• Journal of Information Processing Systems
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• v.18 no.3
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• pp.293-301
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• 2022

Direction of arrival (DOA) estimation of space signals is a basic problem in array signal processing. DOA estimation based on the multiple signal classification (MUSIC) algorithm can theoretically overcome the Rayleigh limit and achieve super resolution. However, owing to its inadequate real-time performance and accuracy in practical engineering applications, its applications are limited. To address this problem, in this study, a DOA estimation algorithm with high parallelism and precision based on an analysis of the characteristics of complex matrix eigenvalue decomposition and the coordinate rotation digital computer (CORDIC) algorithm is proposed. For parallel and single precision, floating-point numbers are used to construct an orthogonal identity matrix. Thus, the efficiency and accuracy of the algorithm are guaranteed. Furthermore, the accuracy and computation of the fixed-point algorithm, double-precision floating-point algorithm, and proposed algorithm are compared. Without increasing complexity, the proposed algorithm can achieve remarkably higher accuracy and efficiency than the fixed-point algorithm and double-precision floating-point calculations, respectively.

• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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• pp.123-127
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• 2005

The numerical analyses of the complicated flows are widely attempted in these days. Because of the enormous demanding memory and calculation time, parallel processing is used for these problems. In order to obtain calculation efficiency, it is important to choose proper domain decomposition technique and numerical algorithm. In this research we enhanced the efficiency of the CFDS code developed by ADD, using parallel computation and newly developed numerical algorithms. For the huge amount of data transfer between blocks non-blocking method is used, and newly developed data transfer algorithm is used for non-aligned block interface. Recently developed RoeM scheme is adpoted as a spatial difference method, and AF-ADI and LU-SGS methods are used as a time integration method to enhance the convergence of the code. Analyses of the flows around the ONERA M6 wing and the high angle of attack missile configuration are performed to show the efficiency improvement.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.18-24
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• 2001

This paper presents a model and a heuristic algorithm for the Traveling Salesman Problem with Time Windows(TSPTW). The main difference of our model compared with the previous ones lies in that the time windows we are concerned are more flexible and realistic than the previous ones. In the typical TSPTW, the service at a node must begin within the time grid called the time window that is defined by the earliest and the latest time to start the service at each node. But, in real business practice, a lateness cost is usually penalized rather than the service is prohibited at all when a vehicle arrives after the latest time. Considering this situation, we develop a model with a new time window that allows an arrival after the latest time and penalizes the late arrival by charging a lateness cost. A two-phased heuristic algorithm is proposed for the model and is extensively tested to verify the accuracy and efficiency of the algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.805-814
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• 2008

Both EPCglobal Generation-2 (Gen2) for passive RFID systems and Intelleflex for semi-passive RFID systems use probabilistic slotted ALOHA with Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. A better tag anti-collision algorithm can reduce collisions so as to increase the efficiency of tag identification. In this paper, we introduce and analyze the estimation methods of the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose two new tag anti-collision algorithms, which are Chebyshev's inequality (CHI) algorithm and hybrid Q algorithm, and compare them with the conventional Q algorithm and adaptive adjustable framed Q (AAFQ) algorithm, which is mentioned in Part I. The simulation results show that AAFQ performs the best in Gen2 scenario. However, in Intelleflex scenario the proposed hybrid Q algorithm is the best. That is, hybrid Q provides the minimum identification time, shows the more consistent collision ratio, and maximizes throughput and system efficiency in Intelleflex scenario.

• Atmosphere
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• v.33 no.4
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• pp.331-341
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• 2023

A numerical forecasting models usually predict future states by performing time integration considering fixed static time-steps. A time-step that is too long can cause model instability and failure of forecast simulation, and a time-step that is too short can cause unnecessary time integration calculations. Thus, in numerical models, the time-step size can be determined by the CFL (Courant-Friedrichs-Lewy)-condition, and this condition acts as a necessary condition for finding a numerical solution. A static time-step is defined as using the same fixed time-step for time integration. On the other hand, applying a different time-step for each integration while guaranteeing the stability of the solution in time advancement is called an adaptive time-step. The adaptive time-step algorithm is a method of presenting the maximum usable time-step suitable for each integration based on the CFL-condition for the adaptive time-step. In this paper, the adaptive time-step algorithm is applied for the Korean Integrated Model (KIM) to determine suitable parameters used for the adaptive time-step algorithm through the monthly verifications of 10-day simulations (during January and July 2017) at about 12 km resolution. By comparing the numerical results obtained by applying the 25 second static time-step to KIM in Supercomputer 5 (Nurion), it shows similar results in terms of forecast quality, presents the maximum available time-step for each integration, and improves the calculation efficiency by reducing the number of total time integrations by 19%.

