• Computers and Concrete
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• v.17 no.6
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• pp.761-786
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• 2016

This paper proposes an automated procedure for optimum seismic design of reinforced concrete (RC) frame structures. This procedure combines a smart pre-processing using a Tree Classification Method (TCM) and a nonlinear optimization technique. First, the TCM automatically creates sections database and assigns sections to structural members. Subsequently, a real valued model of Particle Swarm Optimization (PSO) algorithm is employed in solving the optimization problem. Numerical examples on design optimization of three low- to high-rise RC frame structures under earthquake loads are presented with and without considering strong column-weak beam (SCWB) constraint. Results demonstrate the effectiveness of the TCMin seismic design optimization of the structures.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1122-1129
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• 2009

Recently taping robot with smart recognition function have been studied in the coil manufacturing field. Due to the difficulty of 3D surface processing from the complicated working environment, it is not easy to accomplish smart tape attachment motion with non-contact sensor. To solve these problems the applicable surface recognition algorithm and a flexible sensing device has been recommended. In this research, the fusion method between 1D displacement and 3D laser scanner is applied for robust tape attachment about cold rolled coil. With these sensors we develop a two-step exploration and the smart algorithm for the awareness of non-aligned coil's information. In the proposed robot system for tape attachment, the problem is reduced to coil's radius searching with laser displacement sensor at first, and then position and orientation detection with 3D laser scanner. To get the movement at the robot's base frame, the hand-eye compensation between robot's end effector and sensing device should be also carried out respectively. In this paper, we examine the auto-coordinate transformation method in the calibration step for the real environment usage. From the experimental results, it was shown that the taping motion of robot had a robust under the non-aligned cold rolled coil.

• Land and Housing Review
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• v.10 no.1
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• pp.19-23
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• 2019

In recent years, many studies have been conducted on smart low carbon cities through the fusion of ICT information technology for the purpose of reducing carbon. In this study, we investigated 13 cities in three continents that implement low-carbon city policies and analyzed the size, economic and social characteristics of each city to identify the degree of dynamic mechanism for carbon reduction. To this end, we quantified the elements of the city and analyzed the basic requirements for low-carbon cities using the TOPSIS method. The study found that most cities were better able to activate institutions and cultural conditions, facilities and functional conditions, and economic and industrial conditions than other engines, and these three were the main forms of power for smart low carbon cities. The results of this study are expected to be used as a basis for suggesting policy recommendations and improvement measures for future smart low carbon cities.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.1
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• pp.1-11
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• 2004

This paper presents an implementation of smart antenna system channel card that executes modulation/demodulation. Operations and performances of modules of implemented channel card is confirmed and field test of channel card shows the performance of smart antenna systems. Based on the analysis obtained from the field test in cdma2000 1x environments which contains multipath lading, it is confirmed that smart antenna system channel card provide exact beampattern to the DOA and performance of proposed channel card has better FER by 5∼8 times, compared to 2 antenna diversity system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1040-1057
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• 2014

In this paper, a new bit rate estimation scheme is proposed to determine the bit rate for each subclass in an MPEG-2 TS to H.264/AVC transcoder after dividing an input MPEG-2 TS sequence into several subclasses. Video format transcoding in conventional IPTV and Smart TV services is a time-consuming process since the input sequence should be fully transcoded several times with different bit-rates to decide the bit-rate suitable for a service. The proposed scheme can automatically decide the bit-rate for the transcoded video sequence in those services which can be stored on a video streaming server as small as possible without losing any subject quality loss. In the proposed scheme, an input sequence to the transcoder is sub-classified by hierarchical clustering using a parameter value extracted from each frame. The candidate frames of each subclass are used to estimate the bit rate using a statistical analysis and a mathematical model. Experimental results show that the proposed scheme reduces the bit rate by, on an average approximately 52% in low-complexity video and 6% in high-complexity video with negligible degradation in subjective quality.

