• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.820-823
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• 2003

In this paper, we describe a design procedure for cascade controller for induction motor drives based on Genetic Algorithms(GAs). Most electric drives have two separate controllers for current and speed control, which are in general designed in two consecutive steps(firstly the current controller and then the speed controller). We search simultaneously for the couple of discrete anti-windup controllers achieving the optimal compromise of weighted cost and performance indices related to both current and speed responses.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.7
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• pp.909-915
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• 1999

In this paper, we propose an efficient VLSI architecture of Reed-Solomon(RS) decoder. To improve the speed. we develope an architecture featuring parallel and pipelined processing. To implement the parallel and pipelined processing architecture, we analyze the RS decoding algorithm and the honor's algorithm for parallel processing and we also modified the Euclid's algorithm to apply the efficient parallel structure in RS decoder. To show the proposed architecture, the performance of the proposed RS decoder is compared to Shao's and we obtain the 10 % efficiency in area and three times faster in speed when it's compared to Shao's time domain decoder. In addition, we implemented the proposed RS decoder with Altera FPGA Flex10K-50.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.140-143
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• 2019

The Internet has been expanded constantly and greatly such that we are having vast number of web pages with dynamic changes. Especially, the fast development of wireless communication technology and the wide spread of various smart devices enable information being created at speed and changed anywhere, anytime. In this situation, web crawling, also known as web scraping, which is an organized, automated computer system for systematically navigating web pages residing on the web and for automatically searching and indexing information, has been inevitably used broadly in many fields today. This paper aims to implement a prototype web crawler with Python and to improve the execution speed using threads on multicore CPU. The results of the implementation confirmed the operation with crawling reference web sites and the performance improvement by evaluating the execution speed on the different thread configurations on multicore CPU.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.360-367
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• 1999

An inverter-driven induction motor is used as the traction motor for a high speed drive system that required safety, reliabillity, performance, compact size owing to the space and weight alloted for attaching to train, etc. particularly it is possible to happen the saturation effects of flux density at constant voltage-frequency region and then increase very higher than the at lowed capacity of no-load current and temperature in any case. therefore the optimum design of core, optimum voltage-frequency ratio, adoption of high grade magnetic core have been developed and researched for preventing these problems. this paper show the saturation effects of traction rotor by measuring the induced voltage of search coil at stator teeth and presents optimum voltage-frequency ratio as well as optimum core design through the comparison with efficiency, power factor, load current and no-load current for korea high speed train.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.446-448
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• 2021

In training a deep learning model, it is crucial to tune various hyperparameters and gain speed and accuracy. While hyperparameters that mathematically induce convergence impact training speed, system parameters that affect host-to-device transfer are also crucial. Therefore, it is important to properly tune and select parameters that influence the data loader as a system parameter in overall time acceleration. We propose an automated framework called Num Worker Tuner (NWT) to address this problem. This method finds the appropriate number of multi-processing subprocesses through the search space and accelerates the learning through the number of subprocesses. Furthermore, this method allows memory efficiency and speed-up by tuning the system-dependent parameter, the number of multi-process spawns.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.715-723
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• 2016

This paper proposes a design of optimal PI(D) controller for brushless DC (BLDC) motor speed control by the particle swarm optimization (PSO), one of the powerful metaheuristic optimization search techniques. The proposed control system is implemented on the TMS320F28335 DSP board interfacing to MATLAB/SIMULINK. With Back EMF detection, the proposed system is considered as a class of sensorless control. This scheme leads to the speed adjustment of the BLDC motor by PWM. In this work, the BLDC motor of 100 watt is conducted to investigate the control performance. As results, it was found that the speed response of BLDC motor can be regulated at the operating speed of 800 and 1200 rpm in both no load and full load conditions. Very satisfactory responses of the BLDC system can be successfully achieved by the proposed control structure and PSO-based design approach.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.123-130
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• 2009

Motion estimation (ME) plays an important role in digital video compression. But it limits the performance of image quality and encoding speed and is computational demanding part of the encoder. To reduce computational time and maintain the image quality, integer pel and fractional pel ME methods are proposed in this paper. The proposed method for integer pel ME uses a hierarchical search strategy. This strategy method consists of symmetrical cross-X pattern, multi square grid pattern, diamond patterns. These search patterns places search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum and to reduce the computational time. The proposed method for fractional pel uses full search pattern, center biased fractional pel search pattern and the proposed search pattern. According to block sizes, the proposed method for fractional pel decides the search pattern adaptively. Experiment results show that the speedup improvement of the proposed method over Unsymmetrical cross Multi Hexagon grid Search (UMHexagonS) and Full Search (FS) can be up to around $1.2{\sim}5.2$ times faster. Compared to image quality of FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain of 0.02 dB in comparison to that of UMHexagonS.

