• Smart Structures and Systems
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• v.23 no.1
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• pp.71-79
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• 2019

In general, it may be advantageous to measure the pressure pulsation near a valve to detect a valve defect in a linear compressor. However, the acceleration signals are more advantageous for rapid classification in a mass-production line. This paper deals with the performance improvement of fault classification using only the compressor-shell acceleration signal based on the relation between the refrigerant pressure pulsation and the shell acceleration of the compressor. A transfer function was estimated experimentally to take into account the signal noise ratio between the pressure pulsation of the refrigerant in the suction pipe and the shell acceleration. The shell acceleration signal of the compressor was modified using this transfer function to improve the defect classification performance. The defect classification of the modified signal was evaluated in the acceleration signal in the frequency domain using Fisher's discriminant ratio (FDR). The defect classification method was validated by experimental data. By using the method presented, the classification of valve defects can be performed rapidly and efficiently during mass production.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.73-76
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• 2018

A Gaussian noise is caused by surrounding environment or channel interference when transmitting image. The noise reduces not only image quality degradation but also high-level image processing performance. The Non-Local Means (NLM) filter finds similarity in the neighboring sets of pixels to remove noise and assigns weights according to similarity. The weighted average is calculated based on the weight. The NLM filter method shows low noise cancellation performance and high complexity in the process of finding the similarity using weight allocation and neighbor set. In order to solve these problems, we propose an algorithm that shows an excellent noise reduction performance by using Summed Square Image (SSI) to reduce the complexity and applying the weighting function based on a cosine Gaussian kernel function. Experimental results demonstrate the effectiveness of the proposed algorithm.

• Journal of information and communication convergence engineering
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• v.22 no.2
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• pp.98-108
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• 2024

Scrypt is a password-based key derivation function proposed by Colin Percival in 2009 that has a memory-hard structure. Scrypt has been intentionally designed with a memory-intensive structure to make password cracking using ASICs, GPUs, and similar hardware more difficult. However, in this study, we thoroughly analyzed the operation of Scrypt and proposed strategies to maximize computational parallelism in GPU environments. Through these optimizations, we achieved an outstanding performance improvement of 8284.4% compared with traditional CPU-based Scrypt computations. Moreover, the GPU-optimized implementation presented in this paper outperforms the simple GPU-based Scrypt processing by a significant margin, providing a performance improvement of 204.84% in the RTX3090. These results demonstrate the effectiveness of our proposed approach in harnessing the computational power of GPUs and achieving remarkable performance gains in Scrypt calculations. Our proposed implementation is the first GPU implementation of Scrypt, demonstrating the ability to efficiently crack Scrypt.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.80-87
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• 2024

This paper focuses on improving accuracy in constrained computing settings by employing the ReLU (Rectified Linear Unit) activation function. The research conducted involves modifying parameters of the ReLU function and comparing performance in terms of accuracy and computational time. This paper specifically focuses on optimizing ReLU in the context of a Multilayer Perceptron (MLP) by determining the ideal values for features such as the dimensions of the linear layers and the learning rate (Ir). In order to optimize performance, the paper experiments with adjusting parameters like the size dimensions of linear layers and Ir values to induce the best performance outcomes. The experimental results show that using ReLU alone yielded the highest accuracy of 96.7% when the dimension sizes were 30 - 10 and the Ir value was 1. When combining ReLU with the Adam optimizer, the optimal model configuration had dimension sizes of 60 - 40 - 10, and an Ir value of 0.001, which resulted in the highest accuracy of 97.07%.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1195-1200
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• 2009

Two important concepts in VE are "function" and "cost." Cost can be expressed quantitatively. Unlike cost, the function can only be expressed qualitatively. Thus, to accurately evaluate the performance in VE analysis, it is required that the functional aspect should be considered a qualitative one. This study suggests a procedure of function oriented evaluation which can evaluate function enhancement of a VE proposal more logically and objectively. To conduct this study, problems were induced via case analysis, and solutions were found. In addition, the existing simple evaluation procedures were corrected, and a function enhancement evaluation procedure via function classification was suggested. For function classification, the use of the concepts, which were "intended function" and "additionally obtained function," was suggested. Function oriented evaluation procedure to VE proposals which is suggested in this study is expected to be a great help in treating valuable functions through VE job plan.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.1
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• pp.103-116
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• 2021