• Smart Media Journal
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• v.4 no.2
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• pp.26-33
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• 2015

In this paper, we propose an efficient automatic pedestrian removal system from a frame in a video sequence. It firstly finds pedestrians from the frame using a Histogram of Oriented Gradient(HOG) / Linear-Support Vector Machine(L-SVM) classifier, searches for proper background patches, and then the patches are used to replace the deleted pedestrians. Background patches are retrieved from the reference video sequence and a modified feather blender algorithm is applied to make boundaries of replaced blocks look naturally. The proposed system, is designed to automatically detect object and generate natural-looking patches, while most existing systems provide search operation in manual. In the experiment, the average PSNR of the replaced blocks is 19.246

• Smart Structures and Systems
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• v.15 no.4
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• pp.963-995
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• 2015

The effectiveness of the various control algorithms for semi-active structural control systems proposed in the literature is highly questionable when dealing with earthquake actions, which never reach a steady state. From this perspective, the paper summarizes the results of an experimental activity aimed to compare the effectiveness of four different semi-active control algorithms on a structural mock up representative of a class of structural systems particularly prone to seismic actions. The controlled structure is a near full scale 2-story steel frame, equipped with two semi-active bracing systems including two magnetorheological dampers designed and manufactured in Europe. A set of earthquake records has been applied at the base of the structure, by utilizing a shaking table facility. Experimental results are compared in terms of displacements, absolute accelerations and energy dissipation capability. A further analysis on the percentage incidence of undesired and/or unpredictable operations corresponding to each algorithm gives an insight on some factors affecting the reliability and, in turn, the real effectiveness of semi-active structural control systems.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1543-1567
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• 2015

In this study, a wireless crack sensor is developed for monitoring cracks propagating in two dimensions. This sensor is developed by incorporating a laser-based optical navigation sensor board (ADNS-9500) into a smart wireless platform (Imote2). To measure crack propagation, the Imote2 sends a signal to the ADNS-9500 to collect a sequence of images reflected from the concrete surface. These acquired images can be processed in the ADNS-9500 directly (the navigation mode) or sent to Imote2 for processing (the frame capture mode). The computed crack displacement can then be transmitted wirelessly to a base station. The design and the construction of this sensor are reported herein followed by some calibration tests on one prototype sensor. Test results show that the sensor can provide sub-millimeter accuracy under sinusoidal and step movement. Also, the two modes of operation offer complementary performance as the navigation mode is more accurate in tracking large amplitude and fast crack movement while the frame capture mode is more accurate for small and slow crack movement. These results illustrate the feasibility of developing such a crack sensor as well as point out directions of further research before its actual implementation.

• Smart Structures and Systems
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• v.18 no.6
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• pp.1189-1202
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• 2016

This paper describes an application of wavelet analysis for damage detection of a steel frame structure with bolted connections. The wavelet coefficients of the acceleration response for the healthy and loosened connection structure were calculated at each measurement point. The difference of the wavelet coefficients of the response of the healthy and loosened connection structure is selected as an indicator of the damage. At each node of structure the norm of the difference of the wavelet coefficients matrix is then calculated. The point for which the norm has the higher value is a candidate for location of the damage. The above procedure was experimentally verified on a laboratory-scale 2-meter-long steel frame. The structure consists of 11 steel beams forming a four-bay frame, which is subjected to impact loads using a modal hammer. The accelerations are measured at 20 different locations on the frame, including joints and beam elements. Two states of the structure are considered: healthy and damaged one. The damage is introduced by means of loosening two out of three bolts at one of the frame connections. Calculating the norm of the difference of the wavelet coefficients matrix at each node the higher value was found to be at the same location where the bolts were loosened. The presented experiment showed the effectiveness of the wavelet approach to damage detection of frame structures assembled using bolted connections.

• Smart Media Journal
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• v.9 no.4
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• pp.102-108
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• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.