.

The Performance Improvement for Congestion Control under TCP Traffic in Wireless Network (무선네트워크 전송기반에서 프로토콜에 의한 트래픽 혼잡제어)

  • Ra, Sang-Dong;Kim, Moon-Hwan;Lee, Sung-Joo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.10A
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    • pp.965-973
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    • 2007
  • We analyzed that the loss of data in TCP protocol based wireless networks caused by overlapped responses in bi-directional nodes that were resulted in out of the data sequence. This loss can be prevented by using revised TCP rate control algorithm and the performance of throughput can also be improved. The rate control algorithm is applied when the congestion happens between nodes while traffic packets are retransmitting in TCP bandwidth. In addition to applying the rate control algorithm, we determine the number of system clients in bandwidth and the average of pausing time between transmitting serial files to produce a competitive level so that an efficient performance of rapid retransmitting for the loss of multi-packets. This paper discusses the improvement of congestion control in that the decrease of the loss, firstly, as ensuring an efficient connection rate and, secondly, as using sliding window flow control.

A Concurrency Control Method for Data Broadcasting in Mobile Computing Environment (이동 컴퓨팅 환경에서 데이타 방송을 위한 동시성 제어 기법)

  • 윤혜숙;김영국
    • Journal of KIISE:Databases
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    • v.31 no.2
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    • pp.140-149
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    • 2004
  • Data broadcast has received much attention as a very efficient method for disseminating data items in mobile environment with large number of mobile clients. In this approach, a database server periodically and continuously broadcasts data items through wireless channels and clients perform read-only transactions by accessing necessary data items from the air. While broadcasting, the server must also process update transactions on the database, which raises an obstacle for client's accessing consistent data. In this research, we propose a new algorithm SCDSC(Serialization Checking with DirtySet on Commit) which is an alternative for solving the concurrency control problem efficiently. The SCDSC is a kind of optimistic concurrency control in that a client checks the consistency of data using a DirtySet as a part of data broadcast when it commits its transaction. In each broadcast cycle, the server updates and disseminates the DirtySet with newly changed data items for last few cycles in the sliding window approach. We perform an analysis and a simulation study to evaluate the performance of our SCDSC algorithm in terms of data consistency and data currency.

Driving Assist System using Semantic Segmentation based on Deep Learning (딥러닝 기반의 의미론적 영상 분할을 이용한 주행 보조 시스템)

  • Kim, Jung-Hwan;Lee, Tae-Min;Lim, Joonhong
    • Journal of IKEEE
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    • v.24 no.1
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    • pp.147-153
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    • 2020
  • Conventional lane detection algorithms have problems in that the detection rate is lowered in road environments having a large change in curvature and illumination. The probabilistic Hough transform method has low lane detection rate since it exploits edges and restrictive angles. On the other hand, the method using a sliding window can detect a curved lane as the lane is detected by dividing the image into windows. However, the detection rate of this method is affected by road slopes because it uses affine transformation. In order to detect lanes robustly and avoid obstacles, we propose driving assist system using semantic segmentation based on deep learning. The architecture for segmentation is SegNet based on VGG-16. The semantic image segmentation feature can be used to calculate safety space and predict collisions so that we control a vehicle using adaptive-MPC to avoid objects and keep lanes. Simulation results with CARLA show that the proposed algorithm detects lanes robustly and avoids unknown obstacles in front of vehicle.

Continuous Query Processing in Data Streams Using Duality of Data and Queries (데이타와 질의의 이원성을 이용한 데이타스트림에서의 연속질의 처리)

  • Lim Hyo-Sang;Lee Jae-Gil;Lee Min-Jae;Whang Kyu-Young
    • Journal of KIISE:Databases
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    • v.33 no.3
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    • pp.310-326
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    • 2006
  • In this paper, we deal with a method of efficiently processing continuous queries in a data stream environment. We classify previous query processing methods into two dual categories - data-initiative and query-initiative - depending on whether query processing is initiated by selecting a data element or a query. This classification stems from the fact that data and queries have been treated asymmetrically. For processing continuous queries, only data-initiative methods have traditionally been employed, and thus, the performance gain that could be obtained by query-initiative methods has been overlooked. To solve this problem, we focus on an observation that data and queries can be treated symmetrically. In this paper, we propose the duality model of data and queries and, based on this model, present a new viewpoint of transforming the continuous query processing problem to a multi-dimensional spatial join problem. We also present a continuous query processing algorithm based on spatial join, named Spatial Join CQ. Spatial Join CQ processes continuous queries by finding the pairs of overlapping regions from a set of data elements and a set of queries defined as regions in the multi-dimensional space. The algorithm achieves the effects of both of the two dual methods by using the spatial join, which is a symmetric operation. Experimental results show that the proposed algorithm outperforms earlier methods by up to 36 times for simple selection continuous queries and by up to 7 times for sliding window join continuous queries.

