• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.414-424
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• 2012

Finding or automatically generating problem instance is useful for algorithm analysis/test. The topic has been of interest in the field of hardware/software engineering and theory of computation. We apply objective value-distance correlation analysis to problem spaces, as previous researchers applied it to solution spaces. According to problems, we define the objective function by (1) execution time of tested algorithm or (2) its optimality; this definition is interpreted as difficulty of the problem instance being solved. Our correlation analysis is based on the following aspects: (1) change of correlation when we use different algorithms or different distance functions for the same problem, (2) change of that when we improve the tested algorithm, (3) relation between a problem instance space and the solution space for the same problem. Our research demonstrates the way of problem instance space analysis and will accelerate the problem instance space analysis as an initiative research.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.9-16
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• 2011

Due to the development and proliferation of ubiquitous technologies and services, various sensor network applications are being appeared on the stage. The needs for algorithms requiring sensor data fusion and complex signal processing with a high-performance processor such as a digital signal processor are also increased. However, it is difficult to use such processor for the low-power sensor network operating with a battery because of power consumption. This paper proposes a hybrid-type sensor module architecture supporting wakeup/sleep software framework for the wireless sensor node and shows the implemented sensor node platform and performances focused on the energy consumption and wakeup time.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.113-121
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• 1989

A software interface called CGI-K including device driver routines and graphics primitives for the grphic board "K" was designed, implemented in the Design Automation Laboratory of KAIST and installed on IBM PC/AT, using assembly and C language supported by TMS 34010 grphics processor. Several algorithms generating the graphics primitives such as box, circle, pie chord are proposed. The drawing speed of CGI-K on the graphic board K was found out to be three to ten times faster than that of the EGA for several examples. A 2-D graphics editor called GRIM (graphics input and modification) and a 3-dimensional graphics renderer called IPCHE which can draw 3-D objects were developed as two major application programs running on CGI-K. The graphics primitives supported in GRIM include polygon, box, circle, and ace. The IPCHE receives a 3-D objects data file and displays the 3-D object on the screen with hidden surface removal, shading, and perspective scaling.

• Smart Structures and Systems
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• v.26 no.1
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• pp.35-47
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• 2020

This paper proposes the use of transmissibility functions combined with a machine learning algorithm, Artificial Neural Networks (ANNs), to assess damage in a truss bridge. A new approach method, which makes use of the input parameters calculated from the transmissibility function, is proposed. The network not only can predict the existence of damage, but also can classify the damage types and identity the location of the damage. Sensors are installed in the truss joints in order to measure the bridge vibration responses under train and ambient excitations. A finite element (FE) model is constructed for the bridge and updated using FE software and experimental data. Both single damage and multiple damage cases are simulated in the bridge model with different scenarios. In each scenario, the vibration responses at the considered nodes are recorded and then used to calculate the transmissibility functions. The transmissibility damage indicators are calculated and stored as ANNs inputs. The outputs of the ANNs are the damage type, location and severity. Two machine learning algorithms are used; one for classifying the type and location of damage, whereas the other for finding the severity of damage. The measurements of the Nam O bridge, a truss railway bridge in Vietnam, is used to illustrate the method. The proposed method not only can distinguish the damage type, but also it can accurately identify damage level.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.2
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• pp.10-16
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• 2012

Currently, the majority of systems which are non-linear are in need of the correct system equations for controlling and monitoring. Therefore, the correct estimation of parameters is crucial. Generally, parameters are changed due to system deterioration or sudden environmental alterations. Given the limitations of system monitoring unstable controls can arise. In the following paper, the parameter estimation method is proposed using software filters to combat these system instabilities. For dynamic instances, a powerful particle filter is used to control the nonlinear and noisy environments in which they take place. Using a setup simulation comprised of a slider and pendulum, the state variable of noise is obtained. After collecting the data, the proposed algorithm is used to estimate both the state variable and its parameters. Finally, these results are checked with correct parameter estimations to evaluate and verify the algorithms performance.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.347-350
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• 2006

Maritime and Ocean Engineering Research Institute (MOERI), a branch of KORDI, has designed and manufactured a model of an autonomous underwater vehicle (AUV) named ISiMI(Integrated Submergible for Intelligent Mission Implementation). ISiMI is an AUV platform to satisfy the various needs of experimental test required for development of challenging technologies newly investigated in the field of underwater robot; control and navigational algorithms and software architectures. The main design goal of ISiMI AUV is downsizing which will reduce substantially the operating cost compared to other vehicles previously developed in KORDI such as VORAM or DUSAUV. As a result of design and manufacturing process, ISiMI is implemented to be 1.2m in length, 0.17m in diameter and weigh 20 kg in air. A series of tank test is conducted to verify the basic functions of ISiMI in the Ocean Engineering Basin of MOERI, which includes manual control with R/F link, auto depth, auto heading control and a final approach control for underwater docking. This paper describes the implementation of ISiMI system and the experimental results to verify the function of ISiMi as a test-bed AUV platform.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.6 s.336
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• pp.39-48
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• 2005

This paper proposes a reconfigurable coprocessor for communication systems, which can perform high speed computations and various functions. The proposed reconfigurable coprocessor can easily implement communication operations, such as scrambling, interleaving, convolutional encoding, Viterbi decoding, FFT, etc. The proposed architecture has been modeled by VHDL and synthesized using the SEC 0.18$\mu$m standard cell library. The gate count is about 35,000 gates and the critical path is 3.84ns. The proposed coprocessor can reduced about $33\%$ for FFT operations and complex MAC, $37\%$ for Viterbi operations, and $48\%\~84\%$ for scrambling and convolutional encoding for the IEEE 802.11a WLAN standard compared with existing DSPs. The proposed coprocessor shows Performance improvements compared with existing DSP chips for communication algorithms.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.5
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• pp.58-65
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• 2007

As multimedia portable devices become popular, the amount of computation for processing data including video compression has significantly increased. Various researches for low power consumption of the mobile devices and real time processing have been reported. Motion Estimation is responsible for 67% of H.264 encoder complexity. In this research, a new circuit is designed for motion estimation. The new circuit uses motion prediction based on approximate SAD, Alternative Row Scan (ARS), DAU, and FDVS algorithms. Our new method can reduce the amount of computation by 75% when compared to multi-frame motion estimation suggested in JM8.2. Furthermore, optimal number and size of reference frame blocks are determined to reduce computation without affecting the PSNR. The proposed Motion Estimation method has been verified by using the hardware and software Co-Simulation with iPROVE. It can process 30 CIF frames/sec at 50MHz.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.357-365
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• 2005

We present a B-spline fitting method based on genetic algorithm for the extraction of object contours from the complex image sequence, where objects with similar shape and intensity are adjacent each other. The proposed algorithm solves common malfitting problem of the existing B-spline fitting methods including snakes. Classical snake algorithms have not been successful in such an image sequence due to the difficulty in initialization and existence of multiple extrema. We propose a B-spline fitting method using a genetic algorithm with a new initial population generation and fitting function, that are designed to take advantage of the contour of the previous slice. The test results show that the proposed method extracts contour of individual object successfully from the complex image sequence. We validate the algorithm by false-positive/negative errors and relative amounts of agreements.