• Journal of Industrial Technology
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• v.22 no.A
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• pp.101-105
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• 2002

Counters for various kinds of bank notes require high-speed distinctive point extraction and recognition for notes. In this paper we propose a new point extraction and data extraction method from specific parts of a bank note representing the same color. The recognition algorithm uses a back-propagation neural network that has coordinate data input. The proposed algorithm is designed to minimize recognition time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.129-134
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• 2018

Research on the technique for estimating the indoor position has been actively carried out. In particular, the WiFi fingerprint method, which does not require any additional infrastructure, is being partially used because of its high economic efficiency. The KNN method which estimates similar points to the corresponding points by comparing intensity information of the WLAN reception signal measured at various points in advance with intensity information measured at a specific point in the future is simple but has a good performance. However, in the conventional KNN scheme, since the number K of average candidate positions is constant, there is a problem that the position estimation error is not optimized according to a specific point. In this paper, we proposed an algorithm that adaptively changes the K value for each point and applied it to experimental data and evaluated its performance.

• The Journal of the Korea Contents Association
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• v.14 no.3
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• pp.33-39
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• 2014

Domestic and international researches, about intelligent systems based on a variety of location recognitions using location information, have actively proceeded. The representative location recognition method based on PTMP(Point To Multi Point) communication uses TOA(Time Of Arrival) to calculate distances to a fixed node that you want to recognize a position. The method is used to obtain the fixed node location information from three nodes location information that is applied by the triangulation method. There are disadvantages, an infrastructure should be established at a specific space and the system established cost is needed, in the location recognition method based on the PTMP communication, In this paper, the ranging based PTP(Point To Point) location recognition method is proposed to revise the disadvantage of PTMP location recognition method. And then it is compared with PTMP communication location recognition to evaluate performance. In this way, PTMP and PTP communication location recognition systems based on ranging were constructed and tested in an indoor environment. Experiment results show that the proposed PTP location recognition method could be confirmed to improve accuracy more than 3 times when it was compared with the existed PTMP location recognition method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.3
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• pp.111-115
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• 2012

Generally, brushless DC motor(BLDCM) driving system uses hall sensors or encoders as the mechanical position or speed sensor. It is necessary to achieve the informations of rotor position for driving trapezoidal type brushless DC motor without any position sensor. In this paper, the commutation signals are obtained without the motor neutral voltage, multistage analog filters, A/D converters, or the complex digital phase shift circuits which are indispensable in the conventional sensorless control algorithms. In the proposed method, in stead of detecting the zero crossing point of the nonexcited motor back electromagnetic force for the average motor terminal to neutral voltage, the commutation signal are extracted directly from the specific average line to line voltage with low-pass filter, adder and comparators circuit. In contrast to conventional methods, the neutral voltage is not need; therefore, the commutation signals are insensitive to the common mode noise. Moreover, the complex phase shift circuit can be eliminated. The effectiveness of the proposed method is verified through simulation results.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.42-52
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• 2006

In order to utilize hydrodynamic drag force on articulated robots moving in an underwater environment, an optimum motion planning procedure is proposed. The drag force acting on cylindrical underwater arms is modeled and a directional drag measure is defined as a quantitative measure of reaction force in a specific direction in a workspace. A repetitive trajectory planning method is formulated from the general point-to-point trajectory planning method. In order to globally optimize the parameters of repetitive trajectories under inequality constraints, a 2-level optimization scheme is proposed, which adopts the genetic algorithm (GA) as the 1st level optimization and sequential quadratic programming (SQP) as the 2nd level optimization. To verify the validity of the proposed method, optimization examples of periodic motion planning with the simple two-link planner robot are also presented in this paper.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.189-198
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• 2021

In this paper, we introduce the software/hardware system that can reliably calculate the distance from sensor to the model regardless of point cloud density. As the 3d point cloud map is widely adopted for SLAM and computer vision, the accuracy of point cloud map is of great importance. However, the 3D point cloud map obtained from Lidar may reveal different point cloud density depending on the choice of sensor, measurement distance and the object shape. Currently, when measuring map accuracy, high reflective bands are used to generate specific points in point cloud map where distances are measured manually. This manual process is time and labor consuming being highly affected by Lidar sparsity level. To overcome these problems, this paper presents a hardware design that leverage high intensity point from three planar surface. Furthermore, by calculating distance from sensor to the device, we verified that the automated method is much faster than the manual procedure and robust to sparsity by testing with RGB-D camera and Lidar. As will be shown, the system performance is not limited to indoor environment by progressing the experiment using Lidar sensor at outdoor environment.

