• Journal of Digital Contents Society
• /
• v.14 no.1
• /
• pp.65-72
• /
• 2013

Current and future parallel computing model has been suggested for running and solving large-scale application problems such as climate, bio, cryptology, and astronomy, etc. Parallel computing is a form of computation in which many calculations are carried out simultaneously. And we are able to shorten the execution time of the program, as well as can extend the scale of the problem that can be solved. In this paper, we perform the actual cryptographic algorithms through parallel processing and evaluate its efficiency. Length of the key, which is stable criterion of cryptographic algorithm, judged according to the amount of complete enumeration computation. So we present a detailed procedure of DES key search cryptographic algorithms for executing of enumeration computation in parallel processing environment. And then, we did the simulation through applying to clustering system. As a result, we can measure the safety and solidity of cryptographic algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.26 no.6
• /
• pp.625-631
• /
• 2008

Correct evaluation of cut and fill volume of soil is one of the most important factors which controls construction cost in enormous construction sites. To achieve accurate computation of soil volume in construction site precise surveying is required, however most of construction sites adopt existing optical surveying instruments such as Total Station. The problem when using these optical instruments in construction sites is that these instruments take longer time in data acquisition. Due to insufficiency of computation time accurate and precise observation cannot be accomplished with these equipments. As a result roughly calculated earthwork volume may cause arguments between contractors and supervisors in the matter of reduction or increasement of total construction cost. In this study VRS-RTK Surveying is adopted to perform fast and accurate in-situ surveying for rapid computation of soil volume. This VRS-RTK Surveying system is proved to have more accurate three dimensional coordinates with high density and better economical solution with less manpower.

• Journal of Navigation and Port Research
• /
• v.33 no.3
• /
• pp.215-220
• /
• 2009

Container cranes are vulnerable structure to difficult weather conditions bemuse there is no shielding facility to protect them from strong wind. This study was carried out to analyze the effect of wind load on the structure of a container crane according to the change of the boom shape using wind tunnel test and computation fluid dynamics. And we provide a container crane designer with data which am be used in a wind resistance design of a container crane assuming that a wind load 75m/s wind velocity is applied in a container crane. In this study, we applied mean wind load conformed to 'Design Criteria of Wind Load' in 'Load Criteria of Building Structures' and an external fluid field was divided as interval of 10 degrees to analyze the effect according to a wind direction. In this conditions, we carried out the wind tunnel test and the computation fluid dynamic analysis and than we analyzed the wind load which was needed to design the container crane.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.11
• /
• pp.2721-2726
• /
• 2014

In a MOG algorithm using the GMM to subtract background, the model parameter computation and the object classification to be performed at every pixel require a huge computation and are the chief obstacles to its uses. This paper proposes a fast MOG algorithm that partly adopts the simple model parameter computation and the object classification skip on the basis of the object prediction. The former is applied to the pixels that gives little effect on the model parameter and the latter is applied to the pixels whose object prediction is firmly trusted. In comparative experiment between the conventional and proposed algorithms using videos, the proposed algorithm carries out the simple model parameter computation and the object classification skip over 77.75% and 92.97%, respectively, nevertheless it retains more than 99.98% and 99.36% in terms of image and moving object-unit average classification accuracies, respectively.

• Journal of KIISE:Databases
• /
• v.28 no.3
• /
• pp.430-448
• /
• 2001

In navigation system, a primary task is to compute the minimum cost route from the current location to the destination. One of major problems for navigation systems is that a significant amount of computation time is required when the digital road map is large. Since navigation systems are real time systems, it is critical that the path be computed while satisfying a time constraint. In this paper, we have developed a HiTi(Hierarchical MulTi) graph model for hierarchically structuring large digital road maps to speedup the minimum cost path computation. We propose a new shortest path algorithm named SPAH, which utilizes HiTi graph model of a digital road map for its computation. We prove that the shortest path computed by SPAH is the optimal. Our performance analysis of SPAH also showed that it significantly reduces the computation time over exiting methods. We present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.2
• /
• pp.365-372
• /
• 2000

