• 제목/요약/키워드: Information Processing Technology

검색결과 7,830건 처리시간 0.035초

On Efficient Processing of Continuous Reverse Skyline Queries in Wireless Sensor Networks

  • Yin, Bo;Zhou, Siwang;Zhang, Shiwen;Gu, Ke;Yu, Fei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권4호
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    • pp.1931-1953
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    • 2017
  • The reverse skyline query plays an important role in information searching applications. This paper deals with continuous reverse skyline queries in sensor networks, which retrieves reverse skylines as well as the set of nodes that reported them for continuous sampling epochs. Designing an energy-efficient approach to answer continuous reverse skyline queries is non-trivial because the reverse skyline query is not decomposable and a huge number of unqualified nodes need to report their sensor readings. In this paper, we develop a new algorithm that avoids transmission of updates from nodes that cannot influence the reverse skyline. We propose a data mapping scheme to estimate sensor readings and determine their dominance relationships without having to know the true values. We also theoretically analyze the properties for reverse skyline computation, and propose efficient pruning techniques while guaranteeing the correctness of the answer. An extensive experimental evaluation demonstrates the efficiency of our approach.

Novel Parallel Approach for SIFT Algorithm Implementation

  • Le, Tran Su;Lee, Jong-Soo
    • Journal of information and communication convergence engineering
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    • 제11권4호
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    • pp.298-306
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    • 2013
  • The scale invariant feature transform (SIFT) is an effective algorithm used in object recognition, panorama stitching, and image matching. However, due to its complexity, real-time processing is difficult to achieve with current software approaches. The increasing availability of parallel computers makes parallelizing these tasks an attractive approach. This paper proposes a novel parallel approach for SIFT algorithm implementation using a block filtering technique in a Gaussian convolution process on the SIMD Pixel Processor. This implementation fully exposes the available parallelism of the SIFT algorithm process and exploits the processing and input/output capabilities of the processor, which results in a system that can perform real-time image and video compression. We apply this implementation to images and measure the effectiveness of such an approach. Experimental simulation results indicate that the proposed method is capable of real-time applications, and the result of our parallel approach is outstanding in terms of the processing performance.

Statistical Image Processing using Java on the Web

  • Lim, Dong Hoon;Park, Eun Hee
    • Communications for Statistical Applications and Methods
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    • 제9권2호
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    • pp.355-366
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    • 2002
  • The web is one of the most plentiful sources of images. The web has an immediate need for image processing technology in Java. This paper provides a practical introduction to statistical image processing using Java on the web. The paper describes how images are represented in Java and deals with four image processing operations based on basic statistical methods: point processing, spatial filtering, edge detection and image segmentation.

A Genetic Approach for Joint Link Scheduling and Power Control in SIC-enable Wireless Networks

  • Wang, Xiaodong;Shen, Hu;Lv, Shaohe;Zhou, Xingming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권4호
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    • pp.1679-1691
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    • 2016
  • Successive interference cancellation (SIC) is an effective means of multi-packet reception to combat interference at the physical layer. We investigate the joint optimization issue of channel access and power control for capacity maximization in SIC-enabled wireless networks. We propose a new interference model to characterize the sequential detection nature of SIC. Afterward, we formulize the joint optimization problem, prove it to be a nondeterministic polynomial-time-hard problem, and propose a novel approximation approach based on the genetic algorithm (GA). Finally, we discuss the design and parameter setting of the GA approach and validate its performance through extensive simulations.

모바일 클라이언트-서버 모델에 관한 연구 (On the Mobile Client and Server Model)

  • 이지영
    • 정보학연구
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    • 제12권1호
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    • pp.15-20
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    • 2009
  • In this paper, we aim that it solve to problem of the database hoarding because a week connectivity of wireless networks and cutting of link, Consistency of shared data, optimizing of the log include to Mobile Continuous Query Processing System under the mobile client and server environment. and we demonstrate of the superiority for the new Mobile Continuous Query Processing System compare C-I-S(Client-Intercept -Server)model with performance. and we perform to various experiment in order to establishment of superiority compare the index architecture and method for the realtime Continuous Query Processing. in this paper.

