• Title/Summary/Keyword: object location memory

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The Study of the Object Replication Management using Adaptive Duplication Object Algorithm (적응적 중복 객체 알고리즘을 이용한 객체 복제본 관리 연구)

  • 박종선;장용철;오수열
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.1
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    • pp.51-59
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    • 2003
  • It is effective to be located in the double nodes in the distributed object replication systems, then object which nodes share is the same contents. The nodes store an access information on their local cache as it access to the system. and then the nodes fetch and use it, when it needed. But with time the coherence Problems will happen because a data carl be updated by other nodes. So keeping the coherence of the system we need a mechanism that we managed the to improve to improve the performance and availability of the system effectively. In this paper to keep coherence in the shared memory condition, we can set the limited parallel performance without the additional cost except the coherence cost using it to keep the object at the proposed adaptive duplication object(ADO) algorithms. Also to minimize the coherence maintenance cost which is the bi99est overhead in the duplication method, we must manage the object effectively for the number of replication and location of the object replica which is the most important points, and then it determines the cos. And that we must study the adaptive duplication object management mechanism which will improve the entire run time.

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Precision Analysis of NARX-based Vehicle Positioning Algorithm in GNSS Disconnected Area

  • Lee, Yong;Kwon, Jay Hyoun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.5
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    • pp.289-295
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    • 2021
  • Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

Implementation of Extended TB-Trees Based on Direct Table for Indexing Trajectories of Moving Objects in LBS Applications (LBS 응용에서 이동 객체의 궤적 색인을 위한 직접 테이블 기반의 확장된 TB-트리의 구현)

  • Shin Yong-Won;Park Byung-Rae;Shim Choon-Bo
    • The Journal of the Korea Contents Association
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    • v.5 no.2
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    • pp.187-197
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    • 2005
  • In this paper, we propose an extended TB-tree, called ETB-tree, which can improve the performance of an existing TB-tree proposed for indexing the trajectories of moving objects in Location-Based Service(LBS). The proposed ETB-tree directly accesses the preceding node by maintaining a direct table, called D-Table which contains the page number in disk and memory pointers pointing the leaf node with the first and last lines segment of moving objects. It can improve the insertion performance by quick searching the preceding node of a moving object and retrieval performance owing to accessing directly the corresponding trajectories In disk for the trajectory-based query. In addition, the ETB-tree provides consistency of a tree by reflecting a newly inserted line segment to the tree both in memory and disk. The experimental results show that the proposed indexing technique gains better performance than other traditional ones with respect to the insertion and retrieval of a trajectory query.

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Video Image Processing on Apple II P.C. and Its Applications to Anthropometry and Motion Analysis (Apple II P.C.를 이용한 Video Image Processing과 인체계측 및 동작분석에의 응용)

  • Lee, Sang-Do;Jeong, Jung-Seon;Lee, Geun-Bu
    • Journal of the Ergonomics Society of Korea
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    • v.4 no.1
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    • pp.11-16
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    • 1985
  • The object of this research is to develop an Interactive Computerized Graphic Program for graphic output of velocity, acceleration and motion range of body-task reference point (e.g., C.O.G., joint location, etc.). Human motions can be reproduced by scanning (rate = 60Hz) the vidicon image, and the results are stored in an Apple II P.C. memory. The results of this study can be extended to simulation and reproduction of human motions for optimal task design.

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Construction Materials Management System Based on Location Information Using UHF RFID (UHF RFID를 이용한 위치정보 기반 건축자재 관리 시스템)

  • Kim, Tae-Yun;Hwang, Suk-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.9
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    • pp.1027-1032
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    • 2015
  • Using the radio wave, RFID(: Radio Frequency IDentification) wirelessly transmits the unique information saved in a tag attached on the specific object. In the construction area, the trend in using RFID for managing the input and inventory of the construction materials is upward. General management systems for the construction materials have only a function of identifying the tag attached on the construction materials, but the management system with a function of identifying and managing the location information of the construction materials employing RFID, for reusing it, is not actively developed. For the efficient reuse of the construction materials, in this paper, we propose the RFID system with a function of estimating and saving the location information of the specific construction materials, based on the estimated distances between the particular subs and reader. The proposed system consists of RFID reader, distance estimate, communication, and memory units.

Call-Site Tracing-based Shared Memory Allocator for False Sharing Reduction in DSM Systems (분산 공유 메모리 시스템에서 거짓 공유를 줄이는 호출지 추적 기반 공유 메모리 할당 기법)

  • Lee, Jong-Woo
    • Journal of KIISE:Computer Systems and Theory
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    • v.32 no.7
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    • pp.349-358
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    • 2005
  • False sharing is a result of co-location of unrelated data in the same unit of memory coherency, and is one source of unnecessary overhead being of no help to keep the memory coherency in multiprocessor systems. Moreover. the damage caused by false sharing becomes large in proportion to the granularity of memory coherency. To reduce false sharing in a page-based DSM system, it is necessary to allocate unrelated data objects that have different access patterns into the separate shared pages. In this paper we propose call-site tracing-based shared memory allocator. shortly CSTallocator. CSTallocator expects that the data objects requested from the different call-sites may have different access patterns in the future. So CSTailocator places each data object requested from the different call-sites into the separate shared pages, and consequently data objects that have the same call-site are likely to get together into the same shared pages. We use execution-driven simulation of real parallel applications to evaluate the effectiveness of our CSTallocator. Our observations show that by using CSTallocator a considerable amount of false sharing misses can be additionally reduced in comparison with the existing techniques.

