• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.413-423
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• 2003

The CMA algorithmis most widely investigated blind algorithm and the most widely used one in practice. But, since nonlinear CM cost function have not closed form solution about the optimum weight. There have been difficultiesto analyze the CMA equalizer's theoretical performance. Recently, Zeng presents the notable theoretical resultabout the MSE of CM-minimizing estimators for the FIR linear channel in the presence of AWGN. Through this method, It wouldbe possible to campare the theoretical performance between CMA and Wiener equalizer in terms of MSE. In this paper, based on Zeng's method, we first calculate the theoretical MSE bound of CMA equalizer in partial response channel which is widely used in HDD, digital VCR such as high-density digital recording.playback systems. We confirmedthis result withthe computer simulation. Except this, we also performedthe theoretical and simulation analysis about the modified CMA equalizer, which was proposed to improve the performance of CMA equalizer in partial response channel. Finally, we compare and evaluate the performance analysis results between CMA and Modified CMA equalizer.

• Resources Recycling
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• v.29 no.3
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• pp.11-23
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• 2020

This study aims to investigate breakage and liberation characteristics of iron ore from Shinyemi mine, Jeongseon by ball mill. Parameters of breakage functions for three grade samples of iron ore were obtained using single-sized-feed breakage test and back-calculation based on nonlinear programming. The results showed that with the increase in the grade of iron ore, the breakage rate factor decrease whereas the particle size sensitivity decreases. This results from retardation of microcrack-propagation by magnetite grain in the ore. Breakage distribution analysis showed that the breakage mechanism appear to be impact fracture dominant with the increase of grade owing to the stress distribution effect by magnetite grain. Degree of liberation (DOL) increased with the increase in grade and decrease in particle size, respectively. Using the breakage function and size-DOL relationship, a model that can predict time-dependent-DOL is established. When scale-up factors from operating condition are available, the model is expected to be capable of predicting size and DOL with time in actual mining process.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.3
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• pp.133-147
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• 2005

Various types of ray-tracing methods are used to predict the quantity measures of radiation illumination, the uniformity of illumination, radiation performance of LCD BLU(Hack-Light Unit). The uniformity of radiation illumination is one of the most important design factor of BLU and is usually controlled by the diffusive-ink pattern printed on the bottom of light-guide panel of BLU. Therefore it is desirable to produce an improved (ideally, the optimal) ink pattern to achieve the best uniformity of radiation illumination. In this paper, we applied the Welder-Mead simplex-search method among various direct search method to compute the optimal ink pattern. Direct search methods are widely used to optimize the functions which are often highly nonlinear, unpredictably discontinuous, and nondifferentiable, The ink-pattern controlling the uniformity of radiation illumination is one type of these functions. In this paper, we found that simplex search methods are well suited to computing the optimal diffusive-ink pattern. In extensive numerical testing, we have found the simplex search method to be reasonably efficient and reliable at computing the optimal diffusive-ink pattern. The result also suggests that optimization can improve the functionality of simulation tools which are used to design LCD BLU.

• Journal of Korean Society on Water Environment
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• v.34 no.4
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• pp.375-381
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• 2018

The monitoring of phytoplankton biomass and community structure is essential as a first step to control the harmful cyanobacterial blooms in freshwater systems, such as seen in rivers and lakes, due to the process of eutrophication and climate change. In order to quantify the biomass of phytoplankton with a wide range in size and shape, the measurement of cell biovolume along with cell density is required for a comprehensive review on this issue. However, most routine monitoring programs preserve the gathered phytoplankton samples before analysis using chemical additives, because of the constraint of time and the number of samples. The purpose of this study was to investigate the cell biovolume change characteristics of six cyanobacterial species, which are common bloom-causing cyanobacteria in the Nakdong River, after the preservation with Lugol's iodine solution. All species showed a statistically significant difference after the addition of Lugol's iodine solution compared to the live cell biovolume, and the cell biovolume decreased to the level of 34.0 ~ 56.3 % at maximum in each species after the preservation. The nonlinear regression models for determining the shrinkage ratio by a preservation period were derived by using the cell biovolume measured until 180 days preservation of each target species, and the equation to convert the cell biovolume measured after preservation for a certain period to the cell biovolume of viable cell was derived using that formula. The conversion equation derived from this study can be used to estimate the actual cell biovolume in the natural environment at the time of sampling, by using the measured biovolume after the preservation in the phytoplankton monitoring. Moreover this is expected to contribute to the final interpretation of the water quality and aquatic ecosystem impacts due to the cyanobacterial blooms.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.3068-3084
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• 2021

