• International Journal of Concrete Structures and Materials
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• v.1 no.1
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• pp.63-73
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• 2007

Optimum multi-layered feed-forward neural network (NN) models using a resilient back-propagation algorithm and early stopping technique are built to predict the shear capacity of reinforced concrete deep and slender beams. The input layer neurons represent geometrical and material properties of reinforced concrete beams and the output layer produces the beam shear capacity. Training, validation and testing of the developed neural network have been achieved using 50%, 25%, and 25%, respectively, of a comprehensive database compiled from 631 deep and 549 slender beam specimens. The predictions obtained from the developed neural network models are in much better agreement with test results than those determined from shear provisions of different codes, such as KBCS, ACI 318-05, and EC2. The mean and standard deviation of the ratio between predicted using the neural network models and measured shear capacities are 1.02 and 0.18, respectively, for deep beams, and 1.04 and 0.17, respectively, for slender beams. In addition, the influence of different parameters on the shear capacity of reinforced concrete beams predicted by the developed neural network shows consistent agreement with those experimentally observed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.87-94
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• 2001

Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.4
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• pp.143-147
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• 2011

The system using augmented reality can save the time and cost. It is verified in various fields under the possibility of a technology by solving unrealistic feeling in the virtual space. Therefore, augmented reality has a variety of the potential to be used. Generally, multimodal senses such as visual/auditory/tactile feed back are well known as a method for enhancing the immersion in case of interaction with virtual object. By adapting tangible object we can provide touch sensation to users. a 3D model of the same scale overlays the whole area of the tangible object; thus, the marker area is invisible. This contributes to enhancing immersive and natural images to users. Finally, multimodal feedback also creates better immersion. In this paper, sound feedback is considered. By further improving immersion learning augmented reality for children with the initial step learning content is presented. Augmented reality is in the intermediate stages between future world and real world as well as its adaptability is estimated more than virtual reality.

• Proceedings of the Korea Association of Crystal Growth Conference
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• 1999.06a
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• pp.253-269
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• 1999

The development of telecommunication and information technology requires to develop new piezoelectric materials with small size, low impedance, wide pass band width and high thermal stability of frequency. Langasite (La3Ga5SiO14) single crystal has been researched substitute of quartz and LiNbO3 for the applications of SAW filter, BAW filter and resonator. Its single crystal growth has been carried out by Czochralski Method. So, in order to get single crystal with higher quality, in this study, lnagasite (La3Ga5SiO14) single crystal was grown by using Floating Zone (FZ) method and characterized. For the growth of langasite single crystals, the langasite powder was synthesized at 135$0^{\circ}C$ for 5hrs and the feed rod was sintered at 135$0^{\circ}C$ for 5hrs. The growing rate was 1.5mm/h and the rotation speed was 15 rpm for an upper rotation and 13 rpm for a lower rotation. In order to prevent the evaporation of gallium oxide, Ar and O2 gas mixture was flowed. The growth direction was analyzed by Laue back-scattered analysis. The composition of grown crystal was analyzed suing XRD and WDS. The electrical properties of grown crystal at various frequencies and temperature were discussed.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.243-247
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• 2005

We propose an efficient block least-mean-square (BLMS) adaptive algorithm, in conjunction with error control coding, for direct-sequence code division multiple access (DS-CDMA) systems. The proposed adaptive receiver incorporates decision feedback detection and channel encoding in order to improve the performance of the standard LMS algorithm in convolutionally coded systems. The BLMS algorithm involves two modes of operation: (i) The training mode where an uncoded training sequence is used for initial filter tap-weights adaptation, and (ii) the decision-directed where the filter weights are adapted, using the BLMS algorithm, after decoding/encoding operation. It is shown that the proposed adaptive receiver structure is able to compensate for the signal-to­noise ratio (SNR) loss incurred due to the switching from uncoded training mode to coded decision-directed mode. Our results show that by using the proposed adaptive receiver (with decision feed­back block adaptation) one can achieve a much better performance than both the coded LMS with no decision feedback employed. The convergence behavior of the proposed BLMS receiver is simulated and compared to the standard LMS with and without channel coding. We also examine the steady-state bit-error rate (BER) performance of the proposed adaptive BLMS and standard LMS, both with convolutional coding, where we show that the former is more superior than the latter especially at large SNRs ($SNR\;\geq\;9\;dB$).