A Study of Performance Decision Factor for Moving Object Database in Main Memory Index (이동체 데이터베이스를 위한 메인 메모리 색인의 성능 결정 요소에 관한 연구)

  • Lee, Chang-Woo;Ahn, Kyoung-Hwan;Hong, Bong-Hee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.05c
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    • pp.1575-1578
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    • 2003
  • 이동통신 기술의 발달로 인하여 무선 이동 기기의 사용이 보편화되면서 LBS(Location Based System)의 요구가 나날이 증대되고 있다. 이와 같은 위치 기반 서비스에서 클라이언트인 이동체들은 일정한 보고 주기를 가지고 서버에 위치 데이터를 보고하게 되는데, 빈번한 보고 데이터를 실시간으로 처리하기 위해서 서버에서는 메인 메모리 DBMS를 유지하는 것이 필요하다. 기존에 제시된 메인 메모리 색인으로는 T-tree 가 있는데, 이는 1차원 데이터를 위한 것이므로 이동체 데이터베이스 환경에 적합하지 못하다. 그리고, 디스크 기반의 다차원 색인으로는 R-tree 계열이 있는데, 이는 메인 메모리에서 효율적인 사용을 보장하지 못한다. 이 논문에서는 이동체 데이터베이스 환경에 적합한 메인 메모리 색인을 고려함에 있어서, 기존의 디스크 기반의 다차원 색인으로 가장 널리 알려진 R-tree 계열의 색인을 메인 메모리에 적재 후 메인 메모리 환경에서 성능에 영향을 주는 요소를 실험을 통하여 제시한다. 실험은 메인 메모리에서는 간단한 알고리즘을 사용하는 것이 성능에 좋고, 삽입 시에는 삽입할 노드를 찾기 위해서 비교하는 엔트리의 수가, 검색 시에는 노드간의 중첩으로 인하여 비교하는 노드의 수와 엔트리의 수가 성능에 영향을 주는 요소임을 보여준다.

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A Vehicle Detection and Tracking Algorithm Using Local Features of The Vehicle in Tunnel (차량의 부분 특징을 이용한 터널 내에서의 차량 검출 및 추적 알고리즘)

  • Kim, Hyun-Tae;Kim, Gyu-Young;Do, Jin-Kyu;Park, Jang Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.8
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    • pp.1179-1186
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    • 2013
  • In this paper, an efficient vehicle detection and tracking algorithm for detection incident in tunnel is proposed. The proposed algorithm consists of three steps. The first one is a step for background estimates, low computational complexity and memory consumption Running Gaussian Average (RGA) is used. The second step is vehicle detection step, Adaboost algorithm is applied to this step. In order to reduce false detection from a relatively remote location of the vehicles, local features according to height of vehicles are used to detect vehicles. If the local features of an object are more than the threshold value, the object is classified as a vehicle. The last step is a vehicle tracking step, the Kalman filter is applied to track moving objects. Through computer simulations, the proposed algorithm was found that useful to detect and track vehicles in the tunnel.

Design and Performance Analysis of Caching Algorithms for Distributed Non-uniform Objects (분산 이질형 객체 환경에서 캐슁 알고리즘의 설계 및 성능 분석)

  • Bahn, Hyo-Kyung;Noh, Sam-Hyeok;Min, Sang-Lyul;Koh, Kern
    • Journal of KIISE:Computer Systems and Theory
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    • v.27 no.6
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    • pp.583-591
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    • 2000
  • Caching mechanisms have been studied extensively to buffer the speed gap of hierarchical storages in the context of cache memory, paging system, and buffer management system. As the wide-area distributed environments such as the WWW extend broadly, caching of remote objects becomes more and more important. In the wide-area distributed environments, the cost and the benefit of caching an object is not uniform due to the location of the object; which should be considered in the cache replacement algorithms. For online operation, the time complexity of the replacement algorithm should not be excessive. To date, most replacement algorithms for the wide-area distributed environments do not meet both the non-uniformity of objects and the time complexity constraint. This paper proposes a replacement algorithm which considers the non-uniformity of objects properly; it also allows for an efficient implementation. Trace-driven simulations show that proposed algorithm outperforms existing replacement algorithms.

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An Approach Using LSTM Model to Forecasting Customer Congestion Based on Indoor Human Tracking (실내 사람 위치 추적 기반 LSTM 모델을 이용한 고객 혼잡 예측 연구)

  • Hee-ju Chae;Kyeong-heon Kwak;Da-yeon Lee;Eunkyung Kim
    • Journal of the Korea Society for Simulation
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    • v.32 no.3
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    • pp.43-53
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    • 2023
  • In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.