he paper introduces evolutionary computing to Fractal Image Compression(FIC). In Fractal Image Compression(FIC) a partitioning of the image into ranges is required. As a solution to this problem there is a propose that evolution computation should be applied in image partitionings. Here ranges are connected sets of small square image blocks. Populations consist of $N_p$ configurations, each of which is a partitioning with a fractal code. In the evolution each configuration produces $\sigma$ children who inherit their parent partitionings except for two random neighboring ranges which are merged. From the offspring the best ones are selected for the next generation population based on a fitness criterion Collage Theorem. As the optimum image includes duplication in image data, it gets smaller in saving space more efficient in speed and more capable in image quality than any other technique in which other coding is used. Fractal Image Compression(FIC) using evolution computation in multimedia image processing applies to such fields as recovery of image and animation which needs a high-quality image and a high image-compression ratio.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.543-545
• /
• 2017

This paper describes the SAO hardware architecture design for high performance in-loop filters. SAO is an inner module of in-loop filter, which compensates for information loss caused by block-based image compression and quantization. However, HEVC's SAO requires a high computation time because it performs pixel-unit operations. Therefore, the SAO hardware architecture proposed in this paper is based on a $4{\times}4$ block operation and a 2-stage pipeline structure for high-speed operation. The information generation and offset computation structure for SAO computation is designed in a parallel structure to minimize computation time. The proposed hardware architecture was designed with Verilog HDL and synthesized with TSMC chip process 130nm and 65nm cell library. The proposed hardware design achieved a maximum frequency of 476MHz yielding 163k gates and 312.5MHz yielding 193.6k gates on the 130nm and 65nm processes respectively.

• Journal of KIISE:Software and Applications
• /
• v.32 no.2
• /
• pp.85-98
• /
• 2005

Recently, a lot of researches about mobile vision using Personal Digital Assistant(PDA) has been attempted. Many CPUs for PDA are integer CPUs, which have no floating-computation component. It results in slow computation of the algorithms peformed by vision system or image processing, which have much floating-computation. In this paper, in order to resolve this weakness, we propose the Client(PDA)/server(PC) architecture which is connected to each other with a wireless LAN, and we construct the system with pipelining processing using two CPUs of the Client(PDA) and the Server(PC) in image sequence. The Client(PDA) extracts tentative text regions using Edge Density(ED). The Server(PC) uses both the Multi-1.aver Perceptron(MLP)-based texture classifier and Connected Component(CC)-based filtering for a definite text extraction based on the Client(PDA)'s tentativel99-y extracted results. The proposed method leads to not only efficient text extraction by using both the MLP and the CC, but also fast running time using Client(PDA)/server(PC) architecture with the pipelining processing.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.11
• /
• pp.377-386
• /
• 2020

Mobile cloud computing involves mobile or embedded devices as clients, and features small devices with constrained resource and low availability. Due to the fast expansion of smart phones and smart peripheral devices, researches on mobile cloud computing attract academia's interest more than ever. Computation offloading, or code offloading, enhances the performance of computation by migrating a part of computation of a mobile system to nearby cloud servers with more computational resources through wired or wireless networks. Code offloading is considered as one of the best approaches overcoming the limited resources of mobile systems. In this paper, we analyze the factors and the performance of code offloading, especially focusing on static program partitioning and data protection. We survey state-of-the-art researches on analyzed topics. We also describe directions for future research.

• Journal of KIISE
• /
• v.42 no.7
• /
• pp.919-928
• /
• 2015

In recent years, many research efforts have been made on privacy-preserving data mining (PPDM) in data of large volume. In this paper, we propose a PPDM solution based on principal component analysis (PCA), which can be widely used in computing correlation among sensitive data sets. The general method of computing PCA is to collect all the data spread in multiple nodes into a single node before starting the PCA computation; however, this approach discloses sensitive data of individual nodes, involves a large amount of computation, and incurs large communication overheads. To solve the problem, in this paper, we present an efficient method that securely computes PCA without the need to collect all the data. The proposed method shares only limited information among individual nodes, but obtains the same result as that of the original PCA. In addition, we present a dimensionality reduction technique for the proposed method and use it to improve the performance of secure similar document detection. Finally, through various experiments, we show that the proposed method effectively and efficiently works in a large amount of multi-dimensional data.