• Title/Summary/Keyword: computer science

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Image compression using K-mean clustering algorithm

  • Munshi, Amani;Alshehri, Asma;Alharbi, Bayan;AlGhamdi, Eman;Banajjar, Esraa;Albogami, Meznah;Alshanbari, Hanan S.
    • International Journal of Computer Science & Network Security
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    • v.21 no.9
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    • pp.275-280
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    • 2021

  • With the development of communication networks, the processes of exchanging and transmitting information rapidly developed. As millions of images are sent via social media every day, also wireless sensor networks are now used in all applications to capture images such as those used in traffic lights, roads and malls. Therefore, there is a need to reduce the size of these images while maintaining an acceptable degree of quality. In this paper, we use Python software to apply K-mean Clustering algorithm to compress RGB images. The PSNR, MSE, and SSIM are utilized to measure the image quality after image compression. The results of compression reduced the image size to nearly half the size of the original images using k = 64. In the SSIM measure, the higher the K, the greater the similarity between the two images which is a good indicator to a significant reduction in image size. Our proposed compression technique powered by the K-Mean clustering algorithm is useful for compressing images and reducing the size of images.

  • https://doi.org/10.22937/IJCSNS.2021.21.9.36 인용 PDF KSCI

Performance Analysis of Operating Systems for Wireless Sensor Networks (무선 센서 네트워크를 위한 운영체제들의 성능분석)

  • Min Hong;Yi Sang-Ho;Gu Bon-Cheol;Heo Jun-Young;Kim Yong-Tae;Cho Yoo-Kun;Hong Ji-Man
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06a
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    • pp.331-333
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    • 2006

  • 무선 센서 네트워크의 사용분야가 넓어짐에 따라 다양한 종류의 플랫폼을 지원하고 센서 노드의 제한된 자원을 효율적으로 사용할 수 있도록 관리하는 센서 운영체제들에 대한 연구가 활발하게 진행되었다. 본 논문에서는 기존의 운영체제들의 특징과 장단점을 분석해 보고, 태스크 관리와 메모리 관리 측면에서 성능 평가를 수행했다. 이러한 정보를 바탕으로 더욱 효율적인 시스템 설계를 위한 대안을 제시한다.

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Design and Implementation of a Massively Parallel Multithreaded Architecture: DAVRID

  • Sangho Ha;Kim, Junghwan;Park, Eunha;Yoonhee Hah;Sangyong Han;Daejoon Hwang;Kim, Heunghwan;Seungho Cho
    • Journal of Electrical Engineering and information Science
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    • v.1 no.2
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    • pp.15-26
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    • 1996

  • MPAs(Massively Parallel Architectures) should address two fundamental issues for scalability: synchronization and communication latency. Dataflow architecture faces problems of excessive synchronization overhead and inefficient execution of sequential programs while they offer the ability to exploit massive parallelism inherent in programs. In contrast, MPAs based on von Neumann computational model may suffer from inefficient synchronization mechanism and communication latency. DAVRID (DAtaflow/Von Neumann RISC hybrID) is a massively parallel multithreaded architecture which takes advantages of von Neumann and dataflow models. It has good single thread performance as well as tolerates synchronization and communication latency. In this paper, we describe the DAVRID architecture in detail and evaluate its performance through simulation runs over several benchmarks.

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