• International Journal of Korean Welding Society
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• v.2 no.2
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• pp.14-18
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• 2002

Titanium and titanium alloy are excellent in corrosion resistance and specific intensity, and also in the biocompatibility. On the other hand, the brazing is bonding method of which productivity and reliability are high, when the complicated and precise structure of the thin plate is constructed. However, though conventional titanium-based brazing filler metal was excellent in bond strength and corrosion resistance, it was disadvantageous that metal structure and mechanical property of the base metal deteriorated, since the brazing temperature ( about $1000^{\circ}C$ ) is considerably high. Authors developed new brazing filler metal which added Zr to Ti-Cu (-Ni) alloy which can be brazed at $900^{\circ}C$ or less about 15 years ago. In this paper, the development of more low-melting-point brazing filler metal was tried by the addition of the fourth elements such as Ni, Co, Cr for the Ti-Zr-Cu alloy. As a method for finding the low-melting-point composition, eutectic composition exploration method was used in order to reduce the experiment point. As the result, several kinds of new brazing filler metal such as 37.5Ti-37.5-Zr-25Cu alloy (melting point: $825^{\circ}C$) and 30Ti-43Zr-25Cu-2Cr alloy (melting point: $825^{\circ}C$) was developed. Then, the brazing joint showed the characteristics which were almost equal to the base metal from the result of obtaining metallic structure and strength of joint of brazing joint. However, the brazing filler metal composition of the melting point of $820^{\circ}C$ or less could not be found. Consequentially, it was clarified that the brazing filler metal developed in this study could be practically sufficiently used from results such as metal structure of brazing joint and tensile test of the joint.

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.369-388
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• 2023

In this paper, we develop the two-step procedure that detects and estimates the position of structural changes for multivariate nonstationary time series, either on mean parameters or second-order structures. We first investigate the presence of mean structural change by monitoring data through the aggregated cumulative sum (CUSUM) type statistic, a sequential procedure identifying the likely position of the change point on its trend. If no mean change point is detected, the proposed method proceeds to scan the second-order structural change by modeling the multivariate nonstationary time series with a multivariate locally stationary Wavelet process, allowing the time-localized auto-correlation and cross-dependence. Under this framework, the estimated dynamic spectral matrices derived from the local wavelet periodogram capture the time-evolving scale-specific auto- and cross-dependence features of data. We then monitor the change point from the lower-dimensional approximated space of the spectral matrices over time by applying the dynamic principal component analysis. Different from existing methods requiring prior information on the type of changes between mean and covariance structures as an input for the implementation, the proposed algorithm provides the output indicating the type of change and the estimated location of its occurrence. The performance of the proposed method is demonstrated in simulations and the analysis of two real finance datasets.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.187-201
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• 1994

This paper introduces an effective hybridization of the usual simplex method and an interior point method in the convergent framework of Dembo and Sahi. We formulate a specific and detailed algorithm (HYBRID) and report the results of some preliminary testing on small dense problems for its viability. By piercing through the feasible region, the newly developed hybrid algorithm avoids the combinatorial structure of linear programs, and several other interesting and important characteristics of this algorithm are also discussed.

• Journal of Biosystems Engineering
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• v.33 no.1
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• pp.21-29
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• 2008

In this study, the thermal properties of peeled chestnuts were measured, and the mathematical prediction model of freezing time was also developed for various interior positions from center to rind (surface). The measured thermal properties were showed that heat conductivity is $0.43W/m^{\circ}C$, specific heat is $2.7206J/m^3^{\circ}C$, latent heat is $216.9{\times}10^6J/m^3$ and freezing point is $-2.8^{\circ}C$. The entire process about reaching to the freezing time of peeled chestnuts was analyzed with its each regular depth position using the finite difference method (FDM) based on computer simulation. In case of regular freezing temperature, it was showed an that surface (rind) position is more rapidly reached into the freezing point rather than the center position, and also reaching time to the freezing point is more fast at the lower freezing temperature. Comparison results between simulation and experiments showed linear relationship. In regularly varying condition for freezing temperature, this method would give an information to predict a freezing time of the interior points for peeled chestnuts and more similar agricultural products.