• International Journal of Naval Architecture and Ocean Engineering
• /
• v.12 no.1
• /
• pp.617-635
• /
• 2020

The purpose of this study is to discuss how to improve the maneuverability of lifting and diving for underwater vehicle's vertical motion. Therefore, to solve these problems, applied the 3-D numerical simulation, Taguchi's Design of Experiment (DOE), and intelligent parameter design methods, etc. We planned four steps as follows: firstly, we applied the 2-D flow simulation with NACA series, and then through the Taguchi's dynamic method to analyze the sensitivity (β). Secondly, take the data of pitching torque and total resistance from the Taguchi orthogonal array (L9), the ignal-to-noise ratio (SNR), and analysis each factorial contribution by ANOVA. Thirdly, used Radial Basis Function Network (RBFN) method to train the non-linear meta-modeling and found out the best factorial combination by Particle Swarm Optimization (PSO) and Weighted Percentage Reduction of Quality Loss (WPRQL). Finally, the application of the above methods gives the global optimum for multi-quality characteristics and the robust design configuration, including L/D is 9.4:1, the foreplane on the hull (Bow-2), and position of the sail is 0.25 Ls from the bow. The result shows that the total quality is improved by 86.03% in comparison with the original design.

• 전자공학회논문지 IE
• /
• v.43 no.4
• /
• pp.28-36
• /
• 2006

In this paper, an algorithm to classify the 4 motions of arm and a control system to position control the prosthesis are studied. To classify the 4 motions, we use flex sensors which is electrical resistance type sensor that can measure warp of muscle. The flex sensors are attached to the biceps brchii muscle and coracobrachialis muscle and the sensor signals are passed the sensing system. 4 motion of the forearm - flexion and extension, the pronation and supination are classified from this. Also position of forearm is measured from the classified signals. Finally, A two D.O.F prosthesis arm with RC servo-motor is designed to verify the validity of the algorithm. At this time, fuzzy controller is used to reduce the position error by rotary inertia and noise. From the experiment, the position error had occurred within about 5 degree.

• The Journal of the Acoustical Society of Korea
• /
• v.32 no.5
• /
• pp.408-414
• /
• 2013

The famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems may become unstable in non-stationary noise environment. To solve this problem, Sun's algorithm and Akhtar's algorithm are developed based on modifying the reference signal in update of FxLMS algorithm, but these two algorithms have dissatisfactory stability in dealing with sustaining impulsive noise. In proposed algorithm, probability estimation and zero-crossing rate (ZCR) control are used to improve the stability and performance, at the same time, an optimal parameter selection based on fuzzy system is utilized. Computer simulation results prove the proposed algorithm has faster convergence and better stability in non-stationary noise environment.

• Proceedings of the KSR Conference
• /
• 2008.06a
• /
• pp.339-342
• /
• 2008

In this paper, the lessons and learns are introduced from the result of the trial project which is the first CBTC(Communication Based Train Control System) at Korail Bundang Line. This project has started end of 2002 and finished recently by Samsung SDS. The main purpose of this project was that new technology was seek for next generation of railway signal control system adapted in Korea. In 2002, there was no any revenue service system using Radio Frequency CBTC in the world at that time. Just a few trial project was on going in USA and EU. In well developed cities, the metro system have been built and old enough therefore they have to be considering re-signalling their existing system with advanced system for increasing availabilities of line usage and safety. This Bundang Line Trial Project was the first Korean CBTC project for above reasons. Most sub systems have been developed using local technology such as Electronics Controlled Interlocking System and Track Circuit Systems etc. Specially, in this project the RF-Communication devices are developed by local technology using DSSS(Direct Sequency Spread Spectrum) instead of FHSS(Frequency Hopping Spread Spectrum). This project has lasted for more than five years originally planned for three years because it was only accessible only night time in the main line from Ori to Suseo about 20km long. Each night only 2 and half hours are available to use the main line. Now the trial project has been done successfully with meet the customer's requirement, therefore the upgrade the mainline of Bundang line and another extension area up to Wangsipli to make revenue service using this new technology. This paper shows this result of the trial project and the strategy of upgrade and extension project as well.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.4
• /
• pp.429-434
• /
• 2012

