• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

• Advances in nano research
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• v.15 no.3
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• pp.263-275
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• 2023

The electron transport properties of Y-type zigzag branched carbon nanotubes (CNTs) are of great significance for micro and nano carbon-based electronic devices and their interconnection. Based on the semi-empirical method combining tight-binding density functional theory and non-equilibrium Green's function, the electron transport properties between the branches of Y-type zigzag branched CNT are studied. The results show that the drain-source current of semiconducting Y-type zigzag branched CNT (8, 0)-(4, 0)-(4, 0) is cut-off and not affected by the gate voltage in a bias voltage range [-0.5 V, 0.5 V]. The current presents a nonlinear change in a bias voltage range [-1.5 V, -0.5 V] and [0.5 V, 1.5 V]. The tangent slope of the current-voltage curve can be changed by the gate voltage to realize the regulation of the current. The regulation effect under negative bias voltage is more significant. For the larger diameter semiconducting Y-type zigzag branched CNT (10, 0)-(5, 0)-(5, 0), only the value of drain-source current increases due to the larger diameter. For metallic Y-type zigzag branched CNT (12, 0)-(6, 0)-(6, 0), the drain-source current presents a linear change in a bias voltage range [-1.5 V, 1.5 V] and is symmetrical about (0, 0). The slope of current-voltage line can be changed by the gate voltage to realize the regulation of the current. For three kinds of Y-type zigzag branched CNT with different diameters and different conductivity, the current-voltage curve trend changes from decline to rise when the branch of drain-source is exchanged. The current regulation effect of semiconducting Y-type zigzag branched CNT under negative bias voltage is also more significant.

• Journal of radiological science and technology
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• v.47 no.2
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• pp.117-123
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• 2024

This study was to assessment of quality assurance (QA) and noise characteristics of Noise Power Spectrum (NPS) according to the time of by using electronic portal imaging device (EPID) for LINAC (Linear Accelerator). LINAC device was (Varian Clinac^R iX LINAC, USA) used and the were 40 × 30 cm² of detector size were 1024 × 768 photo-electric diode array size. Signal could be obtained the K-space image of white noise images for NPS and we used to Overlap, Non-Overlap, Out of Penumbra, Flatness, Symmetry, Symmetry Rt, Lt methods. The 2013s NPS image Out of Penumbra quantitatively value more than 2013s NPS image Symmetry Rt, Lt methods quantitatively NPS based on the frequency of 1.0 mm^-1. Thus, the 2022s NPS image Out of Penumbra quantitatively value more than 2022s NPS image Symmetry Rt, Lt methods quantitatively NPS based on the frequency of 1.0 mm^-1. The assessment of comparison of white noise for NPS image noise and intensity of this study were to that should be used efficiently of the LINAC EPID detector system for Overlap method for International Electro-technical Commission (IEC).

• The Journal of the Acoustical Society of Korea
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• v.27 no.7
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• pp.386-393
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• 2008

This paper proposes a new approach for speech enhancement in highly nonstationary noisy environments. The spectral subtraction (SS) is a well known technique for speech enhancement in stationary noisy environments. However, in real world, noise is mostly nonstationary. The proposed method uses an auto control parameter for an adaptive threshold to work well in highly nonstationary noisy environments. Especially, the auto control parameter is affected by a linear function associated with an a posteriori signal to noise ratio (SNR) according to the increase or the decrease of the noise level. The proposed algorithm is combined with spectral subtraction (SS) using a hangover scheme (HO) for speech enhancement. The performances of the proposed method are evaluated ITU-T P.835 signal distortion (SIG) and the segment signal to-noise ratio (SNR) in various and highly nonstationary noisy environments and is superior to that of conventional spectral subtraction (SS) using a hangover (HO) and SS using a minimum statistics (MS) methods.

• Journal of the Korean GEO-environmental Society
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• v.11 no.1
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• pp.19-26
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• 2010

