• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.225-231
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• 2013

In this study, we propose the design of optimized pRBFNNs-based night vision face recognition system using PCA algorithm. It is difficalt to obtain images using CCD camera due to low brightness under surround condition without lighting. The quality of the images distorted by low illuminance is improved by using night vision camera and histogram equalization. Ada-Boost algorithm also is used for the detection of face image between face and non-face image area. The dimension of the obtained image data is reduced to low dimension using PCA method. Also we introduce the pRBFNNs as recognition module. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned by using Fuzzy C-Means clustering. In the conclusion part of rules, the connection weights of pRBFNNs is represented as three kinds of polynomials such as linear, quadratic, and modified quadratic. The essential design parameters of the networks are optimized by means of Differential Evolution.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.1
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• pp.17-24
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• 2004

The starter of the turbo generator is composed of a high speed generator(HSG), an inverter and a boost converter instead of a gearbox, a DC motor and a low-voltage battery in the starter of the turbo shaft generation system. Because turbo generator is needed a high speed motoring at start-up, high speed generator has a low leakage inductance and inverter need a high DC link voltage. In this study, for developing the stater of a turbo generator, a boost converter with a high capacity was developed to convert high voltage from a low battery voltage. And for controlling a high frequency current to be injected to a motor winding with a low leakage inductance, the inverter with a high precision and a high speed operation was designed and for a stable ignition, the starting algorithm of a turbo generator was proposed. Turbo generator was started by the starter developed to verify the performances.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.5
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• pp.766-778
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• 2015

In this paper, we design a hybrid system for recognition and tracking realized with the aid of polynomial based RBFNNs pattern classifier and particle filter. The RBFNN classifier is built by learning the training data for diverse pose images. The optimized parameters of RBFNN classifier are obtained by Particle Swarm Optimization(PSO). Testing data for pose image is used as a face image obtained under real situation, where the face image is detected by AdaBoost algorithm. In order to improve the recognition performance for a detected image, pose estimation as preprocessing step is carried out before the face recognition step. PCA is used for pose estimation, the pose of detected image is assigned for the built pose by considering the featured difference between the previously built pose image and the newly detected image. The recognition of detected image is performed through polynomial based RBFNN pattern classifier, and if the detected image is equal to target for tracking, the target will be traced by particle filter in real time. Moreover, when tracking is failed by PF, Adaboost algorithm detects facial area again, and the procedures of both the pose estimation and the image recognition are repeated as mentioned above. Finally, experimental results are compared and analyzed by using Honda/UCSD data known as benchmark DB.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4347-4366
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• 2015

Distinguished with traditional strategies which offload an application's computation to a single server, parallel computation offloading can promote the performance by simultaneously delivering the computation to multiple computing resources around the mobile terminal. However, due to the variability of communication and computation environments, static application component multi-partitioning algorithms are difficult to maintain the optimality of their solutions in time-varying scenarios, whereas, over-frequent algorithm executions triggered by changes of environments may bring excessive algorithm costs. To this end, an adaptive application component mapping algorithm for parallel computation offloading in variable environments is proposed in this paper, which aims at minimizing computation costs and inter-resource communication costs. It can provide the terminal a suitable solution for the current environment with a low incremental algorithm cost. We represent the application component multi-partitioning problem as a graph mapping model, then convert it into a pathfinding problem. A genetic algorithm enhanced by an elite-based immigrants mechanism is designed to obtain the solution adaptively, which can dynamically adjust the precision of the solution and boost the searching speed as transmission and processing speeds change. Simulation results demonstrate that our algorithm can promote the performance efficiently, and it is superior to the traditional approaches under variable environments to a large extent.

