• Structural Engineering and Mechanics
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• v.81 no.4
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• pp.461-479
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• 2022

A finite element method analysis framework is introduced for the free vibration analyses of functionally graded porous beam structures by employing two variables trigonometric shear deformation theory. Both Young's modulus and material density of the FGP beam element are simultaneously considered as grading through the thickness of the beam. The finite element approach is developed using a nonlocal strain gradient theory. The governing equations derived here are solved introducing a 3-nodes beam element. A comprehensive parametric study is carried out, with a particular focus on the effects of various structural parameters such as the dispersion patterns of GPL reinforcements and porosity, thickness ratio, boundary conditions, nonlocal scale parameter and strain gradient parameters. The results indicate that porosity distribution and GPL pattern have significant effects on the response of the nanocomposite beams.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.4
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• pp.17-23
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• 1984

A model analysis of pattern shift in the epitaxial growth of silicon on (111) substrates was performed. The growth rate anisotropy was considered as the most important affecting factor of pattern shift, and for the model establishment the off angle of the substrate and the process temperature were taken as the variables. We derived a theoretical equation of pattern shift by assuming the growth rate anisotropy as the trigonometric sine function of the off angle of the substrate and defining the growth rate anisotropy factor related to the process temperature. The pattern shift ratio calculated by this model had the same tendency with the experimental ones, which, however, were about twice greater than those. It was supposed that this discrepailcy was due to the second order affecting factor such as facetting and step broadening which had been exluded in model establishment.

• Journal of IKEEE
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• v.23 no.1
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• pp.164-172
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• 2019

Current clinical methods for diagnosing urination disorder are invasive, expensive, and very inconvenient to perform continuous monitoring. EIT is a non-invasive technique that injects electrical current through an external electrodes and measures the induced voltage to visualize the internal electrical (impedance) characteristics, which makes it possible to monitor bladder conditions with low cost. The signal characteristics of the measured voltage data changes according to the current pattern injected through the electrode and affects reconstruction performance. In this paper, image reconstruction performance is compared and analyzed according to the injected current patterns to maximize the sensitivity to the variation of bladder size.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.256-264
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• 2012

The directional algebraic reconstruction technique (DART) using the trigonometric current pattern is one of the image reconstruction algorithms in electrical impedance tomography (EIT). This method needs to compute resistances between electrode pairs as using relation between the injected currents and measured voltages for the reconstruction of the inner image. The delay time is incurred in this process. Therefore this paper proposes modified directional algebraic reconstruction technique (mDART) using the adjacent current pattern instead of the trigonometric current pattern to solve the delay time for initial resistance values. The proposed method uses measured voltages instead of computed resistances in the reconstruction algorithm. Hence this method can eliminate the delay time because it does not use the resistances. In conclusion, the proposed method improves image quality and image reconstruction time by using the adjacent current pattern. To prove performance of the proposed method, we carried on computer simulation of various cases.

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.475-478
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• 2006

In electrical impedance tomography (EIT) an array of electrodes is attached on the boundary of an object and small alternating currents are injected through these electrodes, and then the resulting voltages are measured. An estimation for the cross-sectional resistivity distribution in the object is obtained by using these current and voltage data in a nondestructive manner. In this paper, the electrical impedance imaging of two-phase flows undergoing rapid transient is considered with a special emphasis on the effect of the current pattern on the image reconstruction. The trigonometric current pattern, which is commonly used in the conventional static electrical impedance imaging, shows poor performance in case of the dynamic imaging considered in this work. Extensive numerical experiments are conducted with various kinds of current patterns and their effects on the image reconstruction performance are examined.

