• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.677-682
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• 2003

The non-linear dynamic characteristics of a semi-circular pipe conveying fluid are investigated when the pipe is clamped at both ends. To consider the geometric non-linearity for the radial and circumferential displacements, this study adopts the Lagrange strain theory for large deformation and the extensible dynamics based on the Euler-Bernoulli beam theory for slenderness assumption. By using the Hamilton principle, the non-linear partial differential equations are derived for the in-plane motions of the pipe, considering the fluid inertia forces as a kind of non-conservative forces. The linear and non-linear terms in the governing equations are compared with those in the previous study, and some significant differences are discussed. To investigate the dynamic characteristics of the system, the discretized equations of motion are derived form the Galerkin method. The natural frequencies varying with the flow velocity are computed fen the two cases, which one is the linear problem and the other is the linearized problem in the neighborhood of the equilibrium position. Finally, the time responses at various flow velocities are directly computed by using the generalized- method. From these results, we should to describe the non-linear behavior to analyze dynamics of a semi-circular pipe conveying fluid more precisely.

• Industrial Engineering and Management Systems
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• v.9 no.1
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• pp.10-19
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• 2010

This paper presents an extended computing procedure for the global optimization of the triple response system (TRS) where the response functions are nonconvex (nonconcave) quadratics and the input factors satisfy a radial region of interest. The TRS arising from response surface modeling can be approximated using a nonlinear mathematical program involving one primary (objective) function and two secondary (constraints) functions. An optimization algorithm named triple response surface algorithm (TRSALG) is proposed to determine the global optimum for the nondegenerate TRS. In TRSALG, the Lagrange multipliers of target (secondary) functions are computed by using the Hooke-Jeeves search method, and the Lagrange multiplier of the radial constraint is located by using the trust region (TR) method at the same time. To ensure global optimality that can be attained by TRSALG, included is the means for detecting the degenerate case. In the field of numerical optimization, as the family of TR approach always exhibits excellent mathematical properties during optimization steps, thus the proposed algorithm can guarantee the global optimal solution where the optimality conditions are satisfied for the nondegenerate TRS. The computing procedure is illustrated in terms of examples found in the quality literature where the comparison results with a gradient-based method are used to calibrate TRSALG.

• ETRI Journal
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• v.32 no.4
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• pp.577-587
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• 2010

The layered coding structure of scalable video coding (SVC) with adaptive inter-layer prediction causes noticeable computational complexity increments when compared to existing video coding standards. To lighten the computational complexity of SVC, we present a fast algorithm to speed up the inter-mode decision process. The proposed algorithm terminates inter-mode decision early in the enhancement layers by estimating the rate-distortion (RD) cost from the macroblocks of the base layer and the enhancement layer in temporal, spatial, and inter-layer directions. Moreover, a search range decision algorithm is also proposed in this paper to further increase the motion estimation speed by using the motion vector information from temporal, spatial, or inter-layer domains. Simulation results show that the proposed algorithm can determine the best mode and provide more efficient total coding time saving with very slight RD performance degradation for spatial and quality scalabilities.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.3
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• pp.1-8
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• 2004

The anomalous behavior of the 1/f noise of halo or pocket ion implanted MOSFETs is investigated. The model for the anomalous 1/f noise behaviors of MOSFETs, which consist of inhomogeneous conductance along the channel is improved within a regional approximation as previous works and presented in a fen directly applicable to halo MOSFETs. The presented model reduces to the previous results, discussed in the linear region operation, for small drain bias. Comparisons with experimental results show that the 1/f model based on the regional approach can be applicable for limited ranges, especially for sufficiently large gate bias voltages.

• Membrane and Water Treatment
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• v.10 no.3
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• pp.239-244
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• 2019

Plating wastewater containing various heavy metals can be produced by several industries. Specifically, we focused on the removal of copper (Cu2+) and nickel (Ni+) ions from the plating wastewater because all these ions are strictly regulated when discharged into watershed in Korea. The application of both nanofiltration (NF) and reverse osmosis (RO) technologies for the treatment of wastewater containing copper and nickel ions to reduce fresh water consumption and environmental degradation was investigated. In this work, the removal of copper (Cu2+) and nickel (Ni+) ions from synthetic water was studied on pilot scale remove by before using two commercial nanofiltration (NF) and reverse osmosis(RO) spiral-wound membrane modules (NE2521-90 and RE2521-FEN by Toray Chemical). The influence of main operating parameters such as feed concentration on the heavy metals rejection and permeate flux of both membranes, was investigated. Synthetic plating wastewater samples containing copper ($Cu^{2+}$) and nickel ($Ni^{2+}$) ions at various concentrations(1, 20, 100, 400 mg/L) were prepared and subjected to treatment by NF and RO in the pilot plant. The results showed that NF, RO process, with 98% and 99% removal for copper and nickel, respectively, could achieve high removal efficiency of the heavy metals.