• Journal of Power Electronics
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• v.12 no.1
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• pp.172-180
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• 2012

Z-source inverters (ZSI) are used to realize both DC voltage boost and DC-AC inversion in single stage with a reduced number of power switching devices. A traditional MPPT control algorithm provides a shoot-through interval which should be inserted in the switching waveforms of the inverter to output the maximum power to the Z-network. At this instant, the voltage across the Z-source capacitor is equal to the output voltage of a PV array at the maximum power point (MPP). The control of the Z-source capacitor voltage beyond the MPP voltage of a PV array is not facilitated in traditional MPPT algorithms. This paper presents a unified MPPT control algorithm to simultaneously achieve MPPT as well as Z-source capacitor voltage control. Development and implementation of the proposed algorithm and a comparison with traditional results are discussed. The effectiveness of the proposed unified MPPT control strategy is implemented in Matlab/Simulink software and verified by experimental results.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.32-38
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• 2020

The deployment of geographically distributed wireless sensors has greatly elevated the capability of monitoring structural health in social-overhead capital (SOC) public infrastructures. This paper deals with the utilization of a distributed mobility management (DMM) approach for the deployment of wireless sensing devices in a structural health monitoring system (SHM). Then, a wireless sensing mechanism utilizing low-energy adaptive clustering hierarchy (LEACH)-based clustering algorithm for smart sensors has been analyzed to support the seamless data transmission of structural health information which is essentially important to guarantee public safety. The clustering of smart sensors will be able to provide real-time monitoring of structural health and a filtering algorithm to boost the transmission of critical information over heterogeneous wireless and mobile networks.

• New & Renewable Energy
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• v.3 no.4
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• pp.69-76
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• 2007

In this paper, a PV multi-string PCS with a grid-connection is proposed. An improved MPPT algorithm for the PV multi-string PCS is suggested. Each PV string has its own MPP tracker and the proposed MPPT algorithm prevents LMPP tracking due to power ripple. In the PV PCS with single-phase inverter has a large current ripple at twice the grid frequency. The current ripple reduction algorithm without external component is suggested. Also, this paper proposes a simple control method to achieve sharing of the PV string voltage and current among the interleaved parallel boost converters. All algorithms and controllers are implemented on a single-chip microcontroller. Experimental results obtained on a 3kW prototype show high performance of the proposed PV multi-string PCS.

• Journal of Power Electronics
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• v.18 no.4
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• pp.1201-1210
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• 2018

The applications of thermoelectric generators (TEGs) have received a lot of attention both in terms of harvesting waste thermal energy and the need for multi-levels of power. It is critical to track the optimum electrical operating point using DC to DC converters controlled by a pulse that is generated through a maximum power point tracking algorithm (MPPT). In this paper, the hardware implementation of a short-current pulse algorithm has been demonstrated under steady stated and transient conditions. In addition, the MPPT algorithm has been proposed, which is one of the most effective and applicable algorithms for obtaining the maximum power point of TEGs. During this study, the proposed prototype has been validated both analytically and experimentally. It has also demonstrated successful performance, which highlights the claimed advantages of the proposed MPPT solution.

• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.255-258
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• 2007

In this paper, a PV multi-string PCS with a grid-connection is proposed. An improved MPPT algorithm for the PV multi-string PCS is suggested. Each PV string has its own MPP tracker and the proposed MPPT algorithm prevents LMPP tracking due to power ripple. In the PV PCS with single-phase inverter has a large current ripple at twice the grid frequency. The current ripple reduction algorithm without external component is suggested. Also, this paper proposes a simple control method to achieve sharing of the PV string voltage and current among the interleaved parallel boost converters. All algorithms and controllers are implemented on a single-chip microcontroller. Experimental results obtained on a 3kW prototype show high performance of the proposed PV multi-string PCS.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.455-464
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• 2014

Unlabeled examples are easier and less expensive to obtain than labeled examples. Semisupervised approaches are used to utilize such examples in an eort to boost the predictive performance. This paper proposes a novel semisupervised classication method named transductive least squares support vector machine (TLS-SVM), which is based on the least squares support vector machine. The proposed method utilizes the dierence convex algorithm to derive nonconvex minimization solutions for the TLS-SVM. A generalized cross validation method is also developed to choose the hyperparameters that aect the performance of the TLS-SVM. The experimental results conrm the successful performance of the proposed TLS-SVM.