• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.161-172
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• 2021

Neuromorphic architecture is drawing attention as a next-generation computing that supports artificial intelligence technology with low energy. However, FPGA embedded boards based on Neuromorphic architecturehave limited resources due to size and power. In this paper, we compared and evaluated the image reduction method using the interpolation method that rescales the size without considering the feature points and the DCT (Discrete Cosine Transform) method that preserves the feature points as much as possible based on energy. The scaled images were compared and analyzed for accuracy through CNN (Convolutional Neural Networks) in a PC environment and in the Nengo framework of an FPGA embedded board.. As a result of the experiment, DCT based classification showed about 1.9% higher performance than that of interpolation representation in both CNN and FPGA nengo environments. Based on the experimental results, when the DCT method is used in a limited resource environment such as an embedded board, a lot of resources are allocated to the expression of neurons used for classification, and the recognition rate is expected to increase.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.212-216
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• 2001

Because conventional switching converters have been usually using unbalanced circuit topologies, parasitic capacitance between the drain/collector of an active switch and the frame ground through its heat sink may generate the common-mode conducted noise. We have proposed a balanced switching converter circuit, which is an effective way to reduce the common-mode conducted noise. As an example, a boost converter version of the balanced switching converter was presented and the mechanism of the common-mode noise reduction was explained using equivalent circuits. This paper extends the concept of the balanced switching converter circuit and presents a buck-boost converter version of the balanced switching converter. The feature of common-mode noise reduction is confirmed by experimental results and the mechanism of the common-mode noise reduction is explained using equivalent circuits.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.745-749
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• 1998

Mathematical morphology (MM) has been introduced as a powerful tool for studying the geometrical properties of images, MM is a good approach to digital image processing , which is based on the shape feature. The MM operators such as dilation, erosion, closing and opening have been applied successfully to image noise reduction. The MM filters can easily filter the noise when the noise factors are known. However it is very difficult to reduce the noise when images are ambiguous, because the boundary between the noise and object is vague. In this paper, we propose a new method to reduce noise from ambiguous images by using Fuzzy Mathematical Morphology (FMM) operators. Performance evaluation via simulations show that the FMM filters efficiently reduce the image noise. Furthermore, the FMM filters show a good performance compared with the conventional filters.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.69-72
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• 2003

The paper considers partial least squares (PLS) as a new dimension reduction technique for the feature vector to overcome the small sample size problem in face recognition. Principal component analysis (PCA), a conventional dimension reduction method, selects the components with maximum variability, irrespective of the class information. So PCA does not necessarily extract features that are important for the discrimination of classes. PLS, on the other hand, constructs the components so that the correlation between the class variable and themselves is maximized. Therefore PLS components are more predictive than PCA components in classification. The experimental results on Manchester and ORL databases show that PLS is to be preferred over PCA when classification is the goal and dimension reduction is needed.

• Nuclear Engineering and Technology
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• v.38 no.3
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• pp.225-230
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• 2006

With the advent of inexpensive computing power over the past two decades, applications of Monte Carlo radiation transport techniques have proliferated dramatically. At Los Alamos, the Monte Carlo codes MCNP5 and MCNPX are used routinely on personal computer platforms for radiation shielding analysis and dosimetry calculations. These codes feature a rich palette of variance reduction (VR) techniques. The motivation of VR is to exchange user efficiency for computational efficiency. It has been said that a few hours of user time often reduces computational time by several orders of magnitude. Unfortunately, user time can stretch into the many hours as most VR techniques require significant user experience and intervention for proper optimization. It is the purpose of this paper to outline VR strategies, tested in practice, optimized for several common radiation shielding tasks, with the hope of reducing user setup time for similar problems. A strategy is defined in this context to mean a collection of MCNP radiation transport physics options and VR techniques that work synergistically to optimize a particular shielding task. Examples are offered in the areas of source definition, skyshine, streaming, and transmission.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.535-538
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.

• ETRI Journal
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• v.34 no.4
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• pp.503-510
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• 2012

We analyze the relationship between channel coherence bandwidth and two complexity-reduced lattice reduction aided detection (LRAD) algorithms for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems in correlated fading channels. In both the adaptive LR algorithm and the fixed interval LR algorithm, we exploit the inherent feature of unimodular transformation matrix P that remains the same for the adjacent highly correlated subcarriers. Complexity simulations demonstrate that the adaptive LR algorithm could eliminate up to approximately 90 percent of the multiplications and 95 percent of the divisions of the brute-force LR algorithm with large coherence bandwidth. The results also show that the adaptive algorithm with both optimum and globally suboptimum initial interval settings could significantly reduce the LR complexity, compared with the brute-force LR and fixed interval LR algorithms, while maintaining the system performance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.4 s.97
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• pp.452-456
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• 2005

Cyclone is widely adopted in the vacuum cleaner, because of the simple structure, the high dust collection efficiency and its transparency feature, which can be shown to the customer. At past times, cyclone performance was represented by collection efficiency, flow rate, pressure drop etc. At recent times the noise problem is getting important as cyclone comes into home-appliances. In this paper, pressure drop of cyclone and it's noise were measured at the variation of the cyclone structure and the main sources of cyclone peak noise was found by experimental and numerical analysis. In addition, the structure for peak noise reduction was suggested and it is beneficial both pressure drop and noise reduction.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1121-1123
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• 2006

Tilting trains are now an established feature of railway operations throughout the world. For intercity traffic, tilt provides operators with increasing speeds, and therefore enhanced competitiveness, on existing routes where insufficient traffic or a lack of funds precludes the construction of a dedicated new high-speed railway. This paper explains the reduction effects of journey time with the Korean tilting train. The Korean Tilting Train express (TTX) project has been carried out to develop alt the core technologies related to tilting train and infra-technology to provide high speed inter-city service with the speed of 180 km/h as well as maintenance-free technology for conventional railway system. In order to simulate we considered 5 conventional railway. As a results of simulation, we found out the tilting train has very high efficiency(reduction rate 20-30%).

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.135-140
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• 2007

In this paper, an Improved Dimension Reduction(IDR) method is proposed for uncertainty quantification that employes Kriging interpolation technic. It has been acknowledged that the DR method is accurate and efficient for assessing statistical moments and reliability due to the sensitivity free feature. However, the DR method has a number of drawbacks such as instability and inaccuracy for problems with increased nonlineality. In this paper, improved DR is implanted by three steps. First, the Kriging interpolation method is used to accurately approximate the responses. Second, 2N+1 and 4N+1 ADOEs are proposed to maintain high accuracy of the method for UQ analysis. Third, numerical integration scheme is used with accurate but free response values at any set of integration points of the surrogated model.