• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.1-12
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• 2005

A Mobile manipulator - a serial connection of a mobile robot and a task robot - is a very useful system to achieve various tasks in dangerous environment. because it has the higher performance than a fixed base manipulator in regard to the size of it's operational workspace. Unfortunately the use of a mobile robot introduces non-holonomic constraints, and the combination of a mobile robot and a manipulator generally introduces kinematic redundancy. In this paper, first a method for estimating the position of object at the cartesian coordinate system acquired by using the geometrical relationship between the image captured by 2-DOF active camera mounted on mobile robot and real object is proposed. Second, we propose a method to determine a optimal path between current the position of mobile manipulator whose mobile robot is non-holonomic and the position of object estimated by image information through the global displacement of the system in a symbolic way, using homogenous matrices. Then, we compute the corresponding joint parameters to make the desired displacement coincide with the computed symbolic displacement and object is captured through the control of a manipulator. The effectiveness of proposed method is demonstrated by the simulation and real experiment using the mobile manipulator.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.275-280
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• 2013

Recently, access networking BroadBand the high performance of the video equipment to the Internet via voice, video, multimedia services, such as dealing with the media information dissemination is becoming increasingly attracting attention. More video devices and network environments in the future to keep pace with the high-quality video using the form dealing with an increasingly diversified and shall utilization is expected. Among them, video encoding technology, image compression encoding technology of information technology is one of the central role. Video coding technology that requires a vast amount of information contained in the video signal and the appropriate amount of information to eliminate redundancy as the efficiency of the digital code representing video signal is developed as a technology is going. Therefore, this study applied to video coding mode selection in the cost evaluation methods to examine and to maximize the coding efficiency and the proposed method compared to the conventional method was confirmed excellence.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.10-19
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• 1999

Cellular Automata Neural Systems(CANS) are neural networks based on biological development and evolution. Each neuron of CANS has local connection and acts as a form of pulse according to the dynamics of the chaotic neuron. CANS are generated from initial cells according to the CA rule. In the previous study, to obtain the useful ability of CANS, we make the pattern of initial cells evolve. However, it is impossible to represent all solution space, so we propose an evolving method of CA rule to overcome this defect in this paper. DNA coding has the redundancy and overlapping of gene and is apt for the representation of the rule. In this paper, we show the general expression of CA rule and propose translation method from DNA code to CA rule. The effectiveness of the proposed scheme was verified by applying it to the navigation problem of autonomous mobile robot.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1144-1153
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• 2015

The resonant mechanism of reradiation interference (RRI) over 1.7MHz from power transmission lines cannot be obtained from IEEE standards, which are based on researches of field intensity. Hence, the resonance is ignored in National Standards of protecting distance between UHV power lines and radio stations in China, which would result in an excessive redundancy of protecting distance. Therefore, based on the generalized resonance theory, we proposed the idea of applying model-based parameter estimation (MBPE) to estimate the generalized resonance frequency of electrically large scattering objects. We also deduced equation expressions of the generalized resonance frequency and its quality factor Q in a lossy open electromagnetic system, i.e. an antenna-transmission line system in this paper. Taking the frequency band studied by IEEE and the frequency band over 1.7 MHz as object, we established three models of the RRI from transmission lines, namely the simplified line model, the tower line model considering cross arms and the line-surface mixed model. With the models, we calculated the scattering field of sampling points with equal intervals using method of moments, and then inferred expressions of Padé rational function. After calculating the zero-pole points of the Padé rational function, we eventually got the estimation of the RRI’s generalized resonant frequency. Our case studies indicate that the proposed estimation method is effective for predicting the generalized resonant frequency of RRI in medium frequency (MF, 0.3~3 MHz) band over 1.7 MHz, which expands the frequency band studied by IEEE.