• Journal of Biomedical Engineering Research
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• v.35 no.6
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• pp.227-233
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• 2014

In this paper, to quantitatively evaluate the degree of rehabilitation for the disabled of unilateral lower extremity, we compared the EMG pattern of normal and simulated abnormal gait. The EMG signal was measured at a rate of 1 kHz on the quadriceps and biceps femoris, the pressure sensor was attached to the sole in order to distinguish the gait cycle. Integrated EMG (IEMG) was obtained by the gait cycle, and classified four patterns that were the normal gait pattern, amplitude decrease pattern, reversed pattern, and irregular pattern. For comparison of the patterns, a curve fitting was performed using the trigonometric functions. The result of curve fitting, the method using a variable A that corresponds to the amplitude of the regression curve was able to distinguish the reverse pattern and remaining pattern. The coefficient of determination ($R^2$) representing coincidence of the pattern of the regression curve and EMG was confirmed the biggest value at the normal gait. Therefore, the degree of normal gait can be confirmed using the coefficient of determination. This results show that it is possible to quantitatively confirm the degree of unilateral lower extremity disabled rehabilitation, and it will be contributed to the study of efficient rehabilitation methods by objective analysis.

• Steel and Composite Structures
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• v.43 no.1
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• pp.31-54
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• 2022

This paper is concerned with the buckling behavior of functionally graded graphene reinforced porous nanocomposite beams based on the finite element method (FEM) using two variables trigonometric shear deformation theory. Both Young's modulus and material density of the FGP beam element are simultaneously considered as grading through the thickness of the beam. The finite element approach is developed using a nonlocal strain gradient theory. The governing equations derived here are solved introducing a 3-nodes beam element, and then the critical buckling load is calculated with different porosity distributions and GPL dispersion patterns. After a convergence and validation study to verify the accuracy of the present model, a comprehensive parametric study is carried out, with a particular focus on the effects of weight fraction, distribution pattern of GPL reinforcements on the Buckling behavior of the nanocomposite beam. The effects of various structural parameters such as the dispersion patterns for the graphene and porosity, thickness ratio, boundary conditions, and nonlocal and strain gradient parameters are brought out. The results indicate that porosity distribution and GPL pattern have significant effects on the response of the nanocomposite beams, and the results allows to identify the most effective way to achieve improved buckling behavior of the porous nanocomposite beam.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.142-152
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• 2016

GPS is not able to be used for indoor positioning and currently most of techniques emerging to overcome the limit of GPS utilize private wireless networks. However, these methods require high costs for installation and maintenance, and they are inappropriate to be used in the place where precise positioning is needed as in indoor parking lots. This paper proposes a vehicular indoor positioning method based on QR-code recognition. The method gets an absolute coordinate through QR-code scanning, and obtain the location (an relative coordinate) of a black-box camera using the tilt and roll angle correction through affine transformation, scale transformation, and trigonometric function. Using these information of an absolute coordinate and an relative one, the precise position of a car is estimated. As a result, average error of 13.79cm is achieved and it corresponds to just 27.6% error rate in contrast to 50cm error of the recent technique based on wireless networks.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.1-6
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• 2016

Image rotation is one of main pre-processing step in image processing or image pattern recognition. It is implemented with rotation matrix multiplication. However it requires lots of floating point arithmetic operations and trigonometric function calculations, so it takes long execution time. We propose a new high speed image rotation algorithm without two major time-consuming operations. It use just 2 shear translation operations, so it is very fast. In addition, we apply a parallel computing technique with CUDA. CUDA is a massively parallel computing architecture using prevailed GPU recently. As GPU is a dedicated graphic processor, it is exellent for parallel processing of pixels. We compare the proposed algorithm with the conventional rotation one with various size images. Experimental results show that the proposed algorithm is superior to the conventional rotation ones.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.259-267
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• 2015

In this paper, we proposed the straight line determination method and the algorithm for 8 directions determination of straight line using the coordinate information and the property of trigonometric function. We conduct an experiment that is 8 hand gestures are carried out 100 times each, a total of 800 times. And the accuracy for the 8 derection determination algorithm is showed the diagonal direction to the left upper side shows the highest accuracy as 92%, and the direction to the left side, the diagonal direction to the right upper side and the diagonal direction to the right bottom side show the lowest accuracy as 82%. This method with coordinate information through image processing than the existing recognizer and the recognition through learning process is possible using a hand gesture recognition gesture.