• KIPS Transactions on Software and Data Engineering
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• v.8 no.4
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• pp.153-162
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• 2019

Recently, it is necessary to develop a technology for quantitatively evaluating railway vibration to prevent civil complaints about orbital structures caused by railway noise and normal operation of ultra-precise equipment of orbital industrial complexes. The existing analytical method requires a very complicated dynamic response model, and it is difficult to secure the reliability of the result due to the inaccuracy of the demand model. Therefore, in this paper, we propose a railway vibration evaluation algorithm and system that deduce the vibration value generated from railway operation by using Linear Regression and Gradient Descent technique based on actual measurement railway vibration database that classifies factors affecting railway vibration. The prediction results obtained by the proposed algorithm show higher efficiency and accuracy than the existing analytical methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.97-115
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• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.4
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• pp.132-144
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• 2022

In response to the recent surge in aviation demand, major airport and aviation authorities continue to make efforts to formulate arrival procedures that take into account efficient aircraft separation, noise and environmental issues related to carbon (CO₂) emissions. In order to ensure efficient traffic control and environmental issues, as a result, a new concept Trombone, Point Merge, etc. have been introduced and widely used. However, these new concept incisions are becoming a factor that hinders operational efficiency and stability due to the restricted domestic airspace such as military airspace and excessive constraints of altitude, speed, etc. which do not reflect the concept of continuous descent operation and eventually needs to be modified to make continuous descent operation as feasible as possible. We herewith analyze and propose the way of improving flight safety and efficiency in the arrival operation procedure by supplementary modification which consequently contribute to the aviation industry international competitiveness.

• Physical Therapy Korea
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• v.13 no.2
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• pp.16-25
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• 2006

The aim of this study was to investigate the kinematics of young adults during descent ramp climbing at different inclinations. Twenty-three subjects descended four steps at four different inclinations (level, $-8^{\circ}$, $-16^{\circ}$, $-24^{\circ}$). The 3-D kinematics were measured by a camera-based Falcon System. The data were analyzed using one-way ANOVA and the Student-Newman-Keuls test. The kinematics of descent ramp walking could be clearly distinguished from the kinematics of level walking. On a sagittal plane, the ankle joint was more plantar flexed at initial contact with $-16^{\circ}/-24^{\circ}$ inclination, was decreased in the toe off position with all inclinations (p<.001),and was decreased at maximum plantar flexion during the swing phase (p<.001). The knee joint was more flexed at initial contact with the $-24^{\circ}$ inclination (p<.001), was more flexed in the toe off position with all inclinations (p<.001), and was more flexed at minimum flexion during stance phase and at maximum flexion during swing phase with $-16^{\circ}$, $-24^{\circ}$ inclination (p<.001). The hip joint was more flexed in the toe off position with $-16^{\circ}$, $-24^{\circ}$ inclination and was deceased at maximum extension during stance phase with $-16^{\circ}$, $-24^{\circ}$ inclination (p<.05). In the frontal plane, the ankle joint was more everted at maximum eversion during stance phase with $-16^{\circ}/-24^{\circ}$ inclination (p<.01) and was decreased at maximum inversion during swing phase with $-16^{\circ}$, $-24^{\circ}$ inclination (p<.01). The knee joint was more increased at maximum varus during stance phase with $-16^{\circ}/-24^{\circ}$ inclination (p<.001). The hip joint was deceased at maximum adduction during stance phase with $-24^{\circ}$ inclination (p<.05). In a horizontal plane, only the knee joint was increased at maximum internal rotation during stance phase with $-24^{\circ}$ inclination (p<.05). In descent ramp walking, the different gait patterns occurred at an inclination of over $16^{\circ}$ on the descending ramp in the sagittal and frontal planes. These results suggest that there is a certain inclination angle or angular range where subjects do switch between level walking and descent ramp walking gait patterns.