Performance Analysis of Adaptive Corner Shrinking Algorithm for Decimating the Document Image (문서 영상 축소를 위한 적응형 코너 축소 알고리즘의 성능 분석)

  • Kwak No-Yoon
    • Journal of Digital Contents Society
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    • v.4 no.2
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    • pp.211-221
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    • 2003
  • The objective of this paper is performance analysis of the digital document image decimation algorithm which generates a value of decimated element by an average of a target pixel value and a value of neighbor intelligible element to adaptively reflect the merits of ZOD method and FOD method on the decimated image. First, a target pixel located at the center of sliding window is selected, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each local intelligible weight. Next, a value of neighbor intelligible element is obtained by adding a value of the right neighbor pixel times its local intelligible weight to a value of the lower neighbor pixel times its intelligible weight. The decimated image can be acquired by applying the process repetitively to all pixels in input image which generates the value of decimated element by calculating the average of the target pixel value and the value of neighbor intelligible element. In this paper, the performance comparison of proposed method and conventional methods in terms of subjective performance and hardware complexity is analyzed and the preferable approach for developing the decimation algorithm of the digital document image on the basis of this analysis result has been reviewed.

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The Fault Diagnosis Model of Ship Fuel System Equipment Reflecting Time Dependency in Conv1D Algorithm Based on the Convolution Network (합성곱 네트워크 기반의 Conv1D 알고리즘에서 시간 종속성을 반영한 선박 연료계통 장비의 고장 진단 모델)

  • Kim, Hyung-Jin;Kim, Kwang-Sik;Hwang, Se-Yun;Lee, Jang Hyun
    • Journal of Navigation and Port Research
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    • v.46 no.4
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    • pp.367-374
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    • 2022
  • The purpose of this study was to propose a deep learning algorithm that applies to the fault diagnosis of fuel pumps and purifiers of autonomous ships. A deep learning algorithm reflecting the time dependence of the measured signal was configured, and the failure pattern was trained using the vibration signal, measured in the equipment's regular operation and failure state. Considering the sequential time-dependence of deterioration implied in the vibration signal, this study adopts Conv1D with sliding window computation for fault detection. The time dependence was also reflected, by transferring the measured signal from two-dimensional to three-dimensional. Additionally, the optimal values of the hyper-parameters of the Conv1D model were determined, using the grid search technique. Finally, the results show that the proposed data preprocessing method as well as the Conv1D model, can reflect the sequential dependency between the fault and its effect on the measured signal, and appropriately perform anomaly as well as failure detection, of the equipment chosen for application.

Efficient Processing of Multidimensional Vessel USN Stream Data using Clustering Hash Table (클러스터링 해쉬 테이블을 이용한 다차원 선박 USN 스트림 데이터의 효율적인 처리)

  • Song, Byoung-Ho;Oh, Il-Whan;Lee, Seong-Ro
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.6
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    • pp.137-145
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    • 2010
  • Digital vessel have to accurate and efficient mange the digital data from various sensors in the digital vessel. But, In sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. In this paper, We propose efficient processing method that arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and pre-clustering using multiple Support Vector Machine(SVM) algorithm and manage hash table to summarized information. Processing performance improve as store and search and memory using hash table and usage reduced so maintain hash table in memory. We obtained to efficient result that accuracy rate and processing performance of proposal method using 35,912 data sets.

Chattering Reduction of Variable Structure Controller for Position System of Induction Motor (유도전동기의 위치제어 시스템을 위한 가변구조제어기의 떨림저감)

  • Kim, Young-Jo;Kim, Hyun-Jung
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.2
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    • pp.39-47
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    • 1998
  • It has been known that variable structure control(VSC) has theoretically powerful control technique of providing fast response, no overshoot, and very robust control with respect to system parameter variations and disturbances. However, the technique has not become more widely extended in the industrial circles because chattering phenomenon which may excite high-frequency unmodelled plant dynamics and damage to system components exists. In this paper, a modified variable structure control(MVSC) is developed to alleviate these problems which are applied to the position control of induction motor. While the conventional VSC makes the structure of the system change with high-frequency switching on the center of the one switching surface, in the MVSC two switching surface are used to establish a sliding sector. The structure of the system will be changed with low-frequency switching. Therefore, the proposed algorithm has the properties of reducing chattering, retaining the benefits achieved in the conventional VSC, and working even under the influences of parameter variations. Experimental results show the effectiveness of the control strategy proposed here for the position control of induction motor.

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