• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.10
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• pp.979-987
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• 2008

In aerospace structural design, the position of lightening hole is often required to be optimized from the initial design in order to avoid an excessive stress concentration. To remodel the updated configuration in optimization procedure, re-meshing procedure is conventionally adopted. However, this approach is time-consuming, and has limitations especially in handling hexahedral or quadrilateral meshes, which are preferred because of their good numerical performances. To attenuate these disadvantages, new optimization scheme is proposed by combining the MLS(Moving Least Squares) based overset method and the genetic algorithm in this work. To test the validity of the proposed optimization scheme, optimizations of positions of lightening holes in 2D structures have been carried out.

• Journal of Computing Science and Engineering
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• v.5 no.2
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• pp.111-120
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• 2011

Data mining algorithms should exploit new hardware technologies to accelerate computations. Such goal is difficult to achieve in database management system (DBMS) due to its complex internal subsystems and because data mining numeric computations of large data sets are difficult to optimize. This paper explores taking advantage of existing multithreaded capabilities of multicore CPUs as well as caching in RAM memory to efficiently compute summaries of a large data set, a fundamental data mining problem. We introduce parallel algorithms working on multiple threads, which overcome the row aggregation processing bottleneck of accessing secondary storage, while maintaining linear time complexity with respect to data set size. Our proposal is based on a combination of table scans and parallel multithreaded processing among multiple cores in the CPU. We introduce several database-style and hardware-level optimizations: caching row blocks of the input table, managing available RAM memory, interleaving I/O and CPU processing, as well as tuning the number of working threads. We experimentally benchmark our algorithms with large data sets on a DBMS running on a computer with a multicore CPU. We show that our algorithms outperform existing DBMS mechanisms in computing aggregations of multidimensional data summaries, especially as dimensionality grows. Furthermore, we show that local memory allocation (RAM block size) does not have a significant impact when the thread management algorithm distributes the workload among a fixed number of threads. Our proposal is unique in the sense that we do not modify or require access to the DBMS source code, but instead, we extend the DBMS with analytic functionality by developing User-Defined Functions.

• Journal of Microbiology and Biotechnology
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• v.30 no.1
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• pp.136-145
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• 2020

Chlorella sp. HS2, which previously showed excellent performance in phototrophic cultivation and has tolerance for wide ranges of salinity, pH, and temperature, was cultivated heterotrophically. However, this conventional medium has been newly optimized based on a composition analysis using elemental analysis and ICP-OES. In addition, in order to maintain a favorable dissolved oxygen level, stepwise elevation of revolutions per minute was adopted. These optimizations led to 40 and 13% increases in the biomass and lipid productivity, respectively (7.0 and 2.25 g l^-1d^-1 each). To increase the lipid content even further, 12 h heat shock at 50℃ was applied and this enhanced the biomass and lipid productivity up to 4 and 17% respectively (7.3 and 2.64 g l^-1d^-1, each) relative to the optimized conditions above, and the values were 17 and 14% higher than ordinary lipid-accumulating N-limitation (6.2 and 2.31 g l^-1d^-1). On this basis, heat shock was successfully adopted in novel Chlorella sp. HS2 cultivation as a lipid inducer for the first time. Considering its fast and cost-effective characteristics, heat shock will enhance the overall microalgal biofuel production process.

• Current Photovoltaic Research
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• v.5 no.1
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• pp.20-24
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• 2017

Recently, three-dimensional (3D) light harvesting structures are highly attracted because of their high light harvesting capacity and charge collection efficiencies. In this study, we have fabricated $Cu_2ZnSn(S_xSe_{1-x})_4$ based 3D thin film solar cells on PR patterned Molybdenum (Mo) substrates using photolithography technique. Specifically, Mo patterns were deposited on PR patterned Mo substrates by sputtering and the thin Cu-Zn-Sn stacked layer was deposited over this Mo patterns by sputtering technique. The stacked Zn-Sn-Cu precursor thin films were sulfo-selenized to form CZTSSe pattern. Finally, CZTSSe absorbers were coated with thin CdS layer using chemical bath deposition and ZnO window layer was deposited over CZTSSe/CdS using DC sputtering technique. Fabricated 3-D solar cells were characterized by X-ray diffraction (XRD), X-ray fluorescence (XRF) analysis, Field-emission scanning electron microscopy (FE-SEM) to study their structural, compositional and morphological properties, respectively. The 3% efficiency is achieved for this kind of solar cell. Further efforts will be carried out to improve the performance of solar cell through various optimizations.

