• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1726-1748
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• 2024

Trajectory planning is vital for autonomous systems like robotics and UAVs, as it determines optimal, safe paths considering physical limitations, environmental factors, and agent interactions. Recent advancements in trajectory planning and future location prediction stem from rapid progress in machine learning and optimization algorithms. In this paper, we proposed a novel framework for Spatial-temporal transformer-based feed-forward neural networks (STTFFNs). From the traffic flow local area point of view, skip-gram model is trained on trajectory data to generate embeddings that capture the high-level features of different trajectories. These embeddings can then be used as input to a transformer-based trajectory planning model, which can generate trajectories for new objects based on the embeddings of similar trajectories in the training data. In the next step, distant regions, we embedded feedforward network is responsible for generating the distant trajectories by taking as input a set of features that represent the object's current state and historical data. One advantage of using feedforward networks for distant trajectory planning is their ability to capture long-term dependencies in the data. In the final step of forecasting for future locations, the encoder and decoder are crucial parts of the proposed technique. Spatial destinations are encoded utilizing location-based social networks(LBSN) based on visiting semantic locations. The model has been specially trained to forecast future locations using precise longitude and latitude values. Following rigorous testing on two real-world datasets, Porto and Manhattan, it was discovered that the model outperformed a prediction accuracy of 8.7% previous state-of-the-art methods.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.2
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• pp.165-174
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• 2010

The numerical modeling of a coal gasification reaction occurring in an entrained flow coal gasifier is presented in this study. The purposes of this study are to develop a reliable evaluation method of coal gasifier not only for the basic design but also further system operation optimization using a CFD(Computational Fluid Dynamics) method. The coal gasification reaction consists of a series of reaction processes such as water evaporation, coal devolatilization, heterogeneous char reactions, and coal-off gaseous reaction in two-phase, turbulent and radiation participating media. Both numerical and experimental studies are made for the 1.0 ton/day entrained flow coal gasifier installed in the Korea Institute of Energy Research (KIER). The comprehensive computer program in this study is made basically using commercial CFD program by implementing several subroutines necessary for gasification process, which include Eddy-Breakup model together with the harmonic mean approach for turbulent reaction. Further Lagrangian approach in particle trajectory is adopted with the consideration of turbulent effect caused by the non-linearity of drag force, etc. The program developed is successfully evaluated against experimental data such as profiles of temperature and gaseous species concentration together with the cold gas efficiency. Further intensive investigation has been made in terms of the size distribution of pulverized coal particle, the slurry concentration, and the design parameters of gasifier. These parameters considered in this study are compared and evaluated each other through the calculated syngas production rate and cold gas efficiency, appearing to directly affect gasification performance. Considering the complexity of entrained coal gasification, even if the results of this study looks physically reasonable and consistent in parametric study, more efforts of elaborating modeling together with the systematic evaluation against experimental data are necessary for the development of an reliable design tool using CFD method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.2
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• pp.145-152
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• 2015

In the study, the effects of damping devices on damping ratio increase and wind-load reduction were investigated based on the computational platform, which is one of the parametric modeling methods. The computational platform helps the designers or engineers to evaluate the efficacy of the numerous alternative structural systems for irregular Super-Tall building, which is crucial in determining the capacity and the number of the supplemental damping devices for adding the required damping ratios to the building. The inherent damping ratio was estimated based on the related domestic and foreign researches conducted by using real wind-load records. Two types of damping devices were considered: One is inter-story installation type passive control devices and the other is mass type active control devices. The supplemental damping ratio due to the damping devices was calculated by means of equivalent static analysis using an equation suggested by FEMA. The optimal design of the damping devices was conducted by using the computational platform. The structural element quantity reduction effect resulting from the installation of the damping devices could be simply assessed by proposing a wind-load reduction factor, and the effectiveness of the proposed method was verified by a numerical example of a 455m high-rise building. The comparison between roof displacement and the story shear forces by the nonlinear time history analysis and the proposed method indicated that the proposed method could simply but approximately estimate the effects of the supplemental damping devices on the roof displacement and the member force reduction.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.334-339
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• 2008

Construction that over 70% of the structure consists of concrete gets bigger and higher gradually and the demand of that is increasing as well. However, it's not easy to supply young and skilled persons on construction site because of social avoidance phenomena about 3D occupation, so it causes serious problems like aging and shortage of technicians. To solve the problems, executives related to the construction field make a management effort in various ways such as construction period shortening, labor productivity improvement and good quality but recently, they have an increasing interest in the necessity of the modularization of the high-rise building and the automation of the engineering development for the strengthening of international competitive power as more active and long-term alternatives. Therefore, this study is to propose the roadmap in order to make lots of efforts in developing construction technologies of high-rise buildings by performing a foundation study, the strategy for 4-step research development, on modularized construction system of concrete structure of high-rise buildings through domestic and foreign preceding research analyses associated with optimal design modularization technique, module factory automation and assembly automation of modularized objects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.688-695
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• 2017