Investigations of large commercial aircraft impact effect on nuclear power plant (NPP) buildings have been drawing extensive attentions, particularly after the 9/11 event, and this paper aims to experimentally assess the damage and vibrations of NPP buildings subjected to aircraft crash. In present Part I, two shots of reduce-scaled model test of aircraft impacting on NPP building were carried out. Firstly, the 1:15 aircraft model (weighs 135 kg) and RC NPP model (weighs about 70 t) are designed and prepared. Then, based on the large rocket sled loading test platform, the aircraft models were accelerated to impact perpendicularly on the two sides of NPP model, i.e., containment and auxiliary buildings, with a velocity of about 170 m/s. The strain-time histories of rebars within the impact area and acceleration-time histories of each floor of NPP model are derived from the pre-arranged twenty-one strain gauges and twenty tri-axial accelerometers, and the whole impact processes were recorded by three high-speed cameras. The local penetration and perforation failure modes occurred respectively in the collision scenarios of containment and auxiliary buildings, and some suggestions for the NPP design are given. The maximum acceleration in the 1:15 scaled tests is 1785.73 g, and thus the corresponding maximum resultant acceleration in a prototype impact might be about 119 g, which poses a potential threat to the nuclear equipment. Furthermore, it was found that the nonlinear decrease of vibrations along the height was well reflected by the variations of both the maximum resultant vibrations and Cumulative Absolute Velocity (CAV). The present experimental work on the damage and dynamic responses of NPP structure under aircraft impact is firstly presented, which could provide a benchmark basis for further safety assessments of prototype NPP structure as well as inner systems and components against aircraft crash.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.707-725
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• 2021

Energy management systems (EnMS) contribute to sustainable energy saving and greenhouse gas reduction by emphasizing the role of energy management in production-oriented economies. Although understanding the methods used to measure energy performance is a key factor in constructing successful EnMS, few attempts have been made to examine these methods, their applicability, and their utility in practice. To fill this research gap, this study aimed to deepen the understanding of energy performance measures by focusing on four energy performance indicators (EnPIs) proposed by ISO 50006, namely the measured energy value, ratio between measured values, linear regression model, and nonlinear regression model. This paper presents policy and managerial implications to facilitate the effective use of these measures. An analytic hierarchy process (AHP) analysis was conducted with 41 experts to analyze the preference for EnPIs and their key selection criteria by the industry sector, and organization and user type. The findings suggest that the most preferred EnPI is the ratio between the measured values followed by the measured energy value. The ease of use was considered to be most important while choosing EnPIs.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.21-33
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• 2022

Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.55-65
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• 2006

This paper presents the closing analysis of a symmetric steel cable-stayed bridge erected by a free cantilever method. Two independent structural systems are formed before the closing procedure of a bridge is performed, and thus the compatibility conditions for vertical displacement and rotational angle are not satisfied at the closing section without the application of proper sectional forces. Since, however, it is usually impossible to apply sectional forces at the closing section, the compatibility conditions should be satisfied by proper external forces that can be actually applicable to a bridge. Unstrained lengths of selected cables and the pull-up force of a derrick crane are adjusted to satisfy nonlinear compatibility conditions, which are solved iteratively by the Newton-Raphson method. Cable members are modeled by the elastic catenary cable elements, and towers and main girders are discretized by linear 3-D frame elements. The sensitivities of displacement with respect to the unstrained lengths of selected cables and the pull-up force of the derrick crane are evaluated by the direct differentiation of the equilibrium equation. A Monte-Carlo simulation approach is proposed to estimate expected construction errors for a given confidence level. The proposed method is applied to the second Jindo Grand Bridge to demonstrate its validity and effectiveness.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.70-78
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• 2023

The ordinary concentrically braced frame has an advantage of having simple design procedure. For this reason, it has been widely used for the small-sized frame structures subject to moderate or lower magnitude earthquake, even though its seismic performance against the earthquake load is not much effective compared to that of other frame systems. To enhance seismic performance of the ordinary concentrically braced frame where the bracing has a weakness for compressive behavior under lateral earthquake, seismic retrofitting by viscous damper has been commonly introduced. However, the viscous damper, itself, generally does not have stiffness for restoring the structure to the original position. This may cause residual displacement to the structure. In this paper, a self-centering viscous damper system in which upper and lower beams having flexural rigidity play a role as a nonlinear-elastic spring, restoring the spring-damper system subject to external displacement history to its original location, is developed. The numerical analysis for a simplified frame structure shows how including the developed self-centering viscous damper system leads to an enhanced seismic performance of the frame structure through energy dissipation during earthquake excitation.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.