• 제목/요약/키워드: redundant data

검색결과 442건 처리시간 0.024초

무선 센서 네트워크 환경에서 적응형 임계값 설정 방법 (An Adaptive Threshold Method in Wireless Sensor Network Environments)

  • 김인태;김두용
    • 반도체디스플레이기술학회지
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    • 제7권1호
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    • pp.23-27
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    • 2008
  • Wireless sensor networks are emerging as a solution for a wide range of data gathering applications. The most difficult challenge for the design of sensor nodes is the need for significant reductions in energy consumption. The threshold methods which filter redundant and similar data can be used to save energy. In this paper, we propose the adaptive threshold method to effectively manage the energy in wireless sensor nodes. In the adaptive threshold method, wireless sensor nodes can change the thresholds dynamically as the sensing environments vary. The simulation results show that the adaptive threshold method works very effectively even when we experience the significant volatility in the data. This scheme can be used in order to monitor the malfunction in the equipment of semiconductor manufacturing line.

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온톨로지 기반 정보 검색 시스템을 이용한 iPMIS (지능형 종합사업관리시스템) 정보 추론에 관한 연구 (A Study of iPMIS(Intelligent Program Management Information System) Information Inference an Searching System Based on Ontologies)

  • 안형준;임재복;김주형;김재준
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2009년도 춘계 학술논문 발표대회 학계
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    • pp.175-179
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    • 2009
  • Researches of current PMIS(Project Management Information System) information searching focus on providing personalized results as well as matching needed queries in an enormous amount of information. This paper aim at discovering hidden knowledge to provide personalized and inferred search results based on the ontology with categorized concepts and relations among construction data. The current PMIS searching occasionally presents too much redundant information or offers no matching results from large volumes of data. In this paper, we propose a service searching system, which becomes aware of users device using iPMIS(Intelligent Program Management Information System). And we design and plant the ontology-based iPMIS, which is aware of the context in its environment.

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Data Alignment for Data Fusion in Wireless Multimedia Sensor Networks Based on M2M

  • Cruz, Jose Roberto Perez;Hernandez, Saul E. Pomares;Cote, Enrique Munoz De
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권1호
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    • pp.229-240
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    • 2012
  • Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN). The WMSNs were created to ubiquitously harvest multimedia content. Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks. These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices. This paradigm of data generation and transmission is known as event-streaming. In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data. A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities. However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity. To decrease such redundancy, data fusion must be performed in a collaborative way. In this paper, we propose a collaborative data alignment approach for event-streaming. Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.

Image Deduplication Based on Hashing and Clustering in Cloud Storage

  • Chen, Lu;Xiang, Feng;Sun, Zhixin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권4호
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    • pp.1448-1463
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    • 2021
  • With the continuous development of cloud storage, plenty of redundant data exists in cloud storage, especially multimedia data such as images and videos. Data deduplication is a data reduction technology that significantly reduces storage requirements and increases bandwidth efficiency. To ensure data security, users typically encrypt data before uploading it. However, there is a contradiction between data encryption and deduplication. Existing deduplication methods for regular files cannot be applied to image deduplication because images need to be detected based on visual content. In this paper, we propose a secure image deduplication scheme based on hashing and clustering, which combines a novel perceptual hash algorithm based on Local Binary Pattern. In this scheme, the hash value of the image is used as the fingerprint to perform deduplication, and the image is transmitted in an encrypted form. Images are clustered to reduce the time complexity of deduplication. The proposed scheme can ensure the security of images and improve deduplication accuracy. The comparison with other image deduplication schemes demonstrates that our scheme has somewhat better performance.

시스템 결함원인분석을 위한 데이터 로그 전처리 기법 연구 (A Study on Data Pre-filtering Methods for Fault Diagnosis)

  • 이양지;김덕영;황민순;정영수
    • 한국CDE학회논문집
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    • 제17권2호
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    • pp.97-110
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    • 2012
  • High performance sensors and modern data logging technology with real-time telemetry facilitate system fault diagnosis in a very precise manner. Fault detection, isolation and identification in fault diagnosis systems are typical steps to analyze the root cause of failures. This systematic failure analysis provides not only useful clues to rectify the abnormal behaviors of a system, but also key information to redesign the current system for retrofit. The main barriers to effective failure analysis are: (i) the gathered data (event) logs are too large in general, and further (ii) they usually contain noise and redundant data that make precise analysis difficult. This paper therefore applies suitable pre-processing techniques to data reduction and feature extraction, and then converts the reduced data log into a new format of event sequence information. Finally the event sequence information is decoded to investigate the correlation between specific event patterns and various system faults. The efficiency of the developed pre-filtering procedure is examined with a terminal box data log of a marine diesel engine.

Visualization of Dynamic Simulation Data for Power System Stability Assessment

  • Song, Chong-Suk;Jang, Gil-Soo;Park, Chang-Hyun
    • Journal of Electrical Engineering and Technology
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    • 제6권4호
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    • pp.484-492
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    • 2011
  • Power system analyses, which involve the handling of massive data volumes, necessitate the use of effective visualization methods to facilitate analysis and assist the user in obtaining a clear understanding of the present state of the system. This paper introduces an interface that compensates for the limitations of the visualization modules of dynamic security assessment tools, such as PSS/e and TSAT, for power system variables including generator rotor angle and frequency. The compensation is made possible through the automatic provision of dynamic simulation data in visualized and tabular form for better data intuition, thereby considerably reducing the redundant manual operation and time required for data analysis. The interface also determines whether the generators are stable through a generator instability algorithm that scans simulation data and checks for an increase in swing or divergence. The proposed visualization methods are applied to the dynamic simulation results for contingencies in the Korean Electric Power Corporation system, and have been tested by power system researchers to verify the effectiveness of the data visualization interface.

