• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.205-213
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• 2021

Due to the advantage of reducing the voltage applied to the switch semiconductor, the input series and output parallel combination is widely used in systems with high input voltage and large output current. On the other hand, the LLC converter is widely used as a high-efficiency power converter, and when connected by ISOP combination, there is a possibility that input voltage imbalance may occur due to a mismatch of passive devices. To avoid damaging the switching device, this study analyzed the DC-link voltage imbalance of a high-capacity supply using an ISOP LLC converter. In addition, the case where DC-link unbalance control was applied and the case not applied was analyzed respectively. Based on this analysis, an initial start-up algorithm was proposed to prevent input power semiconductor device damage due to DC-link over-voltage. The effectiveness of the proposed algorithm has been verified through simulations and experiments.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.2
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• pp.165-173
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• 2022

The electrification trend of mobility increases every year due to the development of power semiconductor and battery technology. Accordingly, the development and distribution of fast chargers for electric vehicles (EVs) are in demand. In this study, we propose a design and implementation method of an LLC converter for fast chargers. Two 15 kW LLC converters are configured in parallel to have 30 kW rated output power, and the control algorithm and driving sequence are designed accordingly and verified. In addition, the improved power conversion efficiency is confirmed through zero-voltage switching (ZVS) of the LLC converter and reduction of turn-off loss through snubber capacitors. The implemented 30 kW LLC converters show a wide output voltage range of 200-950 V. Experiments applying various load conditions verify the converter performance.

• ETRI Journal
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• v.45 no.2
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• pp.318-328
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• 2023

Recently, embedded systems, such as mobile platforms, have multiple processing units that can operate in parallel, such as centralized processing units (CPUs) and neural processing units (NPUs). We can use deep-learning compilers to generate machine code optimized for these embedded systems from a deep neural network (DNN). However, the deep-learning compilers proposed so far generate codes that sequentially execute DNN operators on a single processing unit or parallel codes for graphic processing units (GPUs). In this study, we propose PartitionTuner, an operator scheduler for deep-learning compilers that supports multiple heterogeneous PUs including CPUs and NPUs. PartitionTuner can generate an operator-scheduling plan that uses all available PUs simultaneously to minimize overall DNN inference time. Operator scheduling is based on the analysis of DNN architecture and the performance profiles of individual and group operators measured on heterogeneous processing units. By the experiments for seven DNNs, PartitionTuner generates scheduling plans that perform 5.03% better than a static type-based operator-scheduling technique for SqueezeNet. In addition, PartitionTuner outperforms recent profiling-based operator-scheduling techniques for ResNet50, ResNet18, and SqueezeNet by 7.18%, 5.36%, and 2.73%, respectively.

• Research in Mathematical Education
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• v.26 no.3
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• pp.167-202
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• 2023

A central problem of mathematics teaching worldwide is probably the insufficient adaptive handling of tasks-especially in computational practice phases and modeling tasks. All students in a classroom must often work on the same tasks. In the process, the high-achieving students are often underchallenged, and the low-achieving ones are overchallenged. This publication uses different modeling of the tennis serve as an example to show a possible solution to the problem and develops and discusses one adaptive task each for middle school, high school, and college using three mathematical models of the tennis serve each time. From model to model within the task, the complexity of the modeling increases, the mathematical or physical demands on the students increase, and the new modeling leads to more realistic results. The proposed models offer the possibility to address heterogeneous learning groups by their arrangement in the surface structure of the so-called parallel adaptive task and to stimulate adaptive mathematics teaching on the instructional topic of mathematical modeling. Models A through C are suitable for middle school instruction, models C through E for high school, and models E through G for college. The models are classified in the specific modeling cycle and its extension by a digital tool model, and individual modeling steps are explained. The advantages of the presented models regarding teaching and learning mathematical modeling are elaborated. In addition, we report our first teaching experiences with the developed parallel adaptive tasks.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.385-391
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• 2013

Big Data is data of big size which is not processed, collected, stored, searched, analyzed by the existing database management system. The parallel genetic algorithm using the Hadoop for BigData technology is easily realized by implementing GA(Genetic Algorithm) using MapReduce in the Hadoop Distribution System. The previous study that the genetic algorithm using MapReduce is proposed suitable transforming for the GA by MapReduce. However, they did not show good performance because of frequently occurring data input and output. In this paper, we proposed the MRPGA(MapReduce Parallel Genetic Algorithm) using improvement Map and Reduce process and the parallel processing characteristic of MapReduce. The optimal solution can be found by using the topology, migration of parallel genetic algorithm and local search algorithm. The convergence speed of the proposal method is 1.5 times faster than that of the existing MapReduce SGA, and is the optimal solution can be found quickly by the number of sub-generation iteration. In addition, the MRPGA is able to improve the processing and analysis performance of Big Data technology.

