• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.666-672
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• 2016

Recently the fingerprint is widely used as one of biometrics to improve the security of financial mobile applications, because of its user convenience and high recognition rate. However, in order to apply fingerprint algorithms to finance and security applications, the recognition rate and processing speed of the fingerprint algorithms have to be improved further. In this paper, we propose the parallel fingerprint enhancement algorithm on general-purpose computing on graphics processing unit (GPGPU) using OpenCL. We discuss the analysis of the parallelism in the fingerprint algorithm as well as the exploration of optimization parameters of the parallel fingerprint algorithm to improve the performance. The experimental results showed that the execution of parallel fingerprint enhancement algorithm on GPGPUs was accelerated from 29.4 upto 69.2 times compared with the execution of the original one on the host CPUs.

• Journal of Computing Science and Engineering
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• v.5 no.1
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• pp.1-18
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• 2011

As the first step toward real-time multi-core computing, this paper presents a novel approach to bounding the worst-case performance for threads running on multi-core processors with shared L2 instruction caches. The idea of our approach is to compute the worst-case instruction access interferences between different threads based on the program control flow information of each thread, which can be statically analyzed. Our experiments indicate that the proposed approach can reasonably estimate the worst-case shared L2 instruction cache misses by considering the inter-thread instruction conflicts. Also, the worst-case execution time (WCET) of applications running on multi-core processors estimated by our approach is much better than the estimation by simply assuming all L2 instruction accesses are misses.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.125-129
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• 2016

In this paper, we propose an efficient dynamic workload balancing strategy which improves the performance of high-performance computing system. The key idea of this dynamic workload balancing strategy is to minimize execution time of each job and to maximize the system throughput by effectively using system resource such as CPU, memory. Also, this strategy dynamically allocates job by considering demanded memory size of executing job and workload status of each node. If an overload node occurs due to allocated job, the proposed scheme migrates job, executing in overload nodes, to another free nodes and reduces the waiting time and execution time of job by balancing workload of each node. Through simulation, we show that the proposed dynamic workload balancing strategy based on CPU, memory improves the performance of high-performance computing system compared to previous strategies.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.131-134
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• 2005

This paper presents a computer-aided simulation and robotic-assisted execution technology of external fixation method to achieve fracture reduction and deformity correction in long bones. Combining the kinematic analysis with a graphic model of the tibia and the fixator allowed 3D simulation and visualization of the adjustments required to reduce fracture or correct bone deformity as a pre-operative planning tool. The developed robot model provided accurate deformity correction with small residual deformity based on the results of the planning. By incorporating the robot model with image-guided system and computer-aided planning, the integrated system could be useful for computer-aided pre-operative planning and robotic-assisted execution in fracture treatment and bone deformity surgery.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.290-296
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• 2022

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

• International conference on construction engineering and project management
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• 2015.10a
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• pp.656-657
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• 2015

Recently, Multi-Objective Optimization of design elements is an important issue in building design. Design variables that considering the specificities of the different environments should use the appropriate algorithm on optimization process. The purpose of this study is to compare and analyze the optimal solution using three evolutionary algorithms and energy modeling simulation. This paper consists of three steps: i)Developing three evolutionary algorithm model for optimization of design elements ; ii) Conducting Multi-Objective Optimization based on the developed model ; iii) Conducting comparative analysis of the optimal solution from each of the algorithms. Including Non-dominated Sorted Genetic Algorithm (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO) and Random Search were used for optimization. Each algorithm showed similar range of result data. However, the execution speed of the optimization using the algorithm was shown a difference. NSGA-II showed the fastest execution speed. Moreover, the most optimal solution distribution is derived from NSGA-II.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.259-262
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• 2015

Due to the labor-intensiveness, high investment cost, long execution time, frequent change orders, and many stakeholders in a BIM project, a BIM manager is bound to face a lot of risks to make decisions in cost managing process. Since the productivity of a BIM team will affect the execution cost, this study investigates a simple method of assessing the productivity of a BIM team using the working timesheet records of the team. In this research, the productivity of a BIM team is defined as the effective working floor area (in square meters) of BIM uses per labor-time (in man-months) spent by the team. After the applicability of this method is tested by regression analysis using data from 5 real BIM projects in the construction phase, it is found that the simple productivity definition adopted in the method, although easy-to-implement, does not produce a statistically constant productivity value. More research is therefore needed in the future to devise better indicator(s) for assessing the productivity of a BIM team.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.10a
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• pp.17-24
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• 1994

The pre- and post-processor for finite element structural analysis considering the user-friendly device are developed by using GUI. These can be used on WINDOWS' environment which is realized the multi-tasking and the concurrency by object-oriented paradigm. They are designed to control integratedly the pre-processing, execution and the post-processing of the finite element structural analysis program on multiple windows. These object-oriented modeling approach can be used for complex integrated engineering systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.513-514
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• 2012

• Journal of Korean Institute of Industrial Engineers
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• v.1 no.1
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• pp.87-92
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• 1975

Three approximation methods for generating outcomes on Poisson random variables are discussed. A comparison is made to determine which method requires the least computer execution time and to determine which is the most robust approximation. Results of the comparison study suggest the method to choose for the generating procedure depends on the mean value of Poisson random variable which is being generated.