• Journal of Sensor Science and Technology
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• v.8 no.2
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• pp.124-132
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• 1999

In this paper, we propose interband vector quantization of remotely sensed satellite image using edge region compensation. This method classifies each pixel vector considering spectral reflection characteristics of satellite image data. For each class, we perform classified intraband VQ and classified interband VQ to remove intraband and interband redundancies, respectively. In edge region case, edge region is compensated using class information of neighboring blocks and gray value of quantized reference band. Then we perform classified interband VQ to remove interband, redundancy using compensated class information, effectively. Experiments on remotely sensed satellite image show that coding efficiency of the proposed method is better than that of the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3A
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• pp.213-220
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• 2009

Cooperative diversity is a promising technique for range extension and diversity increase without the use of multiple transmit antennas at the user equipment. In this paper, we propose a cooperative hybrid automatic repeat request relay method with adaptive retransmission to increase the throughput when the SNR of a source user is low. In the proposed method, the source user transmits the first segment of a codeword to relay users and a base station. If the base station fails to recover the information from the received packet, it requests the source or some relay users to retransmit the packet previously sent. In addition, the retransmission type of a selected user is chosen from repetition or incremental redundancy according to the quality of systematic bits in a turbo codeword. Simulation results show that the proposed method improves the throughput compared to conventional methods, and the improvement is significant when the source user has a low SNR.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.433-440
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• 2014

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.166-175
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• 2024

In this paper, the Window-Masking Method and HAT (Hardware Attached Top) CPU SoM (System on Module) are used to improve the performance and reduce the weight of the MANET (Mobile Ad-hoc Network) network synchronization system using time division redundancy. We propose converting it into a RISC-V based soft-core MCU and mounting it on an FPGA, a hardware accelerator. It was also verified through experiment. In terms of performance, by applying the proposed technique, the synchronization acquisition range is from -50dBm to +10dBm to -60dBm to +10dBm, the lowest input level for synchronization is increased by 20% from -50dBm to -60dBm, and the detection delay (Latency) is 220ns. Reduced by 43% to 125ns. In terms of weight reduction, computing resources (48%), size (33%), and weight (27%) were reduced by an average of 36% by replacing with soft-core MCU.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.5
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• pp.17-24
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• 2017

Recently Deep-learning, Technologies using Large or Deep Artificial Neural Networks, have Shown Remarkable Performance, and the Increasing Size of the Network Contributes to its Performance Improvement. However, the Increase in the Size of the Neural Network Leads to an Increase in the Calculation Amount, which Causes Problems Such as Circuit Complexity, Price, Heat Generation, and Real-time Restriction. In This Paper, We Propose and Test a Method to Reduce the Number of Network Connections by Effectively Pruning the Redundancy in the Connection and Showing the Difference between the Performance and the Desired Range of the Original Neural Network. In Particular, we Proposed a Simple Method to Improve the Performance by Re-learning and to Guarantee the Desired Performance by Allocating the Error Rate per Layer in Order to Consider the Difference of each Layer. Experiments have been Performed on a Typical Neural Network Structure such as FCN (full connection network) and CNN (convolution neural network) Structure and Confirmed that the Performance Similar to that of the Original Neural Network can be Obtained by Only about 1/10 Connection.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1157-1165
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• 2017

2-D complex Gabor filtering has found numerous applications in the fields of computer vision and image processing. Especially, in some applications, it is often needed to compute 2-D complex Gabor filter bank consisting of the 2-D complex Gabor filtering outputs at multiple orientations and frequencies. Although several approaches for fast 2-D complex Gabor filtering have been proposed, they primarily focus on reducing the runtime of performing the 2-D complex Gabor filtering once at specific orientation and frequency. To obtain the 2-D complex Gabor filter bank output, existing methods are repeatedly applied with respect to multiple orientations and frequencies. In this paper, we propose a novel approach that efficiently computes the 2-D complex Gabor filter bank by reducing the computational redundancy that arises when performing the Gabor filtering at multiple orientations and frequencies. The proposed method first decomposes the Gabor basis kernels to allow a fast convolution with the Gaussian kernel in a separable manner. This enables reducing the runtime of the 2-D complex Gabor filter bank by reusing intermediate results of the 2-D complex Gabor filtering computed at a specific orientation. Experimental results demonstrate that our method runs faster than state-of-the-arts methods for fast 2-D complex Gabor filtering, while maintaining similar filtering quality.