• Journal of IKEEE
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• v.1 no.1 s.1
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• pp.31-46
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• 1997

In this paper, a parallel Optimal Best-First search Branch-and-Bound(B&B) algorithm(pobs) is designed and evaluated for MIN-based multiprocessor systems. The proposed algorithm decomposes a problem into G subproblems, where each subproblem is processed on a group of P processors. Each processor group uses tile sub-Global Best-First search technique to find a local solution. The local solutions are broadcasted through the network to compute the global solution. This broadcast provides not only the comparison of G local solutions but also the load balancing among the processor groups. A performance analysis is then conducted to estimate the speed-up of the proposed parallel B&B algorithm. The analytical model is developed based on the probabilistic properties of the B&B algorithm. It considers both the computation time and communication overheads to evaluate the realistic performance of the algorithm under the parallel processing environment. In order to validate the proposed evaluation model, the simulation of the parallel B&B algorithm on a MIN-based system is carried out at the same time. The results from both analysis and simulation match closely. It is also shown that the proposed Optimal Best-First search B&B algorithm performs better than other reported schemes with its various advantageous features such as: less subproblem evaluations, prefer load balancing, and limited scope of remote communication.

• International Journal of Fluid Machinery and Systems
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• v.2 no.4
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• pp.392-399
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• 2009

The paper concerns the description of the step by step development process of the new fixed blade runner called "Mixer" suitable for the uprating of the Francis turbines units installed at the older low head hydropower plants. In the paper the details of hydraulic and mechanical design are presented. Since the rotational speed of the new runner is significantly higher then the rotational speed of the original Francis one, the direct coupling of the turbine to the generator can be applied. The maximum efficiency at prescribed operational point was reached by the geometry optimization of two most important components. In the first step the optimization of the draft tube geometry was carried out. The condition for the draft tube geometry optimization was to design the new geometry of the draft tube within the original bad draft tube shape without any extensive civil works. The runner blade geometry optimization was carried out on the runner coupled with the draft tube domain. The blade geometry of the runner was optimized using automatic direct search optimization procedure. The method used for the objective function minimum search is a kind of the Nelder-Mead simplex method. The objective function concerns efficiency, required net head and cavitation features. After successful hydraulic design the modal and stress analysis was carried out on the prototype scale runner. The static pressure distribution from flow simulation was used as a load condition. The modal analysis in air and in water was carried out and the results were compared. The final runner was manufactured in model scale and it is going to be tested in hydraulic laboratory. Since the turbine with the fixed blade runner does not allow double regulation like in case of full Kaplan turbine, it can be profitably used mainly at power plants with smaller changes of operational conditions or in case with more units installed. The advantages are simple manufacturing, installation and therefore lower expenses and short delivery time for turbine uprating.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.892-898
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• 2012

Rough classification methods are used to improving the recognition speed in many character recognition problems. In this case, some irreversible result can occur by an error in rough classification. Methods for duplicating each model in several classes are used in order to reduce this risk. But the errors by rough classfication can not be completely ruled out by these methods. In this paper, an recognition method is proposed to increase speed that matches models selectively without any increase in error. This method constructs a model graph using similarity between models. Then a search process begins from a particular point in the model graph. In this process, matching of unnecessary models are reduced that are not similar to the input pattern. In this paper, the proposed method is applied to the recognition problem of handwriting numbers and upper/lower cases of English alphabets. In the experiments, the proposed method was compared with the basic method that matches all models with input pattern. As a result, the same recognition rate, which has shown as the basic method, was obtained by controlling the out-degree of the model graph and the number of maintaining candidates during the search process thereby being increased the recognition speed to 2.45 times.