• Journal of Navigation and Port Research
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• v.33 no.6
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• pp.437-442
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• 2009

The PID controller type autopilot is applied to support shipmaneuvering for course-keeping and heading control. A control constants of autopilot system should be evaluated by promoting energy loss (fuel consumption) from the view point of economic efficiency of the ship. This paper is obtained control constants of autopilot system from the RCGA pursued the minimum energy loss. In addition, the controller which is designed involves a constrained optimization problem. The performance of the proposed method is demonstrated through a set of simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1C
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• pp.69-77
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• 2002

Sine digital signal processing for motion pictures requires huge amount of data computation to store, manipulate and transmit, more effective data compression is necessary. Therefore, the ITU-T recommended H.26x as data compression standards for digital motion pictures. The data compression method that eliminates time redundancies by motion estimation using relationship between picture frames has been widely used. Most video conding systems employ block matching algorithm for the motion estimation and compensation, and the algorithm is based on the minimun value of cast functions. Therefore, fast search algorithm rather than full search algorithm is more effective in real time low data rates encodings such as H.26x. In this paper, motion estimation employing the Nearest-Neighbors algorithm is designed to reduce search time using FPGA, coded in VHDL, and simulated and verified using Xilink Foundation.

• The Journal of the Korea Contents Association
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• v.6 no.7
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• pp.90-98
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• 2006

Digital watermarking is a technique embedding hidden information into multimedia data imperceptibly such as images and sounds. Generally an original image is transformed and coded watermark data is embedded in frequency domain watermarking models. In this paper, We propose a new color image watermarking technique using Fresnel transform. A watermark image is Fresnel - transformed and the intensity of transformed pattern is embedded into color image. In our watermarking model, an original image is converted from RGB components into YCrCb components and then the values of real number and imaginary number of a Fresnel-transformed pattern of a watermark image are embedded into Y component. The watermarking experiments were conducted to show the validity of the proposed method using PSNR value, and the results show that our method has the robustness against lossy compression like JPEG.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.555-560
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• 2003

Korean High Speed Train(KHST) has been tested on the high speed test line in Osung site of Korea High Speed Rail Construction Authority (KHRC). since it was developed as G7 Project Plan In 2002. This paper introduces the dynamic test devices in KHST and shows the comparison between the results of test and theoretical computing results which derive from the new model for KHST dynamic behavior. Previous computer simulation model for KHST was developed to review wether the vehicle system was satisfied with the dynamic performance requirements during the design procedure. But It should be applied the results of the parts test for suspension elements in order to compare between the results of computation and real test. Using VAMPIRE Program made by AEA Technology in UK. the new model also was modified. This paper shows that the static wheel loads calculated from new model is similar to test results. For test on high speed line, we prepared the test devices for evaluating the dynamic performances. which was consisted of the accelerometers( based on Kisler Co.) and the data aquisition systems (based on National instrument Co.), and test program coded by LabView 6i program. These lest devices and programs are flexible to extension the channels for adding sensors and connect to the ethernet network. The acceleration of car bodies, bogie frames and axle boxes were compared between the results of computation and test at 150km/. This paper shows that the results of test were high in high frequency band range but similar frequency band range. It might be considered that these differences were caused by the test which did not performed at constant speed for comparison analysis. Also. It will be able to understand the differences and make better results through a lot of tests planed in future.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.33-38
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• 2002

In this paper, a Two-Degree-of-Freedom-Controller(TDFC) for DC motors based on inverse dynamics and the fuzzy technique is presented. The proposed controller includes the inverse dynamic model of a DC motor system, a prefilter and a fuzzy compensator. The model of the system is characterized by a nonlinear equation with coulomb friction. The prefilter eliminates high frequency effects occurring when the inverse dynamic model is implemented. The fuzzy compensator is designed for tracking the change of the reference input and simultaneously regulating the error between the reference input and the system output which can be caused by disturbances. The optimal parameters of both the model and the compensator are identified by a real-coded genetic algorithm. An experimental work on a DC motor system is carried out to verify the performance of the proposed controller.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1900-1906
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• 1997

In this paper, the efficient BILBO(named EBILBO) is designed for BIST that is able to batch the testing when circuit is designed on FPGA. The proposed algorithm of batch testing is able to test the normal operation speed with one-pin-count that can control all part of large and complex circuit. PRTPG is used for the test pattern and MISR is used for PSA. The proposed algorithm of batch testing is VHDL coding on behavioral description, so it is easily modified the model of test pattern generation, signature analysis and compression. The EBILBO's area and the performance of designed BIST are evaluated with ISCAS89 benchmark circuit on FPGA. In circuit with above 600 cells, it is shown that area is reduced below 30%, test pattern is flexibly generated about 500K and the fault coverage is from 88.3% to 100%. EBILBO for the proposed batch testing BIST is able to execute concurrently normal and test mode operation in real time to the number of $s+n+(2^s/2^p-1)$ clock(where, in CUT, # of PI;n, # of register, p is order # of polynomial). The proposed algorithm coded with VHDL is made of library, then it well be widely applied to DFT that satisfy the design and test field on sme time.

• Journal of Korea Water Resources Association
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• v.39 no.1 s.162
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• pp.47-57
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• 2006

This study derives an event-based tank model with a conceptual rainfall-infiltration process, modifying conventional tank models. The model comprises two serial tanks, one parallel tank and an infiltration regulating element. The infiltration process within the element is not represented as a function of only time, but as a function of soil moisture content for three possible cases owing to the relationship between rainfall intensity and infiltration capacity. This study considers the previous soil moisture condition of a watershed by using antecedent precipitation index. Six parameters of the model are identified by using the real coded genetic algorithm. The applicability and validity of the proposed model are assessed for the observed stormwater data from the research basin of the International Hydrological Program, the Pyeongchanggang River basin, Republic of Korea. The results computed streamflows show relatively good agreement with observed ones.

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.851-856
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• 2008

Construction of large-scale container ports with the productivity improvements in container cranes shortened time of staying port to increase the level of service it harbors efforts accelerated. About container crane system exerted on the input, which is designed to look good performance considering the states feedback control system. The states observer designed of container cranes state variables that are expected to measurement noise or particular measurement signal. In the status of existing research, the feedback gain matrix and the state observer gain matrix are searched by being separated solving. But the feedback gain matrix and the state observer gain matrix are searched by RCGAs at once that be used robust search method in this paper.

• Journal of the Korea Society for Simulation
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• v.30 no.4
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• pp.1-8
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• 2021

Deep learning is one of the most widely accepted methods for the forecasting of time series data which have the complexity and non-linear behavior. In this paper, we investigate the modification of a state-of-art WaveNet deep learning architecture and walk forward validation (WFV) in order to forecast electric power consumption data 24-hour-ahead. WaveNet originally designed for raw audio uses 1D dilated causal convolution for long-term information. First of all, we propose a modified version of WaveNet which activates real numbers instead of coded integers. Second, this paper provides with the training process with tuning of major hyper-parameters (i.e., input length, batch size, number of WaveNet blocks, dilation rates, and learning rate scheduler). Finally, performance evaluation results show that the prediction methodology based on WFV performs better than on the traditional holdout validation.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.