• The Journal of the Acoustical Society of Korea
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• v.29 no.3
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• pp.191-199
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• 2010

Physical modeling is a synthesis method of high quality sound which is similar to real sound for musical instruments. However, since physical modeling requires a lot of parameters to synthesize sound of a musical instrument, it prevents real-time processing for the musical instrument which supports a large number of sounds simultaneously. To solve this problem, this paper proposes a single instruction multiple data (SIMD) parallel processor that supports real-time processing of sound synthesis of guitar, a representative plucked string musical instrument. To control six strings of guitar, we used a SIMD parallel processor which consists of six processing elements (PEs). Each PE supports modeling of the corresponding string. The proposed SIMD processor can generate synthesized sounds of six strings simultaneously when a parallel synthesis algorithm receives excitation signals and parameters of each string as an input. Experimental results using a sampling rate 44.1 kHz and 16 bits quantization indicate that synthesis sounds using the proposed parallel processor were very similar to original sound. In addition, the proposed parallel processor outperforms commercial TI's TMS320C6416 in terms of execution time (8.9x better) and energy efficiency (39.8x better).

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.121-121
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• 2009

A clean and highly efficient energy production has long been sought to solve energy and environmental problems. A fuel cell energy is expected to be a key to solve the problems. The emissions of fuel cell is low, the by-product is low, the by-product is pure water. This paper shows the I-R and V-R characteristics of fuel cell which are connected in parallel and series. In addition, the voltage of the fuel cells which are connected in parallel is less than the voltage of the fuel cells which are connected in series.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.84-88
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• 2001

In an effort to develop more reliable and cost-effective satellite power system, a multiple-battery subsystem operating in parallel become a viable solution. The idea can further be extended to the parallel-able standardized battery module concept that offers many attractive features in configuring a spacecraft power system. In this paper, Multiple Battery Modules employing the charge control scheme are proposed. In addition to the conventional voltage mode controller, the charge control scheme internally regulates and controls the battery current, resulting in the identical current distribution and balanced battery charge.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.5
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• pp.122-130
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• 2001

In this paper, an operational algorithm for a 2-shaft parallel hybrid electric vehicle is suggested for the minimization of operation cost. The operation cost is obtained as a summation of the engine fuel cost and the motor electricity cost. The electrical cost function is estimated in case of motoring, and generating when the recuperation is carried out during the braking. In addition, weight function is introduced in order to maintain the battery state of charge. Based on the operation algorithm, the optimal engine operation point that minimizes the operation cost is obtained with respect to the required vehicle power for every state of charge of battery. The optimal operation point provides the optimal power distribution of the engine and the motor for a required vehicle power Simulation was performed and the fuel economy of the hybrid vehicle was compared to that of the conventional vehicle. Simulation results showed that hybrid vehicle's fuel economy can be improved as much as 45∼48% compared to the conventional vehicle's.

• Korean Journal of Plant Taxonomy
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• v.37 no.4
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• pp.351-361
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• 2007

In angiosperms, leaves typically develop as three-dimensional structure with dorsoventral, longitudinal, and lateral axes. We have shown that the control of two axes of leaves, longitudinal and lateral axis, can be genetically separable, and four classes of genes are responsible for the polar cell expansion and polar cell proliferation in Arabidopsis. In monocots, unifacial leaf, in which leaf surface consists only of abaxial identity, has been evolved in a number of divergent species. The unifacial leaves provide very unique opportunities for the developmental studies of the leaf axes formation in monocots, because their leaf polarities are highly disorganized. In addition, the mechanism of the parallel evolution of such drastic changes in leaf polarities is of interest from an evolutionary viewpoint. In this article, we describe our recent approaches to reveal the mechanism of unifacial leaf development and evolution, including recent advances in the leaf polarity specification in angiosperms.