• Structural Engineering and Mechanics
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• v.35 no.1
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• pp.19-35
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• 2010

This paper proposes a hybrid heuristic and criteria-based method of optimum design which combines the advantages of both the iterated simulated annealing (SA) algorithm and the rigorously derived optimality criteria (OC) for structural optimum design of reinforced concrete (RC) buildings under multi-load cases based on the current Chinese design codes. The entire optimum design procedure is divided into two parts: strength optimum design and stiffness optimum design. A modified SA with the strategy of adaptive feasible region is proposed to perform the discrete optimization of RC frame structures under the strength constraints. The optimum stiffness design is conducted using OC method with the optimum results of strength optimum design as the lower bounds of member size. The proposed method is integrated into the commercial software packages for building structural design, SATWE, and for finite element analysis, ANSYS, for practical applications. Finally, two practical frame-shear-wall structures (15-story and 30-story) are optimized to illustrate the effectiveness and practicality of the proposed optimum design method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1485-1490
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• 2005

Variable length code is an integral component of many international standards on image and video compression currently. Context-based Adaptive Variable Length Coding(CAVLC) is adopted by the emerging JVT(also called H.264, and AVC in MPEG-4). In this paper, we design an architecture for CAVLC encoder, including a coeff_token encoder, level encoder, total_zeros encoder and run_before encoder. The designed CAVLC encoder can encode one syntax element in one clock cycle. As a result of implementation by Vertex-1000e of Xilinx, its operation frequency is 68MHz. Therefore, it is very suitable for video applications that require high throughput.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.179-188
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• 2017

The Internet Video Coding (IVC) standard is due to be published by Moving Picture Experts Group (MPEG) for various Internet applications such as internet broadcast streaming. IVC aims at three things fundamentally: 1) forming IVC patents under a free of charge license, 2) reaching comparable compression performance to AVC/H.264 constrained Baseline Profile (cBP), and 3) maintaining computational complexity for feasible implementation of real-time encoding and decoding. MPEG experts have worked diligently on the intellectual property rights issues for IVC, and they reported that IVC already achieved the second goal (compression performance) and even showed comparable performance to even AVC/H.264 High Profile (HP). For the complexity issue, however, there has not been thorough analysis on IVC decoder. In this paper, we analyze the IVC decoder in view of the time complexity by evaluating running time. Through the experimental results, IVC is 3.6 times and 3.1 times more complex than AVC/H.264 cBP under constrained set (CS) 1 and CS2, respectively. Compared to AVC/H.264 HP, IVC is 2.8 times and 2.9 times slower in decoding time under CS1 and CS2, respectively. The most critical tool to be improved for lightweight IVC decoder is motion compensation process containing a resolution-adaptive interpolation filtering process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1120-1129
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• 2015

In this paper, we propose an algorithm to detect movement noise in PPG(Photoplethysmography) measurements. Movement noise significantly deteriorate PPG signals in measurement, so that a movement noise detection algorithm is critical before using measured PPG signals for applications such as diagnosis. To detect movement noise, we apply wavelet transform to PPG signals instead of short-time Fourier transform and decide if the measured signlas include movement noise. To that end, we adaptively choose a wavelet, which is the most similar to the subject's PPG pattern. In the case when movement noise is intentionally added in the 20% and 30% of the total experiment time, our algorithm detects time-slots including movement and outperforms previous works.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.89-95
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• 2017

Ship detection in synthetic aperture radar(SAR)imagery has long been an active research topic and has many applications. In this paper,we propose an efficient method for detecting ships from SAR imagery using filtering. This method exploits ship masking using a median filter that considers maximum ship sizes and detects ships from the reference image, to which a Non-Local means (NL-means) filter is applied for speckle de-noising and a differential image created from the difference between the reference image and the median filtered image. As the pixels of the ship in the SAR imagery have sufficiently higher values than the surrounding sea, the ship detection process is composed primarily of filtering based on this characteristic. The performance test for this method is validated using KOMPSAT-5 (Korea Multi-Purpose Satellite-5) SAR imagery. According to the accuracy assessment, the overall accuracy of the region that does not include land is 76.79%, and user accuracy is 71.31%. It is demonstrated that the proposed detection method is suitable to detect ships in SAR imagery and enables us to detect ships more easily and efficiently.

• ETRI Journal
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• v.25 no.5
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• pp.356-368
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• 2003

This paper analyzes the characteristics of packet losses in mobile computing environments based on the Gilbert model and then describes a mechanism that can recover the lost audio packets using redundant data. Using information periodically reported by a receiver, the sender dynamically adjusts the amount and offset values of redundant data with the constraint of minimizing the bandwidth consumption of wireless links. Since mobile computing environments can be often characterized by frequent and consecutive packet losses, loss recovery mechanism need to deal efficiently with both random and consecutive packet losses. To achieve this, the suggested mechanism uses relatively large, discontinuous exponential offset values. That gives the same effect as using both the sequential and interleaving redundant information. To verify the effectiveness of the mechanism, we extended and implemented RTP/RTCP and applications. The experimental results show that our mechanism, with an exponential offset, achieves a remarkably low complete packet loss rate and adapts dynamically to the fluctuation of the packet loss pattern in mobile computing environments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.565-570
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• 2009

Micro particles in fluid can be manipulated by using ultrasonic standing wave since the ultrasound makes particles move by means of its acoustic radiation force. This work concerns the micro particle manipulation system using ultrasonic standing wave which consists of a microchannel, an adaptive layer, a reflector, and an ultrasonic transduer. In the present system, the effects of the structural elements should be carefully considered to comprehend the system and find the optimal operational condition. In this investigation, finite element analysis was employed to analyze the system. Some interesting characteristics on the reflector thickness, the channel width, and the operational frequency were observed. Several experimental results were compared with the analytic results. Consequently, this work solidifies the importance of those system parameters and reveals the possibility of various applications of the particle manipulation using ultrasonic standing wave.

• Journal of the Korean Institute of Navigation
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• v.23 no.3
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.566-569
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• 2005

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using artificial intelligent(AI) controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using learning mechanism fuzzy neural network(LM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also. this paper is proposed the experimental results to verify the effectiveness of AI controller.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2670-2685
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• 2020

Flying ad-hoc networks (FANETs) is a vibrant research area nowadays. This type of network ranges from various military and civilian applications. FANET is formed by micro and macro UAVs. Among many other problems, there are two main issues in FANET. Limited energy and high mobility of FANET nodes effect the flight time and routing directly. Clustering is a remedy to handle these types of problems. In this paper, an efficient clustering technique is proposed to handle routing and energy problems. Transmission range of FANET nodes is dynamically tuned accordingly as per their operational requirement. By optimizing the transmission range packet loss ratio (PLR) is minimized and link quality is improved which leads towards reduced energy consumption. To elect optimal cluster heads (CHs) based on their fitness we use k-means. Selection of optimal CHs reduce the routing overhead and improves energy consumption. Our proposed scheme outclasses the existing state-of-the-art techniques, ACO based CACONET and PSO based CLPSO, in terms of energy consumption and cluster building time.