• Research in Mathematical Education
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• v.22 no.3
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• pp.153-174
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• 2019

Measuring alignment of various educational components is an important issue in educational research because with aligned educational system, we can have clear expectations about what to teach and assess. In this study, we examined the alignment between mathematics curriculum standards and college entrance examinations from Korea and China. The results indicate that curriculum standards and high stakes assessments from both countries are not well aligned to each other. Their Surveys of Enacted Curriculum (SEC) indices were lower than what previous studies have found and the critical values (Fulmer, 2011; Liu & Fulmer, 2008; Liu et al., 2009). There are several topics that are not assessed in both countries' national assessments. Also, discrepancies between the most frequently covered topics in the curriculum standards and the most frequently assessed mathematical topics in the national assessments caused topic level misalignment. We also found misalignment in cognitive level. Both national assessments included more perform procedures and demonstrate understanding items than their respective curriculum standards. Thus, previous findings about the inclusion of more items with higher cognitive demand in assessments is only partially true for either country. With these results, it is difficult to say that whether mathematical topics in the curriculum standards appropriately represent and support students to do well on the CSAT and the NCEE or that the mathematical items in the CSAT and the NCEE validly assess students' level of mathematical understanding.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.29-36
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• 2022

This study uses the panel probit model to investigate and evaluate the relationship between exchange rate regimes, political stability, and carbon dioxide during currency crises. To understand currency crisis times, we study a panel dataset of seven South Asian nations that contain annual observations from 1996 to 2020. Furthermore, we created the EMPI exchange market pressure indicator to detect crises. Our results strongly suggested that fixed exchange rate is negatively associated with currency crises, with good regulatory quality and better effective governments. Simultaneously, the floating exchange rate is positively related to the currency crises in those countries where the rule of law has less adequately flowed. However, CO₂, exports, and interest rates are buoyantly associated with crises. The floating exchange rate, the rule of law, exports, and interest rate are associated positively and contribute more prone to the crisis episodes. Negatively associated variables contributed less amid crises episodes: fixed exchange rate regime, government effectiveness, and regulatory quality. Meanwhile, CO₂ has a positive relationship with a currency crisis and contributes more likelihood to the probability of a currency crisis. Countries that adopted the fixed exchange rates with effective governments and regulatory quality faced more minor currency crises.

• Advances in aircraft and spacecraft science
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• v.9 no.6
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• pp.537-551
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• 2022

The rapid decrease of fossil fuel resources and increase of environmental pollution caused by aviation industries have become a severe issue which leads to an increase in the greenhouse effect. The use of biofuel becomes an option to alleviate issues related to unrenewable resources. This study presents a computational simulation of the biofuel combustion characteristics of various alternative fuels in an annular combustion chamber designed for training aircraft. The biofuels used in this study are Sorghum Oil Methyl Ester (SOME), Spirulina Platensis Algae (SPA) and Camelina Hydrotreated Esters and Fatty Acids (CHEFA). Meanwhile, Jet-A is used as a baseline fuel. The fuel properties and combustion characteristics are being investigated and analysed. The results are presented in terms of temperature and pressure profiles in addition to the formation of NOx and soot generated from the combustion chamber. Results obtained show that CHEFA fuel is the most recommended biofuel among all four tested fuels as it is being found that it burns with 37.6% lower temperature, 15.2% lower pressure, 89.5% lower NOx emission and 8.1% lower soot emission compared with the baseline fuel in same combustion chamber geometry with same initial parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1200-1215
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• 2023

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.382-388
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• 2011

Being aware of the risk in advance necessitates intricate processes but is feasible. Although previous studies have demonstrated high accuracy, their performance still leaves room for improvement. A self-organizing feature map (SOM) based neurofuzzy model is developed in this study to provide another alternative for forecasting corporate financial distress. The model is designed to yield high prediction accuracy, as well as reference rules for evaluating corporate financial status. As a database, the study collects all financial reports from listed construction companies during the latest decade, resulting in over 1000 effective samples. The proportion of "failed" and "non-failed" companies is approximately 1:2. Each financial report is comprised of 25 ratios which are set as the input variable s. The proposed model integrates the concepts of pattern classification, fuzzy modeling and SOM-based optimization to predict corporate financial distress. The results exhibit a high accuracy rate at 85.1%. This model outperforms previous tools. A total of 97 rules are extracted from the proposed model which can be also used as reference for construction practitioners. Users may easily identify their corporate financial status by using these rules.