Analysis of runoff is substantial for effective water management in the watershed. Runoff occurs by reaction of a watershed to the rainfall and has non-linearity and uncertainty due to the complex relation of weather and watershed factors. ANN (Artificial Neural Network), which learns from the data, is one of the machine learning technique known as a proper model to interpret non-linear data. The performance of ANN is affected by the ANN's structure, the number of hidden layer nodes, learning rate, and activation function. Especially, the activation function has a role to deliver the information entered and decides the way of making output. Therefore, It is important to apply appropriate activation functions according to the problem to solve. In this paper, ANN models were constructed to estimate runoff with different activation functions and each model was compared and evaluated. Sigmoid, Hyperbolic tangent, ReLU (Rectified Linear Unit), ELU (Exponential Linear Unit) functions were applied to the hidden layer, and Identity, ReLU, Softplus functions applied to the output layer. The statistical parameters including coefficient of determination, NSE (Nash and Sutcliffe Efficiency), NSEln (modified NSE), and PBIAS (Percent BIAS) were utilized to evaluate the ANN models. From the result, applications of Hyperbolic tangent function and ELU function to the hidden layer and Identity function to the output layer show competent performance rather than other functions which demonstrated the function selection in the ANN structure can affect the performance of ANN.

• International Journal of Reliability and Applications
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• v.1 no.1
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• pp.81-87
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• 2000

One of the most important quantities in reliability theory is the expected number of renewals of a system during a given interval. This quantity, the renewal function, is used to determine the optimal preventive maintenance policy and to estimate the cost of a warranty. In this paper we study a parametric approach for a renewal function. The simulation study is presented to compare the relative performance of the introduced estimators of a renewal function. And we show that the proposed parametric estimator performs well.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.721-723
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• 2007

Commercial conductive metal inks are available, but metals used in these have unsuitable work function for efficient OLED device performance. Metals with low work function tend to oxidize easily, which makes it challenging to develop low work function metal inks. In this research we describe printed low work function Al cathode.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6A
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• pp.794-801
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• 2000

In this paper, the efficient new performance evaluation method for digital communication channels is suggested and verified its efficiency in terms of simulation run-tim for the digital satellite broadcasting satellite TV channel. In order to solve the difficulties of the existing Importance Sampling(IS) Technics, we adopted the discrete probability mass function(PMF) in the new method for estimating the statistical characteristics of received signals from the measured Nth order central moments. From the discrete probability mass function obtained with less number of the received signal than the one required in the IS technic, continuous cumulative probability function and its inverse function are exactly estimated by using interpolation and extrapolation technic. And the overall channel is simplified with encoding block, inner channel performance degra-dation modeing block which is modeled with the Uniform Random Number Generator (URNG) and concatenated Inverse Cummulative Pr bility Distribution function, and decoding block. With the simplified channel model, the overall performance evaluation can be done within a drastically reduced time. The simulation results applied to the nonlinear digital satellite broadcasting TV channel showed the great efficiency of the alogrithm in the sense of computer run time, and demonstrated that the existing problems of IS for the nonlinear satellite channels with coding and M-dimensional memory can be completely solved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.105-110
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• 2018

This paper compare the adaptive equalization performance of NM-MMA (Novel Mixed-MMA) algorithm which using the mixed const function by scaling factor values. The mixed cost function of NM-MMA composed of the appropriate weighted addition of gradient vector in the MMA and SE-MMA cost function, and updating the tap coefficient based on these function, it is possible to improve the convergence speed and MSE value of current algorithm. The computer simulation was performed in the same channel, step size, SNR environment by changing the scaling factor, and its performance were compared appling the equalizer output constellation, residual isi, MD, MSE, SER. As a result of computer simulation, the residual values of performance index were reduced in case of the scaling factor of MMA cost function was greater than the scaling factor of SE-MMA. and the convergence speed was improved in case of the scaling factor of SE-MMA was greater than the MMA.