• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.624-633
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• 2018

While the multimedia lecture system has been getting smart using immerging technology, the microphone still relies on the classical approach such as holding in hand or attaching on the body. In this paper, we propose a ceiling mounted array microphone system that allows a wide reception coverage and instructors to move freely without attaching microphone. The proposed system adopts cell and handover of mobile communication instead of a complicated beamforming method and implements a wide range microphone over several cells with low cost. Since the characteristics of unvoiced speech is similar to Pseudo Noise it is shown that soft handover are possible with 3 microphones connected to delay-sum multipath receiver. The proposed system is tested in $6.3{\times}1.5m$ area. For real-time processing the correlation range can be reduced by 82% or more, and the output latency delay can be improved by using the delay adaptive filter.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.3
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• pp.242-249
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• 2011

The proposed converter has easy device selection for high step-up and high power applications since boost half bridge and voltage doubler cells are connected, respectively, in parallel and series in order to increase output power and voltage. Especially, optimized design of high frequency transformers is possible owing to reduced turn ratio and eliminated dc offset, and distributed power through three cores is beneficial to low profile and thermal distribution. The proposed converter does not necessitate start-up circuit and additional clamp circuit due to the use of whole duty range between 0 and 1 and is suitable for applications with wide input voltage range. Also, high efficiency can be achieved since ZVS turn on of switches are achieved in wide duty cycle range and ZCS turn on and off of diodes are achieved. The proposed converter was validated through 5 kW prototype.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.5
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• pp.343-354
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• 2009

In this paper, a magnetic-less dc-dc switching converter realizing an integrable power conversion system is described. Instead of magnetic devices, the inductive impedance range of piezoelectric transducers is utilized to store and resonate the energy for soft-switching. Piezoelectric devices have no windings and deliver the power by the electrodes, which lead to mass product through semiconductor-manufacturing process. This paper presents a resonant-type step-up dc-dc power converter employing a disk-type piezoelectric transducer, analyzing the operation principles and the frequency control characteristics. Also, a topology extension of the single stage converter into cascaded multi-stage is presented and analyzed with the operation principles and control characteristics. For verification of the analysis, a 10W output dc-dc power converter hardware was implemented. The hardware experiments shows a good frequency control and power efficiency greater than 96% in the single stage. A hardware prototype of the extended multi-stage one was also realized and tested. The results shows that the converter has the same frequency control performance and high efficiency such as 93%.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1257-1259
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• 1996

In this paper, we introduce an integrated communication and control system(ICCS) for control of a crane. The system is integrated with a compasite technique as a network interfacing, a user interfacing and a system control for continuous process like as a container crane. The field-bus(Profibus) network module is used to interconnect each input/output module with main control unit. The MMI system for user interfacing is integrated with an ODBC-based data management tool and IECl131-based control logic design tool(Soft-Logic Designer:SLD). The each programmed control task in the main Controller is executed using a petri-net based scheduler.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.1954-1960
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• 2008

Modem Robot is used in all industries. Previous Robot was used by simplicity work, at recent times, robot is developed in form that can do action such as a person. Robot's action runs according to command repeat or in the every moment according to sensor's output value, achieve other action. In this raper, we studied about self-regulation transfer robot that follow Object autonomously. This robot can be used by purpose that carry heavy burden instead of human. Robot's composition is drive part which run object's position awareness Sensor, Processor that control action and Motor part. After robot is connects with Network, we did robot remote control and monitor the action situation of robot. For the methode to reduce drive error, we developed algorithm for outside environment. For an experiment we made the self-regulation robot. We showed the directivity of sensor, error of directivity and soft moving of robot. We showed the monitoring system and the execution screen for communication between robot and PC.

• Steel and Composite Structures
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• v.33 no.3
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• pp.319-332
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• 2019

This study is aimed to predict the behaviour of channel shear connectors in composite floor systems at different temperatures. For this purpose, a soft computing approach is adopted. Two novel intelligence methods, including an Extreme Learning Machine (ELM) and a Genetic Programming (GP), are developed. In order to generate the required data for the intelligence methods, several push-out tests were conducted on various channel connectors at different temperatures. The dimension of the channel connectors, temperature, and slip are considered as the inputs of the models, and the strength of the connector is predicted as the output. Next, the performance of the ELM and GP is evaluated by developing an Artificial Neural Network (ANN). Finally, the performance of the ELM, GP, and ANN is compared with each other. Results show that ELM is capable of achieving superior performance indices in comparison with GP and ANN in the case of load prediction. Also, it is found that ELM is not only a very fast algorithm but also a more reliable model.

• Journal of IKEEE
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• v.23 no.3
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• pp.994-1002
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• 2019

In this paper, we propose the development of a power conversion system for electric power take-off (e-PTO) of agricultural electric vehicles. Most e-PTOs use commercial power $220V_{AC}$. A bidirectional power conversion system having a two-stage structure consisting of a DC-DC converter and a DC-AC inverter for supplying a high output voltage using a low battery voltage of an agricultural electric vehicle is suitable. we propose a power conversion system consisting of the one-stage dual active bridge (DAB) converter and the two-stage bidirectional full bridge inverter. In addition, we propose a soft start algorithm for reducing the inrush current generated by the link capacitor charging during the initial operation. A 3kW prototype system and its corresponding algorithms have been implemented to verify its effectiveness through experiments.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.327-340
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• 2022

The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.

• Korean Journal of Materials Research
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• v.32 no.11
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• pp.508-514
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• 2022

Piezoelectric composite films which are enabled by inorganic piezoelectric nanomaterials-embedded polymer, have attracted enormous attention as a sustainable power source for low powered electronics, because of their ease of fabrication and flexible nature. However, the absorption of applied stress by the soft polymeric matrices is a major issue that must be solved to expand the fields of piezoelectric composite applications. Herein, a flexible and porous piezoelectric composite (piezoelectric sponge) comprised of BaTiO₃ nanoparticles and polydimethylsiloxane was developed using template method to enhance the energy conversion efficiency by minimizing the stress that vanishes into the polymer matrix. In the porous structure, effective stress transfer can occur between the piezoelectric active materials in compression mode due to direct contact between the ceramic particles embedded in the pore-polymer interface. The piezoelectric sponge with 30 wt% of BaTiO₃ particles generated an open-circuit voltage of ~12 V and a short-circuit current of ~150 nA. A finite element method-based simulation was conducted to theoretically back up that the piezoelectric output performance was effectively improved by introducing the sponge structure. Furthermore, to demonstrate the feasibility of pressure detecting applications using the BaTiO₃ particles-embedded piezoelectric sponge, the composite was arranged in a 3 × 3 array and integrated into a single pressure sensor. The fabricated sensor array successfully detected the shape of the applied pressure. This work can provide a cost-effective, biocompatible, and structural strategy for realizing piezoelectric composite-based energy harvesters and self-powered sensors with improved energy conversion efficiency.

• Geomechanics and Engineering
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• v.28 no.6
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• pp.599-611
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• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.