• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.26 no.4
• /
• pp.458-468
• /
• 2016

Electromechanical model for analyzing a multimodal piezoelectric energy harvester comprising three connected beams is presented in this paper. This system consists of three beams which are connected alternately. The piezoelectric layer is only attached to the middle beam. With this special structural configuration, the first, second, and third natural frequencies are congregated so that the energy harvester can generate meaningful amount of power consistently when the main frequency component of the excitation varies around the lowest three natural frequencies of the harvester. To investigate the dynamic and electric response of the piezoelectric energy harvester, an electromechanical model is developed using the Kane's method and the accuracy of the model is validated by comparing the results obtained with the model with those obtained with the commercial software ANSYS. The results show that the piezoelectric energy harvester comprising three connected beams has much broader power generating frequency range than that of the conventional piezoelectric energy harvester.

• Journal of Power Electronics
• /
• v.16 no.6
• /
• pp.2306-2314
• /
• 2016

Design and implementation of a low cost grid-connected 5kVA solar photovoltaic (PV) system is proposed in this paper. Since the inverter is a major component of the PV system, the B4 inverter used in this paper reduces the total cost of the PV system. In order to eliminate the massive transformer, the PV system is connected to the grid through IGBT switches. In addition to injection of active power into the grid, the B4 inverter can compensate reactive power and reduce harmonics of the nonlinear loads. A TMS320F28335 DSP processor is used for effective control of the B4 inverter. Various features of this processor enable the implementation of the necessary control algorithms. As a first step, the PV system is simulated and evaluated in Matlab/Simulink. In the second step, hardware circuits are designed and implemented based on the simulation results. The operation of the PV system has been evaluated under balanced, unbalanced, linear and nonlinear loads which proves its accuracy and efficiency.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.550-558
• /
• 2018

This paper presents the current limit strategy of voltage controller of delta-connected H-bridge static synchronous compensator (STATCOM) under an unbalanced voltage fault event. When phase to ground fault happens, the feasibility to heighten the magnitude of sagging phase voltage is considered by using symmetric transformation method in delta-structure STATCOM. And the efficiency to cover the maximum physical current limit of switching device is considered by using vector analysis method that calculate the zero sequence current for balancing the cluster energy in delta connected H-bridge STATCOM. The result is simple and obvious. Only positive sequence current has to be used to support the unbalanced voltage sag. Although the relationship between combination of the negative sequence voltage with current and zero sequence current is nonlinear, the more negative sequence current is supplying, the larger zero sequence current is required. From the full-model STATCOM system simulation, zero sequence current demand is identified according to a ratio of positive and negative sequence compensating current. When only positive sequence current support voltage sag, the least zero sequence current is needed.

• Journal of Biomedical Engineering Research
• /
• v.38 no.2
• /
• pp.82-88
• /
• 2017

Enlargement of the lateral ventricles have been identified as a surrogate marker of neurological disorders. Quantitative measure of the lateral ventricle from MRI would enable earlier and more accurate clinical diagnosis in monitoring disease progression. Even though it requires an automated or semi-automated segmentation method for objective quantification, it is difficult to define lateral ventricles due to insufficient contrast and brightness of structural imaging. In this study, we proposed a fully automated lateral ventricle segmentation method based on a graph cuts algorithm combined with atlas-based segmentation and connected component labeling. Initially, initial seeds for graph cuts were defined by atlas-based segmentation (ATS). They were adjusted by partial volume images in order to provide accurate a priori information on graph cuts. A graph cuts algorithm is to finds a global minimum of energy with minimum cut/maximum flow algorithm function on graph. In addition, connected component labeling used to remove false ventricle regions. The proposed method was validated with the well-known tools using the dice similarity index, recall and precision values. The proposed method was significantly higher dice similarity index ($0.860{\pm}0.036$, p < 0.001) and recall ($0.833{\pm}0.037$, p < 0.001) compared with other tools. Therefore, the proposed method yielded a robust and reliable segmentation result.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.6 s.44
• /
• pp.19-26
• /
• 2006