해양자료 객체 DB 모델링 연구 (Study on Object Modelling for Oceanic Data)

  • 박종민;서상현
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 1999년도 추계종합학술대회
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    • pp.454-457
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    • 1999
  • 해양분야의 정보들은 대부분 지리정보와 관련되어 있으며 또한 응용 분야 및 시스템에 따라 표현 방식이 상이하여 시스템 차원의 개발 비용이 증가하고 있다 이러한 문제를 해결하기 위한 근본적인 방법은 해양정보에 대한 단일 개념의 데이터 모델을 기반으로 한 자료 이용체계를 확립하는 것이다. 본 논문에서는 해양정보의 GIS 기반 객체 데이터 모델 정의를 위한 가이드라인을 설정하고 이에 따른 객체 데이터 모델을 설계한다. 이러한 GIS 기반 객체 데이터모델을 설계하여 데이터베이스 시스템을 구축함으로서 데이터 통합, 관리 및 응용시스템 개발 전반에 관한 효율성 증진을 예상할 수 있을 것이다.

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New Medical Image Fusion Approach with Coding Based on SCD in Wireless Sensor Network

  • Zhang, De-gan;Wang, Xiang;Song, Xiao-dong
    • Journal of Electrical Engineering and Technology
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    • 제10권6호
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    • pp.2384-2392
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    • 2015
  • The technical development and practical applications of big-data for health is one hot topic under the banner of big-data. Big-data medical image fusion is one of key problems. A new fusion approach with coding based on Spherical Coordinate Domain (SCD) in Wireless Sensor Network (WSN) for big-data medical image is proposed in this paper. In this approach, the three high-frequency coefficients in wavelet domain of medical image are pre-processed. This pre-processing strategy can reduce the redundant ratio of big-data medical image. Firstly, the high-frequency coefficients are transformed to the spherical coordinate domain to reduce the correlation in the same scale. Then, a multi-scale model product (MSMP) is used to control the shrinkage function so as to make the small wavelet coefficients and some noise removed. The high-frequency parts in spherical coordinate domain are coded by improved SPIHT algorithm. Finally, based on the multi-scale edge of medical image, it can be fused and reconstructed. Experimental results indicate the novel approach is effective and very useful for transmission of big-data medical image(especially, in the wireless environment).

RAID를 위한 SSD 캐시: 데이터 캐싱과 패리티 갱신 지연 기법의 결합 (SSD Cache for RAID: Integrating Data Caching and Parity Update Delay)

  • 하성태;이동희
    • 정보과학회 컴퓨팅의 실제 논문지
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    • 제23권6호
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    • pp.379-385
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    • 2017
  • 디스크 기반 RAID와 SSD를 결합한 하이브리드 스토리지가 기업 환경에서 널리 이용되고 있다. RAID 상단의 SSD는 주로 데이터 캐시로 사용된다. 최근 SSD를 사용하여 패리티 갱신 비용을 감소시키는 LeavO 캐시 기법이 제안되었으며, 본 논문에서는 데이터 캐시와 LeavO 캐시를 결합한 혼합 캐시기법을 제안한다. 특히 SSD 공간을 데이터 캐시와 LeavO 캐시, 두 영역으로 최적으로 분할하기 위해 비용 모델을 도출하고, 워크로드에 따라 두 영역의 크기를 동적으로 조절하는 적응형 혼합 캐시 기법을 개발하였다. 실험 결과에 따르면 적응형 혼합 캐시 기법은 기존 데이터 캐시 기법에 비해 좋은 성능을 보이며, 오프라인 최적 기법과 대등한 성능을 보인다.

Cellular Traffic Offloading through Opportunistic Communications Based on Human Mobility

  • Li, Zhigang;Shi, Yan;Chen, Shanzhi;Zhao, Jingwen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권3호
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    • pp.872-885
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    • 2015
  • The rapid increase of smart mobile devices and mobile applications has led to explosive growth of data traffic in cellular network. Offloading data traffic becomes one of the most urgent technical problems. Recent work has proposed to exploit opportunistic communications to offload cellular traffic for mobile data dissemination services, especially for accepting large delayed data. The basic idea is to deliver the data to only part of subscribers (called target-nodes) via the cellular network, and allow target-nodes to disseminate the data through opportunistic communications. Human mobility shows temporal and spatial characteristics and predictability, which can be used as effective guidance efficient opportunistic communication. Therefore, based on the regularity of human mobility we propose NodeRank algorithm which uses the encounter characteristics between nodes to choose target nodes. Different from the existing work which only using encounter frequency, NodeRank algorithm combined the contact time and inter-contact time meanwhile to ensure integrity and availability of message delivery. The simulation results based on real-world mobility traces show the performance advantages of NodeRank in offloading efficiency and network redundant copies.