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Development of Thermal Image System Based Multi-Core Image Processor (멀티코어 이미지 프로세서 기반 열화상 이미지 시스템 개발)

  • Cha, Jeong Woo;Han, Joon Hwan;Park, Chan;Kim, Young Jin
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.2
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    • pp.25-30
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    • 2020
  • The thermal image system was widely used in the defence-related industry because of detect infrared light from the object without light. but, as the demand in the security system and automobile market increases, the civilian industry are expanding to the private sector. There are difficult to apply various requirement because of previous systems are based by FPGA, so it need new system that apply to various requirement. The proposed paper is thermal image processing system using common image processor. It has various requirement and scalable to support image input/output interface and device driver. If it is used to proposed system, it reduce development cost and period than previous system based FPGA. Because there has very high accessibility. In addition, it expect to have satisfaction of customer requirements, development cost, development period, release date of product.

Optimizing Skyline Query Processing Algorithms on CUDA Framework (CUDA 프레임워크 상에서 스카이라인 질의처리 알고리즘 최적화)

  • Min, Jun;Han, Hwan-Soo;Lee, Sang-Won
    • Journal of KIISE:Databases
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    • v.37 no.5
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    • pp.275-284
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    • 2010
  • GPUs are stream processors based on multi-cores, which can process large data with a high speed and a large memory bandwidth. Furthermore, GPUs are less expensive than multi-core CPUs. Recently, usage of GPUs in general purpose computing has been wide spread. The CUDA architecture from Nvidia is one of efforts to help developers use GPUs in their application domains. In this paper, we propose techniques to parallelize a skyline algorithm which uses a simple nested loop structure. In order to employ the CUDA programming model, we apply our optimization techniques to make our skyline algorithm fit into the performance restrictions of the CUDA architecture. According to our experimental results, we improve the original skyline algorithm by 80% with our optimization techniques.

Generalized Steganalysis using Deep Learning (딥러닝을 이용한 범용적 스테그아날리시스)

  • Kim, Hyunjae;Lee, Jaekoo;Kim, Gyuwan;Yoon, Sungroh
    • KIISE Transactions on Computing Practices
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    • v.23 no.4
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    • pp.244-249
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    • 2017
  • Steganalysis is to detect information hidden by steganography inside general data such as images. There are stegoanalysis techniques that use machine learning (ML). Existing ML approaches to steganalysis are based on extracting features from stego images and modeling them. Recently deep learning-based methodologies have shown significant improvements in detection accuracy. However, all the existing methods, including deep learning-based ones, have a critical limitation in that they can only detect stego images that are created by a specific steganography method. In this paper, we propose a generalized steganalysis method that can model multiple types of stego images using deep learning. Through various experiments, we confirm the effectiveness of our approach and envision directions for future research. In particular, we show that our method can detect each type of steganography with the same level of accuracy as that of a steganalysis method dedicated to that type of steganography, thereby demonstrating the general applicability of our approach to multiple types of stego images.

Large-Memory Data Processing on a Remote Memory System using Commodity Hardware (대용량 메모리 데이타 처리를 위한 범용 하드웨어 기반의 원격 메모리 시스템)

  • Jung, Hyung-Soo;Han, Hyuck;Yeom, Heon-Y.
    • Journal of KIISE:Computer Systems and Theory
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    • v.34 no.9
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    • pp.445-458
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    • 2007
  • This article presents a novel infrastructure for large-memory database processing using commodity hardware with operating system support. We exploit inexpensive PCs and a high-speed network capable of Remote Direct Memory Access (RDMA) operations to build a new memory hierarchy between fast volatile memory and slow disk storage. The new memory hierarchy guarantees a reasonable response time, and its storage size enables us to run large-memory database systems with little performance degradation. The proposed architecture has two main components: (1) a remote memory system inside the Linux kernel to manage other computers' memory pages efficiently and (2) a remote memory pager responsible for manipulating remote read/write operations on remote memory pages. We insist that the proposed architecture is practical enough to support the rigorous demands of commercial in-memory database systems by demonstrating the performance of publicly available main-memory databases (e.g., MySQL) on our prototyped system. The experimental results show very interesting results from the TPC-C benchmark.