• Journal of Magnetics
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• v.13 no.2
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• pp.37-42
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• 2008

In this paper, design parameters of high Q (> 50), high current inductor for on-chip power module were optimized by 4 Xs 3 Ys DOE (Design of Experiment). Coil spacing, coil thickness, ferrite thickness, and permeability were assigned to Xs, and inductance (L) and Q factor at 10 MHz, and resonance frequency ($f_r$) were determined Ys. Effects of each X on the Ys were demonstrated and explained using known inductor theory. Multiple response optimizations were accomplished by three derived regression equations on the Ys. As a result, L of 125 nH, Q factor of 197.5, and $f_r$ of 316.3 MHz were obtained with coil space of $127\;{\mu}m$, Cu thickness of $67.8\;{\mu}m$, ferrite thickness of $130.3\;{\mu}m$, and permeability 156.5. Loss tan ${\delta}=0$ was assumed for the estimation. Accordingly, Q factor of about 60 is expected at tan ${\delta}=0.02$.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.102-108
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• 2011

Support vector machines are well known for their outstanding performance in pattern recognition fields. One example of their applications is music/speech classification for a standardized codec such as 3GPP2 selectable mode vocoder. In this paper, we propose a novel scheme that improves the speech/music classification of support vector machines based on the second-order conditional maximum a priori. While conventional support vector machine optimization techniques apply during training phase, the proposed technique can be adopted in classification phase. In this regard, the proposed approach can be developed and employed in parallel with conventional optimizations, resulting in synergistic boost in classification performance. According to experimental results, the proposed algorithm shows its compatibility and potential for improving the performance of support vector machines.

• Bulletin of the Korean Chemical Society
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• v.32 no.9
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• pp.3372-3376
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• 2011

We have studied the relative stability and atomic structures of five $C_{20}X_2$ regioisomers obtained as diadducts of a $C_{20}$ cage (X = H, F, Cl, Br, and OH). All the regioisomers are geometric isomers, i.e., they differ in their spatial arrangement. Full-geometry optimizations of the regioisomers have been performed using the hybrid density-functional (B3LYP/6-31G(d, p)) method. Our results suggest that the cis-1 regioisomer (the 1,2-diadduct) is the most stable and that the second most stable is the trans-2 (1,13-diadduct) regioisomer, implying that the long-range interaction between the two adducts and the resonance effect are more pronounced than the diadduct-induced strain in the $C_{20}$ cage. The HOMO and LUMO characteristics of each regioisomer with the same symmetry of structural regioisomers except $C_{20}(OH)_2$ are topologically same. This suggests that by using an entirely different set of characteristic chemical reactions for each regioisomer, we can distinguish between the five regioisomers for each $C_{20}$ diadduct derivative.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.65-67
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• 2002

A PC based software, the RTP Research Tool Box (RTB), was developed for IMRT optimization research. The software was consisted of an image module, a beam registration module, a dose calculation module, a dose optimization module and a dose display module. The modules and the Graphical User Interface (GUI) were designed to easily amendable by negotiating the speed of performing tasks. Each module can be easily replaced to new functions for research purpose. IDL 5.5 (RSI, USA) language was used for this software. Five major modules enable one to perform the research on the dose calculation, on the dose optimization and on the objective function. The comparison of three cost functions, such as the uncomplicated tumor control probability (UTCP), the physical objective function and the pseudo-biological objective function, which was designed in this study, were performed with the RTB. The optimizations were compared to the simulated annealing and the gradient search optimization technique for all of the optimization objective functions. No significant differences were found among the objective functions with the dose gradient search technique. But the DVH analysis showed that the pseudo-biological objective function is superior to the physical objective function when with the simulated annealing for the optimization.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.141-148
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• 2011

Support vector machines have been extensively studied and utilized in pattern recognition area for years. One of interesting applications of this technique is music/speech classification for a standardized codec such as 3GPP2 selectable mode vocoder. In this paper, we propose a novel approach that improves the speech/music classification of support vector machines. While conventional support vector machine optimization techniques apply during training phase, the proposed technique can be adopted in classification phase. In this regard, the proposed approach can be developed and employed in parallel with conventional optimizations, resulting in synergistic boost in classification performance. We first analyze the impact of kernel width parameter on the classifications made by support vector machines. From this analysis, we observe that we can fine-tune outputs of support vector machines with the kernel width parameter. To make the most of this capability, we identify strong correlation among neighboring input frames, and use this correlation information as a guide to adjusting kernel width parameter. According to the experimental results, the proposed algorithm is found to have potential for improving the performance of support vector machines.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2325-2349
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• 2014

Network virtualization technology plays a key role in cloud computing, which serves as an effective approach for provisioning a flexible and highly adaptable shared substrate network to satisfy the demands of various applications or services. Recently, the problem of mapping a virtual network (VN) onto a substrate network has been addressed by various algorithms. However, these algorithms are typically efficient for unicast service-oriented virtual networks, and generally not applicable to multicast service-oriented virtual networks (MVNs). Furthermore, the survivable MVN mapping (SMVNM) problem that considers the survivability of MVN has not been studied and is also the focus of this work. In this research, we discuss SMVNM problem under regional failures in the substrate network and propose an efficient algorithm for solving this problem. We first propose a framework and formulate the SMVNM problem with the objective of minimizing mapping cost by using mixed integer linear programming. Then we design an efficient heuristic to solve this problem and introduce several optimizations to achieve the better mapping solutions. We validate and evaluate our framework and algorithms by conducting extensive simulations on different realistic networks under various scenarios, and by comparing with existing approaches. Our simulation experiments and results show that our approach outperforms existing solutions.