This paper presents a technology for manipulating external devices by Brain Computer Interface (BCI) system. Recently, BCI based rehabilitation and assistance system for disabled people, such as patient of Spinal Cord Injury (SCI), general paralysis, and so on, is attracting tremendous interest. Especially, electroencephalogram (EEG) signal is used to organize the BCI system by analyzing the signals, such as evoked potential. The general findings of neurophysiology support an availability of the EEG-based BCI system. We concentrate on the event-related synchronization of motor imagery EEG signal, which have an affinity with an intention for moving control of external device. To analyze the brain activity, short-time Fourier transform and particle swarm optimization are used to optimal feature selection from the preprocessed EEG signals. In our experiment, we can verify that the power spectral density correspond to range mu-rhythm(${\mu}8$~12Hz) have maximum amplitude among the raw signals and most of particles are concentrated in the corresponding region. Result shows accuracy of subject left hand 40% and right hand 38%.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.4
• /
• pp.40-51
• /
• 2015

This study analysis traffic phase order alternatives to maximize throughput. According to theoretical analysis alternative2(EW: left turn after through, NS: through after left turn) and alternative5(EW: through after left turn, NS: left turn after through) can minimize the maximum delay. Both alternatives split the phase that have the same destination link under the whole cycle length. This shows that phase order alternative can effect to the fully saturated intersection. In side of simulation analysis by microscopic traffic simulator PTV VISSIM F 7.0, each phase order alternatives can't effect throughput under the non saturated condition. However under the saturated condition, the average controlled delay of the intersection has been changed by phase order alternatives. The simulation analysis shows that alternative2 and alternative5 increase throughput 3.8% to 5.1% under the saturated condition.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.1
• /
• pp.90-95
• /
• 2014

The researchs using brain-computer interface, the new interface system which connect human to macine, have been maded to implement the user-assistance devices for control of wheelchairs or input the characters. In recent researches, there are several trials to implement the speech recognitions system based on the brain wave and attempt to silent communication. In this paper, we studied how to extract features of vowel based on international phonetic alphabet (IPA), as a foundation step for implementing of speech recognition system based on electroencephalogram (EEG). We conducted the 2 step experiments with three healthy male subjects, and first step was speaking imagery with single vowel and second step was imagery with successive two vowels. We selected 32 channels, which include frontal lobe related to thinking and temporal lobe related to speech function, among acquired 64 channels. Eigen value of the signal was used for feature vector and support vector machine (SVM) was used for classification. As a result of first step, we should use over than 10th order of feature vector to analyze the EEG signal of speech and if we used 11th order feature vector, the highest average classification rate was 95.63 % in classification between /a/ and /o/, the lowest average classification rate was 86.85 % with /a/ and /u/. In the second step of the experiments, we studied the difference of speech imaginary signals between single and successive two vowels.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.6
• /
• pp.15-22
• /
• 2012

A performance index of singalized intersections is a standard to optimize signal control variables and to manage traffic flow. Traffic delays is generally used to minimize the average delay time on intersections or networks, progression efficiency is used to improve travel speed of main cooridors or to provide transit signal priority. We manage traffic flows with only selecting one index between delays and progression according to the objective of traffic management and field characteristics. In real field, the driver's satisfaction is high in any performance criteria when the waiting time is shorter and the unnecessary stop in front of traffic is smaller. This paper aims to develop simulation model to represent real progression with concurrently considering delays and progression. In order to reflect an effect of level of traffic volumes and residual queues which don't be considered in prior progression model, we apply shockwave model with flow-density diagram. We derive Cell Transmission Model of Daganzo in order to develop the delay index and the progression index for the macroscopic simulation model. In order to validate the effect, we analysis traffic delays and progression efficiency with comparing this model to Transyt-7F and PASSER V.

• Korean Journal of Remote Sensing
• /
• v.14 no.4
• /
• pp.376-391
• /
• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• Journal of Internet Computing and Services
• /
• v.23 no.1
• /
• pp.77-86
• /
• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.