• Korean Journal of Plant Resources
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• v.17 no.3
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• pp.297-303
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• 2004

This study was carried out to investigate into the dyeability of ramie fabrics using the extract of native plant, red-dye madder (Rubia akane Nakai) in different conditions. Surface color of ramie fabrics dyed with extracts from red-dye madder plants showed an order of descent YR. However, it was changed by the different mordants. Surface color of ramie fabrics treated with FeSO$_4$, SnCl$_4$, and tartaric acid was an order of descent Y, and that treated with the ashes of common camellia, and bean straw was an order of descent R. At higher temperatures, surface color and coloring matter concentration of ramie fabrics were as follows that values of a increased, however, values of b decreased and values of L lowered. Coloring matter concentration increased in the order of 7$0^{\circ}C$, 9$0^{\circ}C$, and 6$0^{\circ}C$, and so on. Dyeing colors on the ramie fabrics showed an order of descent Y by pH 4 and 9 in dyestuffs solutions. Coloring matter concentration in terms of K/S values, more or less, was increased at strong acids. Surface color by the concentration of dyestuffs solutions showed an order of descent YR irrelevant to the concentration of dyestuffs solutions. Coloring matter concentration was increased at higher concentrations of dyestuffs solutions. Ten minutes was sufficient for the dyeing of ramie fabrics in terms of surface color and coloring matter concentration.

• Journal of Korean Port Research
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• v.9 no.1
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• pp.45-56
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• 1995

Investigation of the physical behavior of dredged material disposal in coastal water includes estimations of water column concentration in the receiving water, exposure time, the initial deposition pattern as well as thickness of material at the dumping fields near the estuary area. Calculation based on vertical setting and horizontal advection of single particles ignore the effects of bulk properties of the disposed material, vertical and horizontal diffusion, and material dilution due to the entrainment of ambient water during descent. This paper focuses on the spatial and temporal changes in the dumping fields for the water column and bottom at a hypothetically confined coastal water, where the ambient time-invariant velocity and density profiles are applied, within the initial time period following the instantaneous release of the dredged material. This model accounts the behavior of material after release divided into three phases: convective descent, dynamic collapse and long-term passive dispersion

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.781-788
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• 2005

This paper proposes an identification method using a self recurrent wavelet neural network (SRWNN) for dynamic systems. The architecture of the proposed SRWNN is a modified model of the wavelet neural network (WNN). But, unlike the WNN, since a mother wavelet layer of the SRWNN is composed of self-feedback neurons, the SRWNN has the ability to store the past information of the wavelet. Thus, in the proposed identification architecture, the SRWNN is used for identifying nonlinear dynamic systems. The gradient descent method with adaptive teaming rates (ALRs) is applied to 1.am the parameters of the SRWNN identifier (SRWNNI). The ALRs are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of an SRWNNI. Finally, through computer simulations, we demonstrate the effectiveness of the proposed SRWNNI.

• Bulletin of the Korean Mathematical Society
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• v.50 no.1
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• pp.73-81
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• 2013

In this paper, an efficient hybrid nonlinear conjugate gradient method is proposed to solve general unconstrained optimization problems on the basis of CD method [2] and DY method [5], which possess the following property: the sufficient descent property holds without any line search. Under the Wolfe line search conditions, we proved the global convergence of the hybrid method for general nonconvex functions. The numerical results show that the hybrid method is especially efficient for the given test problems, and it can be widely used in scientific and engineering computation.

• Journal of the Korea Society of Computer and Information
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• v.22 no.4
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• pp.9-16
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• 2017

Machine learning has found widespread implementations and applications in many different domains in our life. Logistic regression is a type of classification in machine leaning, and is used widely in many fields, including medicine, economics, marketing and social sciences. In this paper, we present the MapReduce implementation of three existing algorithms, this is, Gradient Descent algorithm, Cost Minimization algorithm and Newton-Raphson algorithm, for logistic regression on RHadoop that integrates R and Hadoop environment applicable to large scale data. We compare the performance of these algorithms for estimation of logistic regression coefficients with real and simulated data sets. We also compare the performance of our RHadoop and RHIPE platforms. The performance experiments showed that our Newton-Raphson algorithm when compared to Gradient Descent and Cost Minimization algorithms appeared to be better to all data tested, also showed that our RHadoop was better than RHIPE in real data, and was opposite in simulated data.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1281-1284
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• 1998

This paper proposes an efficient time series prediction of the nonlinear dynamical discrete-time systems using multilayer neural networks of a hybrid learning algorithm. The proposed learning algorithm is a hybrid backpropagation algorithm based on the steepest descent for high-speed optimization and the dynamic tunneling for global optimization. The proposed algorithm has been applied to the y00 samples of 700 sequences to predict the next 100 samples. The simulation results shows that the proposed algorithm has better performances of the convergence and the prediction, in comparision with that using backpropagation algorithm based on the gradient descent for multilayer neural network.