• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.23-32
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• 2006

This study shows that new methodology improved the problem of unaided eye test level with the digital orthophoto technique can survey more objectively and efficiently any cadastral non-coincidence than existing prior methodologies. For applying to it, we explore eligible other methodologies, and then build up the application strategy of them. New prototype system is implemented with it. Also, we say the availability of new methodology by applying to study area. As a result, we suggest cadastral non-coincidence surveying method based on point-correspondence more objective and more efficient. As a result of comparing with old method and new on same study area for making adequacy, they hardly ever has the difference of accuracy. Constantly, cadastral non-coincidence surveying method based on point-correspondence is acceptable way on the cadastral survey.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.48-55
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• 2002

This paper deals with the sensing ability of the smart sensor that has the sensing ability to distinguish materials according to the input condition changing. This is a study of dynamic characteristics of sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. Experiments and analysis were executed to estimate ability to recognize objects according to the input condition. First, we developed the advanced smart sensor. Second, we developed the new method, which has the capability sensing of different materials. Dynamic characteristics of the smart sensor were evaluated relatively through a new $R_{SAI}$ method. According to frequency changing, influence of the smart sensor are evaluated through a new recognition index ($R_{SAI}$) that ratio of sensing ability index. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safely diagnosis of structure, etc.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1553-1560
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• 2008

The modern logistics has tried not only to convert the conventional packing system into unit load system using pallet but also to enhance the fitness between packing facilities and transport modes. This is based on the goal to reduce total logistics cost using logistics efficiency. Because the packing unit can affect on both loading rate and loading facilities, the basic form of packing unit is very important to the unit load system. In Korea, the standardization of logistics has been centered on pallet, and the basic condition will be continued except of the variety of standardized pallet form. Because of this, to enhance the standardization of pallet, it is necessary to develop new standard size and form of pallet. The object of this study is to develop a new method of collecting the effectiveness of standardized packing module. The new method is based on measure of effectiveness (MOE) which can be developed by expert survey. This study has originality from the fact that the collecting method for effectiveness of pallet standardization has not been developed up to now.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.335-352
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• 2012

Particle Swarm Optimization (PSO) is a stochastic population based optimization algorithm which has attracted attentions of many researchers. This method has great potentials to be applied to many optimization problems. Despite its robustness the standard version of PSO has some drawbacks that may reduce its performance in optimization of complex structures such as laminated composites. In this paper by suggesting a new variation scheme for acceleration parameters and inertial weight factors of PSO a novel optimization algorithm is developed to enhance the basic version's performance in optimization of laminated composite structures. To verify the performance of the new proposed method, it is applied in two multi-objective design optimization problems of laminated cylindrical. The numerical results from the proposed method are compared with those from two other conventional versions of PSO-based algorithms. The convergancy of the new algorithms is also compared with the other two versions. The results reveal that the new modifications inthe basic forms of particle swarm optimization method can increase its convergence speed and evade it from local optima traps. It is shown that the parameter variation scheme as presented in this paper is successful and can evenfind more preferable optimum results in design of laminated composite structures.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.10
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• pp.17-22
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• 2007

This paper presents a baseband complex bandpass filter for PHS applications with a new automatic tuning method. The full-CMOS PHS transceiver is implemented by adopting the Low-IF architecture to overcome the DCoffset problems. To meet the Adjacent Channel Selectivity (ACS) performance, the 3rd-order Chebyshev complex bandpass filter is designed as the baseband channel-select filter. The new corner frequency tuning method is proposed to compensate the process variation. This method can reduce the noise level due to MOS switches. The filter was fabricated using a 0.35{\mu}m$ CMOS process, and the power consumption is 12mW.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2348-2356
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• 2021

As a relatively new radiation imaging method, the cosmic-ray muon scattering imaging technology can be used to prevent nuclear smuggling and is of considerable significance to nuclear safety. Proposed in this paper is a new reconstruction algorithm based on density clustering, aiming to improve inspection quality with better performance. Firstly, this new algorithm is introduced in detail. Then in order to eliminate the inequity of the density threshold caused by the heterogeneity of the muon flux in different positions, a new flux correction method is proposed. Finally, three groups of simulation experiments are carried out with the help of Geant4 toolkit to optimize the algorithm parameters, verify the correction method and test the inspection quality under shielded condition, and compare this algorithm with another common inspection algorithm under different conditions. The results show that this algorithm can effectively identify and locate nuclear material with low misjudging and missing rates even when there is shielding and momentum precision is low, and the threshold correcting method is universally effective for density clustering algorithms.