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2668-2670
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• 1999

In the past, the PWM converter had a large switching loss by hard switching and difficult to high frequency operation. The resonance converter to decrease the switching loss and EMI is required the frequency control and needed to reduce the voltage or current stress at each parts. So, this paper propose the 3-phase boost converter and the method to compensated input power factor by control the amplitude - an instantaneous value of the DC inductor current -and control the switching frequency that a modulation error by the ripple of the DC inductor current. The proposed 3-phase PWM boost converter of single phase control type can takes higher capacity and compensate the power factor by using Feed back controller at each phase for the existing 3-phase bridge rectifier type. Moreover the 3-phase full bridge type using the rectifier at each 3-phase circuit will be small size reactor and compensate input power factor by minimize harmonic components of each phase.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.700-709
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• 2014

The purpose of this study was to examine the effects of question-generating strategy on science academic achievement, scientific attitude in elementary science class. To examine the effects of question-generating strategy this learning materials were applied to elementary science curriculum, and an experimental group and a control group were selected from $5^{th}$ graders at H elementary school located in Gyeonggi-do. Students were taught for 6 weeks. Control group take traditional lessons and solve questions presented textbook. Question generated group generate questions, solve them and feed back by themselves. The results of this study were found statistically significant difference in the pupil's enhancement of the science academic achievement, scientific attitude (p<.05). Thus question-generating strategy for elementary science inquiry instruction that has a positive effect on interests in class is useful and better be widely applied to science education.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.980-986
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• 2003

As the ultra precision grinding can be applied to wafering process by the refinement of the abrasive, the development of high stiffness equipment and grinding skill, the conventional wafering process which consists of lapping, etching, Ist, 2nd and 3rd polishing could be exchanged to the new process which consists of precision surface grinding, final polishing and post cleaning. Especially, the ultra precision grinding of wafer improves the flatness of wafer and the efficiency of production. Futhermore, it has been not only used in bare wafer grinding, but also applied to wafer back grinding and SOI wafer grinding. This paper focused on the effect of the wheel path density and relative velocity on the characteristic of ground wafer in in-feed grinding with cup-wheel. It seems that the variation of the parameters in radial direction of wafer results in the non-uniform surface quality over the wafer. So, in this paper, the geometric analysis on grinding process is carried out, and then, the effect of the parameters on wafer surface quality is evaluated

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1929-1939
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• 1999

This paper presents a neural network approach, which was named PRONET, to 3D object recognition and pose calculation. 3D objects are represented using a set of centroidal profile patterns that describe the boundary of the 2D views taken from evenly distributed view points. PRONET consists of the training stage and the execution stage. In the training stage, a three-layer feed-forward neural network is trained with the centroidal profile patterns using an error back-propagation method. In the execution stage, by matching a centroidal profile pattern of the given image with the best fitting centroidal profile pattern using the neural network, the identity and approximate orientation of the real object, such as a workpiece in arbitrary pose, are obtained. In the matching procedure, line-to-line correspondence between image features and 3D CAD features are also obtained. An iterative model posing method then calculates the more exact pose of the object based on initial orientation and correspondence.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.2
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• pp.1-7
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• 2011

The UAV(Unmanned Aerial Vehicle) which is remotely operating with long endurance in high altitude must have a very reliable propulsion system. The precise fault diagnostic system of the turboprop engine as a propulsion system of this type UAV can promote reliability and availability. This work proposes a diagnostic method which can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. It is found by evaluation examples that the proposed diagnostic method can detect well not only single type faults but also multiple type faults.