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실시간 모바일 클라우드 컴퓨팅을 위한 맵리듀스 응용 처리 기법 분석 (An analysis of MapReduce application processing schemes for realtime mobile cloud computing)

  • 김희재;윤찬현
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2014년도 추계학술발표대회
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    • pp.122-125
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    • 2014
  • 본 논문에서는 실시간 모바일 클라우드 컴퓨팅(mobile cloud computing)을 위한 맵리듀스(Map Reduce) 응용 처리 기법으로써 데이터 전송 경로 관리, 노드(nod) 간 다른 처리 속도로 인한 문제점 개선을 통한 성능 향상 기법들과 맵리듀스 작업의 효과적인 반복적 및 스트리밍(streaming)실행 기법들을 분석한다.

Advanced Big Data Analysis, Artificial Intelligence & Communication Systems

  • Jeong, Young-Sik;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • 제15권1호
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    • pp.1-6
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    • 2019
  • Recently, big data and artificial intelligence (AI) based on communication systems have become one of the hottest issues in the technology sector, and methods of analyzing big data using AI approaches are now considered essential. This paper presents diverse paradigms to subjects which deal with diverse research areas, such as image segmentation, fingerprint matching, human tracking techniques, malware distribution networks, methods of intrusion detection, digital image watermarking, wireless sensor networks, probabilistic neural networks, query processing of encrypted data, the semantic web, decision-making, software engineering, and so on.

PC-KIMMO-based Description of Mongolian Morphology

  • Jaimai, Purev;Zundui, Tsolmon;Chagnaa, Altangerel;Ock, Cheol-Young
    • Journal of Information Processing Systems
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    • 제1권1호
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    • pp.41-48
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    • 2005
  • This paper presents the development of a morphological processor for the Mongolian language, based on the two-level morphological model which was introduced by Koskenniemi. The aim of the study is to provide Mongolian syntactic parsers with more effective information on word structure of Mongolian words. First hand written rules that are the core of this model are compiled into finite-state transducers by a rule tool. Output of the compiler was edited to clarity by hand whenever necessary. The rules file and lexicon presented in the paper describe the morphology of Mongolian nouns, adjectives and verbs. Although the rules illustrated are not sufficient for accounting all the processes of Mongolian lexical phonology, other necessary rules can be easily added when new words are supplemented to the lexicon file. The theoretical consideration of the paper is concluded in representation of the morphological phenomena of Mongolian by the general, language-independent framework of the two-level morphological model.

Pointwise CNN for 3D Object Classification on Point Cloud

  • Song, Wei;Liu, Zishu;Tian, Yifei;Fong, Simon
    • Journal of Information Processing Systems
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    • 제17권4호
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    • pp.787-800
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    • 2021
  • Three-dimensional (3D) object classification tasks using point clouds are widely used in 3D modeling, face recognition, and robotic missions. However, processing raw point clouds directly is problematic for a traditional convolutional network due to the irregular data format of point clouds. This paper proposes a pointwise convolution neural network (CNN) structure that can process point cloud data directly without preprocessing. First, a 2D convolutional layer is introduced to percept coordinate information of each point. Then, multiple 2D convolutional layers and a global max pooling layer are applied to extract global features. Finally, based on the extracted features, fully connected layers predict the class labels of objects. We evaluated the proposed pointwise CNN structure on the ModelNet10 dataset. The proposed structure obtained higher accuracy compared to the existing methods. Experiments using the ModelNet10 dataset also prove that the difference in the point number of point clouds does not significantly influence on the proposed pointwise CNN structure.

Analysis of Business Attributes in Information Technology Environments

  • Lee, Hong-Joo
    • Journal of Information Processing Systems
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    • 제7권2호
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    • pp.385-396
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    • 2011
  • Information technology is changing the business value chain and business systems. This situation is due to the business value chain and the value creation factors in business. Technology companies and researchers are developing new businesses, but many companies and researchers cannot find successful ways to analyze and develop a business in a specific way. In this paper, the following will be explored. First, the value creation motive in business is analyzed through a literary review. Second, business attributes are analyzed while considering the value creation motive and business factors in management. Finally, the business attributes of information technology are studied through a review of previous research that has been conducted on this topic.