• New & Renewable Energy
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• v.19 no.2
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• pp.13-22
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• 2023

With the increased interest in renewable energy, various hydrogen production technologies have been developed. Hydrogen production can be classified into green, blue, gray, and pink hydrogen depending on the production method; each method has different technical performance, costs, and CO₂ emission characteristics. Hence, selecting the technology priorities that meet the company strategy is essential to develop technologically and economically feasible projects and achieve the national carbon neutrality targets. In addition, in early development technologies, analyzing the technology investment priorities based on the company's strategy and establishing investment decisions such as budget and human resources allocation is important. This study proposes a method of selecting priorities for various hydrogen production technologies as a specific implementation plan to achieve the national carbon neutrality goal. In particular, we analyze key performance indicators for technology, economic feasibility, and environmental performance by various candidate technologies and suggest ways to score them. As a result of the analysis using the aforementioned method, the priority of steam methane reforming (SMR) technology combined with carbon capture & storage (CCS) was established to be high in terms of achieving the national carbon neutrality goal.

• Communications of the Korean Mathematical Society
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• v.26 no.4
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• pp.695-708
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• 2011

Based on the multiple-time-scale (MTS) method, a general formula has been presented for solving an n-th, n = 2, 3, ${\ldots}$, order ordinary differential equation with strong linear damping forces. Like the solution of the unified Krylov-Bogoliubov-Mitropolskii (KBM) method or the general Struble's method, the new solution covers the un-damped, under-damped and over-damped cases. The solutions are identical to those obtained by the unified KBM method and the general Struble's method. The technique is a new form of the classical MTS method. The formulation as well as the determination of the solution from the derived formula is very simple. The method is illustrated by several examples. The general MTS solution reduces to its classical form when the real parts of eigen-values of the unperturbed equation vanish.

• Journal of Mechanical Science and Technology
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• v.17 no.11
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• pp.1693-1703
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• 2003

This paper presents a new local obstacle avoidance method for indoor mobile robots. The method uses a new directional approach called the Lane Method. The Lane Method is combined with a velocity space method i.e., the Curvature-Velocity Method to form the Lane-Curvature Method (LCM). The Lane Method divides the work area into lanes, and then chooses the best lane to follow to optimize travel along a desired goal heading. A local heading is then calculated for entering and following the best lane, and CVM uses this local heading to determine the optimal translational and rotational velocities, considering some physical limitations and environmental constraint. By combining both the directional and velocity space methods, LCM yields safe collision-free motion as well as smooth motion taking the physical limitations of the robot motion into account.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.149-161
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• 1994

The Max-Min CRI method , a traditional inference method , has three problems: subjective formulation of membership functions, error-prone weighting strategy, and inefficient compositional rule of inference. Because of these problems, there is an insurmountable error region between desired output and inferred output. To overcome these problems, we propose an Intelligent Neuro-Fuzzy System (INFS) based on fuzzy thoery and self-organizing functions of neural networks. INFS makes use of neural networks(Error Back Propagation) to solve the first problem, and NCRI(New Max-Min CRI) method for the second. With a proposed similarity measure, NCRI method is an improved method compared to the traditional Max-Min CRI method. For the last problem, we propose a new defuzzification method which combines only the appropriate rules produced by the rule selection level. Applying INFS to a D.C. series motor, we can conclude that the error region is reduced and NCRI method performs better than Max-Min CRI method.