Redundant expressions must be eliminated in order to apply optimization for expressions in SSA Form from CTOC. This paper applied VN(Value Numbering) for this purpose. In order to carry out VN, SSAGraph must be first generated to maintain the information in the SSA Form, equivalent nodes must be found and SCC(Strongly Connected Component) generated. Equivalent nodes are assigned with an identical valnum through SCC. We could confirm elimiations for many nodes that added at SSA Form process after VN. The valnum can be applied in optimization and type inference.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.5
• /
• pp.125-134
• /
• 2004

This paper proposes a method for recognition of traffic signs using wavelet transform and shape information from the segmented traffic sign regions. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic sign regions based on their symmetries on X- and Y-axes. In the recognition stage, it utilizes shape information including moment edge correlogram and the number of crossings which concentric circular patterns from region center intersects with frequency information extracted by wavelet transform It finally performs recognition by measuring similarity with the templates in the database. The experimental results show the validity of the proposed method from geometric transformations and environmental factors.

• The KIPS Transactions:PartB
• /
• v.18B no.4
• /
• pp.173-180
• /
• 2011

This paper shows an approach for real-time object segmentation on GPU (Graphics Processing Unit) using CUDA (Compute Unified Device Architecture). Recently, many applications that is monitoring system, motion analysis, object tracking or etc require real-time processing. It is not suitable for object segmentation to procedure real-time in CPU. NVIDIA provide CUDA platform for Parallel Processing for General Computation to upgrade limit of Hardware Graphic. In this paper, we use adaptive Gaussian Mixture Background Modeling in the step of object extraction and CCL(Connected Component Labeling) for classification. The speed of GPU and CPU is compared and evaluated with implementation in Core2 Quad processor with 2.4GHz.The GPU version achieved a speedup of 3x-4x over the CPU version.

• Proceedings of the IEEK Conference
• /
• 2004.08c
• /
• pp.764-767
• /
• 2004

The performance of a speech recognition system is generally degraded in telephone environment because of distortions caused by background noise and various channel characteristics. In this paper, data-driven temporal filters are investigated to improve the performance of a specific recognition task such as telephone speech. Three different temporal filtering methods are presented with recognition results for Korean connected-digit telephone speech. Filter coefficients are derived from the cepstral domain feature vectors using the principal component analysis.

• Journal of Power Electronics
• /
• v.13 no.4
• /
• pp.600-608
• /
• 2013

This paper analyzes the effect of the admittance component for the digitally controlled single-phase bridgeless power factor correction (PFC) converter. To do this, it is shown how the digital delay effects such as the digital pulse-width modulation (DPWM) and the computation delays restrict the bandwidth of the converter. After that, the admittance effect of the entire digital control system is analyzed when the bridgeless PFC converter which has the limited bandwidth is connected to the grid. From this, the waveform distortion of the input current is explained and the compensation method for the admittance component is suggested to improve the quality of the input current. Both the simulations and the experiments are performed to verify the analyses taken in this paper for the 1 kW bridgeless PFC converter prototype.

• KIEE International Transactions on Power Engineering
• /
• v.2A no.4
• /
• pp.136-144
• /
• 2002

Load models are very important for improving the accuracy of stability analysis and load flow studies. Various loads are connected to a power bus and their characteristics of power consumption change with voltage and frequency. Thus, the effect of voltage/frequency changes must be considered in load modeling. In this work, artificial neural networks-ANNs- were used to construct the component load models for more accurate modeling. A typical residential load was selected and subjected to a test under variable voltage/frequency conditions. Acquired data were used to construct component models by ANNs. The aggregation process of separately determined load models is also presented in the paper. Furthermore, this paper proposes a method to transform a single load model constructed by the aggregation method into a mathematical load model that can be used in traditional power system analysis software.