The batch experiments and response surface methodology (RSM) have been applied to the investigation of the cadmium (Cd) adsorption by coal fly ash (CFA). CFA having maximum Cd removal mass of 8.51 mg/g were calculated from Langmuir model. Cd removal reaction with different initial pH ranged from 4 to 9. When the initial pH was higher, Cd was removed more by adsorption and precipitation. These results suggest that the lower pH cause an increase of $H^+$ ion concentration which competed with Cd ions for exchange sites in CFA. Also, The Cd adsorption was mathematically described as a function of parameters initial Cd concentration ($X_1$), initial pH ($X_2$), and initial CFA mass ($X_3$) being modeled by use of the Box-Behnken methods. Empirical models were developed to describe relationship between the experimental variables and response. Statistical analysis indicates that tree factors ($X_1$, $X_2$, and $X_3$) on the linear term (main effects), and tree factors ($X_1X_2$, $X_1X_3$, and $X_2X_3$) on the non-linear term (Interaction effect; cross-product) had significant effects, respectively. In this case, the value of the adjusted determination coefficient (adjusted $R^2=0.9280$) was closed to 1, showing a high significance of the model. Statistical results showed the order of Cd removal at experimental factors to be initial initial pH > initial Cd concentration > initial CFA mass.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.3
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• pp.63-74
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• 1999

A sliding mode fuzzy control (SMFC) algorithm is presented for vibration of large structures. Rule-base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the nonlinear control algorithms. Fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation. Non-linearity of the control rule makes the controller more effective than linear controllers. Design procedure based on the present fuzzy control is more convenient than those of the conventional algorithms based on complex mathematical analysis, such as linear quadratic regulator and sliding mode control(SMC). Robustness of presented controller is illustrated by examining the loop transfer function. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator-structure interaction, modeling error, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as $H_{mixed 2/{\infty}}$ optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is an efficient and attractive control method, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient.

• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.2
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• pp.109-115
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• 2019

In case of the cracks in concrete, the penetration of deterioration ions such as chloride ions in to cracks is accelerated. According to the penetration of chloride ions, structural and durability problems to RC(Reinforced Concrete) structures are caused. In this study, the accelerated chloride diffusion coefficient which is in steady state is evaluated for 2 year aged normal and high strength FA(Fly Ash) concrete, after a range of crack depths are induced up to 1.0 mm in 56 aged day. Considering crack effect by linear regression analysis, high strength concrete has slightly less increasing ratio of diffusion coefficient by crack than normal strength concrete, and diffusion coefficient increases non-linearly as crack width is increased. Also, In two types of concrete, crack effect decrease as the curing period increase. In the case of quantifying crack and curing effect by using exponential function form, the coefficients of determination are higher than those of linear regression analysis. Under steady state, it is thought that there is not a high correlation between the crack effect and the curing effect, and considering the two independent effects, it is believed that reasonable prediction equation for diffusion of concrete with crack can be proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1229-1244
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• 2017

In recent years, as demand for data-based analytical methodologies increases in various fields, optimization methods have been developed to handle them. In particular, various constraints required for problems in statistics and machine learning can be solved by convex optimization. Alternating direction method of multipliers (ADMM) can effectively deal with linear constraints, and it can be effectively used as a parallel optimization algorithm. ADMM is an approximation algorithm that solves complex original problems by dividing and combining the partial problems that are easier to optimize than original problems. It is useful for optimizing non-smooth or composite objective functions. It is widely used in statistical and machine learning because it can systematically construct algorithms based on dual theory and proximal operator. In this paper, we will examine applications of ADMM algorithm in various fields related to statistics, and focus on two major points: (1) splitting strategy of objective function, and (2) role of the proximal operator in explaining the Lagrangian method and its dual problem. In this case, we introduce methodologies that utilize regularization. Simulation results are presented to demonstrate effectiveness of the lasso.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.2
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• pp.207-217
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• 2016

Permeability can not be expressed as a function of porosity alone, it depends on the porosity, pore size and distribution, and tortuosity of pore channels in concrete. There has been considerable interest in the relationship between microstructure and transport in cementitious materials, however, it is very rare to deal with the theoretical study on gas permeability coefficient in connection with carbonation of concrete and the effect of volumetric fraction of cement paste or aggregate on the permeability coefficient. The majority of these researches have not dealt with this issue combined with carbonation of concrete, although carbonation can significantly impact on the permeability coefficient of concrete. In this study, fundamental approach to compute gas permeability of (non)carbonated concrete is suggested. For several compositions of cement pastes, the gas permeability coefficient was calculated with the analytical formulation, followed by a microstructure-based model. For carbonated concrete, reduced porosity was calculated and this was used for calculating the gas permeability coefficeint. As the result of calculation of gas permeability for carbonated concrete, carbonation leaded to the significant reduction of gas permeability coefficient and this was obvious for concrete with high w/c ratio. Meanwhile, the relationship between gas permeability and water permeability has a linear function for cement paste based on Klinkenberg effect, however, which is not effective for concrete. For the evidence of the modeling, YOON's test was accomplished and these results were compared to each other.