• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.419-424
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• 2017

TDoA (Time Difference-of Arrival) or DoA (Direction-of-Arrival) can be used for source localization. However, the localizing performance is dependent on relative position between source and receivers, receivers' geometric structure, sound speed, and so on. In this paper we propose a source localization method with enhanced performance that combines multiple information. The proposed method uses the time TDoA, DoA and sound speed as variables. LM (Levenberg-Marquardt) method which is one of nonlinear optimizations is applied. The performances of the proposed method was evaluated by simulation. As result of simulation, the proposed method has the lower average localizing error performance than the previous method.

• Composites Research
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• v.28 no.1
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• pp.15-21
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• 2015

The purpose of this paper is to investigate the current trends of composite applications in the marine and leisure fields and to study the development of 33ft class America's cup training CFRP sailing yacht. In the field of marine and leisure, composite materials have been just used to marine and leisure structures, recently. Especially, since the America's cup of sailing yacht racing has required the light weight and high mechanical performance to make a high speed, CFRP have been recognized as the critical material to construct the racing yacht structures. To establish the process of CFRP racing yacht construction, the design optimizations and production methods of carbon mast and CFRP yacht hull were discussed in this paper. Finally, the constructed CFRP sailing yacht exhibited high performance as the racing yacht through the sailing test.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.169-172
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• 2015

Dalvik is a virtual machine (VM) that is designed to run Java-based Android applications. A trace-based just-in-time (JIT) compilation technique is currently employed to improve performance of the Dalvik VM. However, due to runtime compilation overhead, the trace-based JIT compiler provides only a few simple optimizations. Moreover, because each trace contains only a few instructions, the trace-based JIT compiler inherently exploits fewer optimization and parallelization opportunities than a method-based JIT compiler that compiles method-by-method. So we propose a new method-based JIT compiler, named DEX2C, in order to improve performance by finding more opportunities for both optimization and parallelization in Android applications. We employ C code as an intermediate product in order to find more optimization opportunities by using the GNU C Compiler (GCC), and we will detect parallelism by using the Intel C/C++ parallel compiler and the AESOP compiler in our future work. In this paper, we introduce our DEX2C compiler, which dynamically translates Dalvik bytecodes (DEX) into C code with method granularity. We also describe a new method-based JIT interface in the Dalvik VM for the DEX2C compiler. Our experiment results show that our compiler and its interface achieve significant performance improvement by up to 15.2 times and 3.7 times on average, in Element Benchmark, and up to 2.8 times for FFT in Smartbench.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.319-326
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• 2009

PSO(Particle Swarm Optimization) is an optimization algorithm in which simple particles search an optimal solution using shared information acquired through their own experiences. PSO applications are so numerous and diverse. Lots of researches have been made mainly on the parameter settings, topology, particle's movement in order to achieve fast convergence to proper regions of search space for optimization. In standard PSO, since each particle uses only information of its and best neighbor, swarm does not explore diverse regions and intended to premature to local optima. In this paper, we propose a new particle's movement strategy in order to explore diverse regions of search space. The strategy is that each particle moves according to relative weights of several better neighbors. The strategy of exploring diverse regions is effective and produces less local optimizations and accelerating of the optimization speed and higher success rates than standard PSO. Also, in order to raise success rates, we propose a strategy for checking whether swarm falls into local optimum. The new PSO algorithm with these two strategies shows the improvement in the search speed and success rate in the test of benchmark functions.

• Mass Spectrometry Letters
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• v.7 no.2
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• pp.50-54
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• 2016

Multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) is currently used in our laboratory for isotopic and quantitative analyses of nuclear materials at ultra-trace levels in environmental swipe samples, which is a very useful for monitoring undeclared nuclear activities. In this study, to improve measurement precisions of uranium isotopes at ultratrace levels, we adopted a desolvating nebulizer system (Aridus-II, CETAC., USA), which can improve signal sensitivity and reduce formation of uranium hydride. A peristaltic pump was combined with Aridus-II in the sample introduction system of MC-ICP-MS to reduce long-term signal fluctuations by maintaining a constant flow rate of the sample solution. The signal sensitivity in the presence of Aridus-II was improved more than 10-fold and the formation ratio of UH/U decreased by 16- to 17- fold compared to a normal spray chamber. Long-term signal fluctuations were significantly reduced by using the peristaltic pump. Detailed optimizations and evaluations with uranium standards are also discussed in this paper.

• Composites Research
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• v.18 no.5
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• pp.34-39
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• 2005

The relationship between strain and applied potential was derived for composite actuators consisting of single-wall carbon nanotubes (SWNTs) and conductive polymers (CPs). During deriving the relationship, an electrochemical ionic approach is utilized to formulate the electromechanical actuation of the composite film actuator. This relationship can give us a direct understanding of the actuation of a nanoactuator. The results show that the well-aligned SWNTs composite actuator can give good actuation responses and high actuating forces available. The actuation is found to be affected by both SWNTs and CPs components and the actuation of SWNTs component has two kinds of influences on that of the CPs component: reinforcement at the positive voltage and abatement at the negative voltage. Optimizations of SWNTs-CPs composite actuator may be achieved by using well-aligned nanotubes as well as choosing suitable electrolyte and input voltage range.

• Journal of KIISE
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• v.42 no.6
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• pp.713-722
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• 2015

As open-source software (OSS) becomes more widely used, many users breach the terms in the license agreement of OSS, or reuse a vulnerable OSS module. Therefore, a technique needs to be developed for investigating if a binary program includes an OSS module. In this paper, we propose an efficient technique to detect a particular OSS module in an executable program using its function-level features. The conventional methods are inappropriate for determining whether a module is contained in a specific program because they usually measure the similarity between whole programs. Our technique determines whether an executable program contains a certain OSS module by extracting features such as its function-level instructions, control flow graph, and the structural attributes of a function from both the program and the module, and comparing the similarity of features. In order to demonstrate the efficiency of the proposed technique, we evaluate it in terms of the size of features, detection accuracy, execution overhead, and resilience to compiler optimizations.

• Investigative Magnetic Resonance Imaging
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• v.15 no.2
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• pp.91-101
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• 2011

Perfusion magnetic resonance imaging (pMRI) is a special technique for evaluation of blood flow. Exogenous pMRI methods which are dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) use an intravenous bolus injection of paramagnetic contrast agent. In contrast, an endogenous pMRM method which is arterial spin labeling (ASL) use diffusible blood in body. In order to scan pMRI in human, technical optimizations are very important according to disease conditions. For examples, DSC is popularly used in patients with acute stroke due to its short scan time, while DSC or DCE provides the various perfusion indices for patients with tumor. ASL is useful for children, women who are expected to be pregnant, and in patients with kidney diseases which are problematic in nephrogenic systemic fibrosis (NSF). Perfusion MRI does not require any injection of radioisotopes. We expect that demand for perfusion MRI will be higher in evaluating drug efficacy and other treatment effects.

• 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.