• International journal of advanced smart convergence
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• v.6 no.4
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• pp.67-72
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• 2017

Deep learning neural network becomes very popular nowadays due to the reason that it can learn a very complex dataset such as the image dataset. Although deep learning neural network can produce high accuracy on the image dataset, it needs a lot of time to reach the convergence stage. To solve the issue, we have proposed a scaling method to improve the neural network to achieve the convergence stage in a shorter time than the original method. From the result, we can observe that our algorithm has higher performance than the other previous work.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.12
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• pp.736-748
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• 2003

Dynamic voltage scaling(DVS), which adjusts the clock speed and supply voltage dynamically, is an effective technique in reducing the energy consumption of embedded real-time systems. The energy efficiency of a DVS algorithm largely depends on the performance of the slack estimation method used in it. In this paper, we propose novel DVS algorithms for periodic hard real-time tasks based on an improved slack estimation algorithm. Unlike the existing techniques, the proposed method can be applied to most priority-driven scheduling policies. Especially, we apply the proposed slack estimation method to EDF and RM scheduling policies. The experimental results show that the DVS algorithms using the proposed slack estimation method reduce the energy consumption by 20∼40 % over the existing DVS algorithms.

• Structural Engineering and Mechanics
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• v.55 no.5
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• pp.1055-1086
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• 2015

The dynamic response of two-dimensional unbounded domain on the rigid bedrock in the time domain is numerically obtained. It is realized by the modified scaled boundary finite element method (SBFEM) in which the original scaling center is replaced by a scaling line. The formulation bases on expanding dynamic stiffness by using the continued fraction approach. The solution converges rapidly over the whole time range along with the order of the continued fraction increases. In addition, the method is suitable for large scale systems. The numerical method is employed which is a combination of the time domain SBFEM for far field and the finite element method used for near field. By using the continued fraction solution and introducing auxiliary variables, the equation of motion of unbounded domain is built. Applying the spectral shifting technique, the virtual modes of motion equation are eliminated. Standard procedure in structural dynamic is directly applicable for time domain problem. Since the coefficient matrixes of equation are banded and symmetric, the equation can be solved efficiently by using the direct time domain integration method. Numerical examples demonstrate the increased robustness, accuracy and superiority of the proposed method. The suitability of proposed method for time domain simulations of complex systems is also demonstrated.

• Journal of the Korea Society of Computer and Information
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• v.3 no.3
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• pp.99-106
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• 1998

This Paper proposes a novel fractal image method for image communication to shorten time to take on fractal encoding by using limited search area method and scaling method First, the original image is contracted respectively by half and by quarter with the scaling method. And then, the corresponding domain block of the quarter-sized image which is most similar with one range block of the half-sized image is searched within the limited area in order to reduce the encoding time extremely As the result of the evaluation, the proposed algorithm provided much shorter encoding time and better compression ratio with a little degradation of the decoded image quality than Jacquin's method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.380-390
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• 1998

In the present work a finite element formulation using dynamic explicit time integration scheme is used for numerical analysis of auto-body panel stamping processes. The lumping scheme is employed for the diagonal mass matrix and linearizing dynamic formulation. A contact scheme is developed by combining the skew boundary condition and direct trial-and-error method. In this work, for economic analysis the faster punch velocity and the mass scaling method are introduced. To investigate the effects of punch velocity and mass scaling, the various values of punch velocity and the various mass scalings are used for numerical analysis. Computations are carried out for analysis of complicated auto-body panel stamping processes such as forming of an oil pan and a fuel tank.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.135-140
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• 1999

This paper describes a affine transform coding which is reducing long time to take on image encoding by using scaling method and limited search area technique. For evaluating its performance, the proposed algorithm compare with Jacquin's method using traditional affine transform coding methods. Simulation results, the proposed algorithm considerably reduces encoding time by using scaling method and limited search area method. Also, the proposed algorithm provides much shorter encoding time with a little degradation of the decoded image quality than Jacquin's method.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.4
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• pp.517-536
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• 2020

The radionuclide inventory in radioactive waste from nuclear power plants should be determined to secure the safety of final repositories. As an alternative to time-consuming, labor-intensive, and destructive radiochemical analysis, the indirect scaling factor (SF) method has been used to determine the concentrations of difficult-to-measure radionuclides. Despite its long history, the original SF methodology remains almost unchanged and now needs to be improved for advanced SF implementation. Intense public attention and interest have been strongly directed to the reliability of the procedures and data regarding repository safety since the first operation of the low- and intermediate-level radioactive waste disposal facility in Gyeongju, Korea. In this review, statistical methodologies for SF implementation are described and evaluated to achieve reasonable and advanced decision-making. The first part of this review begins with an overview of the current status of the scaling factor method and global experiences, including some specific statistical issues associated with SF implementation. In addition, this review aims to extend the applicability of SF to the characterization of large quantities of waste from the decommissioning of nuclear facilities.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.438-440
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• 2004

Energy consumption has become an increasingly important consideration in designing real-time embedded systems. In this paper, we propose a voltage scaling method to reduce energy consumption in fixed priority real-time systems using variable voltage processors. The Hyperperiod of tasks is divided into dimains. The most suitable voltage of each domain is determined off-line and stored in a table. During task execution, the voltage of processor is adjusted according to the information of the table. A simulation result shows that the proposed method can reduce 80% of power consumption in comparison to no power management. The difference to the optimal EDF based method is only 5%.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.73-82
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• 2022

Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1379-1382
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• 2003

Recently, mobile embedded systems used widly in various applications. Managing power consumption is becoming a matter of primary concern because those systems use limited power supply. As an approach reduce power consumption, voltage can be scaled down. according to the execution time and deadline. By reducing the supplying voltage to 1/N power consumption can be reduced to 1/N. DPM-S is a well known method for dynamic voltage scaling. In this paper, we enhanced DPM-S by using average execution time aggressively. The frequency of processor is calculated based in average execution time instead of worst case execution time. Simulation results show that our method achieve up to 5％ energy savings than DPM-S.