• Journal of Power Electronics
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• v.11 no.2
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• pp.194-201
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• 2011

The air flow supplied to a fuel cell system is one of the most significant factors in determining fuel efficiency. The conventional method of controlling the air flow is to fix the oxygen supply at an estimated constant rate for optimal efficiency. However, the actual optimal point can deviated from the pre-set value due to temperature, load conditions and so on. In this paper, the maximum efficiency point tracking (MEPT) algorithm is proposed for finding the optimal air supply rate in real time to maximize the net-power generation of fuel cell systems. The fixed step MEPT algorithm has slow dynamics, thus it affects the overall efficiency. As a result, the variable step MEPT algorithm is proposed to compensate for this problem instead of a fixed one. The complete small signal model of a PEM Fuel cell system is developed to perform a stability analysis and to present a design guideline. For a design example, a 1kW PEM fuel cell system with a DSP 56F807 (Motorola Inc) was built and tested using the proposed MEPT algorithm. This control algorithm is very effective for a soft current change load like a grid connected system or a hybrid electric vehicle system with a secondary energy source.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1627-1636
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• 2014

In real-time electricity price environment, the energy management system can provide the significant advantage to the residential, commercial and industrial customers since it can reduce the electricity charge by controlling the load operation effectively in response to time-varying price. However, the earlier studies for load management mainly focus on the residential and commercial customers except for the industrial customers because most of load operations in industrial sector are intimately related with production schedule. So, it is possible that the inappropriate control of loads in industrial sector causes huge economic loss. In this paper, therefore, we propose load control algorithm for factory energy management system(F-EMS) to achieve not only minimizing the electricity charges but also maintaining production efficiency by considering characteristics of load operation and production schedule. Considering characteristics of load operation and production schedule, the proposed load control algorithm can reflect the various characteristics of specific industrial customer and control their loads within the range that the production efficiency is maintained. Simulation results show that the proposed load control algorithm for F-EMS leads to significant reduction in the electricity charges and peak power in industrial sector.

• Journal of Distribution Science
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• v.14 no.5
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• pp.107-114
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• 2016

Purpose - Loading can decrease the productivity due to the possibility of carrying out with the opposite order of storage in container terminal. When the container is to be taken out, it is needed to move the container stacked upon the container to be carried out to other place temporarily. It is called as rehandling. Remarshalling, with the loading plan, is the arranging the containers before the ship arrives in order to avoid the rehandling during the carrying out. The present study tried to find out the factors affecting the efficiency when building the remarshalling plan with the utilization of neighboring storage space as a outer slot, and analyzed the efficiency of several remarshalling algorithms with the combination of those factors. Research design, data and methodology - The present study used, when the remarshalling plan is prepared for utilizing the outer slot, the simulation methods in order to compare the efficiency of the remarshalling algorithms which made with the factors affecting the efficiency. The factors affecting the efficiency are the method of making the child node, method of arrangement, and possibility of application of FIX. In order to analyze the affecting factors on the efficiency, several algorithms are prepared with the combination of production of the child node and the arrangement method with the availability of FIX application. With this algorithm, the effect of the factors on the efficiency after building up of remarshalling plan with the target on the bay with 10 rows, 8 columns, and 10 indices. Results - The method of rearrangement and making of a child node as the factor affecting the efficiency of remarshalling utilization of the outer bay were studied. It is efficient to combine the method of making a child node with MCS in order to reduce the number of moving the containers. For reducing the time in carrying out, it was found that all arrangement methods should be combined with RCS for the efficiency. The result of experiment shows the application of FIX with good result in case of succession ratio. In addition, when FIX was not applied, all of the most combinations resulted in short time in remarshalling. As a result, it can be concluded that the algorithm with proper combination of making the child node and the arrangement can increase the job efficiency based on the importance. Conclusion - The present study suggested and analyzed the algorithms with the combination of the arrangement method, the making of child node, and FIX. It is needed to develop the algorithm to judge the possibility whether the best remarshalling plan can be built or not within the bay in order to find a better method between the two cases such as within the bay and outer the bay. As a method for extending the study on the factors affecting the efficiency, it is possible to find out the way to build the remarshalling plan within the permitted time under any storage situation.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.156-161
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• 1997

In this thesis, based on Genetic Algorithm, a new route search algorithm is presented to search an optimal route between the origin and the destination in intelligent route guidance systems in order to minimize the route traveling time. The proposed algorithm is effectively employed to complex road networks which have diverse turn constrains, time-delay constraints due to cross signals, and stochastic traffic volume. The algorithm is also shown to significantly promote search efficiency by changing the population size of path individuals that exist in each generation through the concept of age and lifetime to each path individual. A virtual road-traffic network with various turn constraints and traffic volume is simulated, where the suggested algorithm promptly produces not only an optimal route to minimize the route cost but also the estimated travel time for any pair of the origin and the destination, while effectively avoiding turn constraints and traffic jam.

• Advances in Energy Research
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• v.5 no.1
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• pp.31-55
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• 2017

In the present study, PV/T collector was modeled via analysis of governing equations and physics of the problem. Specifications of solar radiation were computed based on geographical characteristics of the location and the corresponding time. Temperature of the collector plate was calculated as a function of time using the energy equations and temperature behavior of the photovoltaic cell was incorporated in the model with the aid of curve fitting. Subsequently, operational range for reaching to maximal efficiency was studied using Genetic Algorithm (GA) technique. Optimization was performed by defining an objective function based on equivalent value of electrical and thermal energies. Optimal values for equipment components were determined. The optimal value of water flow rate was approximately 1 gallon per minute (gpm). The collector angle was around 50 degrees, respectively. By selecting the optimal values of parameters, efficiency of photovoltaic collector was improved about 17% at initial moments of collector operation. Efficiency increase was around 5% at steady condition. It was demonstrated that utilization of photovoltaic collector can improve efficiency of solar energy-based systems.