This paper deals with characteristics analysis of a permanent magnet (PM) linear generator using analytical methods for wave energy harvesting. The wave energy is carried out from the movement of a yo-yo system. A linear generator using permanent magnets to generate a magnetic force itself does not require a separate power supply and has the advantage of simple maintenance. In addition to the use of a rare earth, a permanent magnet having a high-energy density can be miniaturized and lightweight, and can obtain high energy-conversion efficiency. We derived magnetic field solutions produced by the permanent magnet and armature reaction based on 2D polar coordinates and magnetic vector potential. Induced voltage is obtained via arbitrary sinusoidal input. In addition, electrical parameters are obtained, such as back-EMF constant, resistance, and self- and mutual-winding inductances. The space harmonic method used in this paper is confirmed by comparing it with finite element method (FEM) results. These facilitate the characterization of the PM-type linear generator and provide a basis for comparative studies, design optimization, and machine dynamic modeling.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1015-1024
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• 2011

Mobile P2P protocols in ad-hoc networks have gained large attention recently. Although there has been much research on P2P algorithms for wired networks, existing P2P protocols are not suitable for mobile ad-hoc networks because they do not consider mobility of peers. This study proposes a new cluster-based P2P protocol for ad hoc networks which utilizes peer mobility. In typical cluster-based P2P algorithms, each cluster has a super peer and other peers of the cluster register their file list to the super peer. High mobility peers would cause a lot of file list registration traffic because they hand-off between clusters frequently. In the proposed scheme, while peers with low mobility behave in the same way as the peers of the typical cluster-based P2P schemes, peers with high mobility behave differently. They inform their entrance to the cluster region to the super peer but they do not register their file list to the super peer. When a peer wishes to find a file, it first searches the registered file list of the super peer and if fails, query message is broadcasted. We perform mathematical modeling, analysis and optimization of the proposed scheme regarding P2P traffic and associated routing traffic. Numerical results show that the proposed scheme performs much better than or similar to the typical cluster-based P2P scheme and flooding based Gnutella.

• Journal of Korea Water Resources Association
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• v.44 no.9
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• pp.711-720
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• 2011

SWAT (Soil and Water Assessment Tool) model was calibrated for the flow rate of the Deachung lake with a large area of 3108.29 $km^2$. Application of SWAT model requires significant number of input data and is prone to result in uncertainties due to errors in input data, model structure and model parameters. The SUFI-2 (Sequential Uncertainty Fitting Ver. 2) program and GLUE (Generalized Likelihood Uncertainty Estimation) program in SWAT-CUP (SWAT-Calibration and Uncertainty Program) are used to select the best parameters for SWAT model. Optimal combination of parameter values was determined through 2,000 iterative SWAT model runs. The Nash-Sutcliffe values and $R^2$ values were 0.87 and 0.89 respectively indicating both methods show good agreements with observed data successfully. RMSE and MSE values also showed similar results for both programs. It seems the SWAT-CUP has a great practical appeal for parameter optimization especially for large basin area and it also can be used for less experienced SWAT model users.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.487-496
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• 2000

In this paper, the Multi-FNN(Fuzzy-Neural Networks) model is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNN is based on Yamakawa's FNN and uses simplified inference as fuzzy inference method and error back propagation algorithm as learning rules. We use a HCM clustering and Genetic Algorithms(GAs) to identify both the structure and the parameters of a Multi-FNN model. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNN according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. The aggregate performance index stands for an aggregate objective function with a weighting factor to consider a mutual balance and dependency between approximation and predictive abilities. According to the selection and adjustment of a weighting factor of this aggregate abjective function which depends on the number of data and a certain degree of nonlinearity, we show that it is available and effective to design an optimal Multi-FNN model. To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• Korean Chemical Engineering Research
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• v.49 no.2
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• pp.129-136
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• 2011

Simulated Moving Bed(SMB) process consists of multiple chromatographic columns, which are usually partitioned into four zones. Such a process characteristic allows a continuous binary separations those are impracticable in conventional batch chromatographic processes. Compared with batch chromatography, SMB has advantages of continuity, high purity and productivity. Various researches have been reported for the integration of reaction and recovery during process operation on the purpose of economics and effectiveness. Simulated Moving Bed Reactor(SMBR) is introduced to combine SMB as a continuous separation process and reactor. Several cases of SMBR have been reported for diverse reactions with catalytic, enzymatic and chemical reaction on ion exchange resin as main streams. With an early type of fixed bed using catalyst, SMBR has been developed as SMB using fluidized enzyme, SMB with immobilized enzyme and SMB with discrete reaction region. For simple modeling and optimization of SMBR, a method considering convection only is possible. A complex method considering axial dispersion and mass transfer resistance is needed to explain the real behavior of solutes in SMBR. By combining reaction and separation, SMBR has benefits of lower installation cost by minimizing equipment use, higher purity and yield by avoiding the equilibrium restriction in case of reversible reaction.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.26-35
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• 2009

OFDM (Orthogonal Frequency Division Multiplexing) system is robust to frequency selective fading and narrowband interference in high-speed data communications. However, an OFDM signal consists of a number of independently modulated subcarriers and the superposition of these subcarriers causes a problem that can give a large PAPR(Peak-to-Average Power Ratio). Phase rotation method can reduce the PAPR without nonlinear distortion by multiplying phase weighting factors. But computational complexity of searching phase weighting factors is increased exponentially with the number of subblocks and considered phase factor. Therefore, a new method, which can reduce computational complexity and detect phase weighting factors efficiently, should be developed. In this paper, a modeling process is introduced, which apply metaheuristic algerian in phase rotation method and optimize in PTS (Particle Swarm Optimization) scheme. Proposed algorithm can solve the computational complexity and guarantee to reduce PAPR We analyzed the efficiency of the PAPR reduction through a simulation when we applied the proposed method to telecommunication systems.