• The KSFM Journal of Fluid Machinery
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• v.14 no.2
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• pp.17-24
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• 2011

Temperature gradient focusing (TGF) of analytes via Joule heating is achieved when electric field is applied along a microchannel of varying width. The effect of varying width of the microchannel for the focusing performance of the device was numerically studied. The governing equations were implemented into a quasi-1D numerical model along a microchannel. The validity of the numerical model was verified by a comparison between numerical and experimental results. The distributions of temperature, velocity, and concentration along a microchannel were predicted by the numerical results. The narrower middle width and wider outside width of the channel having the fixed length contribute to improve the focusing performance of the device. However, too narrow middle width of the channel generates a higher temperature which can cause the problems including sample denaturation and buffer solution boiling. Therefore, the channel geometry should be optimized to prevent these problems. The optimal widths of the microchannel for the improvement on TGF were proposed and this model can be easily applied to lab-on-a-chip (LOC) applications where focusing is required based on its simple design.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.59-64
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• 2006

A new method to obtain explicit re-parameterization that preserves the curve degree and parametric domain is presented in this paper. The re-parameterization brings a curve very close to the arc length parameterization under $L_2$ norm but with less segmentation. The re-parameterization functions we used are $C^1$ continuous piecewise rational linear functions, which provide more flexibility and can be easily identified by solving a quadratic equation. Based on the outstanding performance of Mobius transformation on modifying pieces with monotonic parametric speed, we first create a partition of the original curve, in which the parametric speed of each segment is of monotonic variation. The values of new parameters corresponding to the subdivision points are specified a priori as the ratio of its cumulative arc length and its total arc length. $C^1$ continuity conditions are imposed to each segment, thus, with respect to the new parameters, the objective function is linear and admits a closed-form optimization. Illustrative examples are also given to assess the performance of our new method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3071-3095
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• 2013

Configuring optimization of wireless sensor networks, which can improve the network performance such as utilization efficiency and network lifetime with minimal energy, has received considerable attention in recent years. In this paper, a cross layer optimal approach is proposed for multi-source linear network and grid network under Rayleigh block-fading channels, which not only achieves an optimal utility but also guarantees the end-to-end reliability. Specifically, in this paper, we first strictly present the optimization method for optimal nodal number $N^*$, nodal placement $d^*$ and nodal transmission structure $p^*$ under constraints of minimum total energy consumption and minimum unit data transmitting energy consumption. Then, based on the facts that nodal energy consumption is higher for those nodes near the sink and those nodes far from the sink may have remaining energy, a cross layer optimal design is proposed to achieve balanced network energy consumption. The design adopts lower reliability requirement and shorter transmission distance for nodes near the sink, and adopts higher reliability requirement and farther transmission distance for nodes far from the sink, the solvability conditions is given as well. In the end, both the theoretical analysis and experimental results for performance evaluation show that the optimal design indeed can improve the network lifetime by 20-50%, network utility by 20% and guarantee desire level of reliability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.896-909
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• 2010

IEEE 802.11 medium access control (MAC) employs the distributed coordination function (DCF) as the fundamental medium access function. DCF operates with binary exponential backoff (BEB) in order to avoid frame collisions. However it may waste wireless resources because collisions occur when multiple stations are contending for frame transmissions. In order to solve this problem, a binary negative-exponential backoff (BNEB) algorithm has been proposed that uses the maximum contention window size whenever a collision occurs. However, when the number of contending stations is small, the performance of BNEB is degraded due to the unnecessarily long backoff time. In this paper, we propose the adaptive BNEB (A-BNEB) algorithm to maximize the throughput regardless of the number of contending stations. A-BNEB estimates the number of contending stations and uses this value to adjust the maximum contention window size. Simulation results show that A-BNEB significantly improves the performance of IEEE 802.11 DCF and can maintain a high throughput irrespective of the number of contending stations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3516-3541
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• 2018

Task scheduling is one of the most challenging aspects of cloud computing nowadays, and it plays an important role in improving overall performance in, and services from, the cloud, such as response time, cost, makespan, and throughput. A recent cloud task-scheduling algorithm based on the symbiotic organisms search (SOS) algorithm not only has fewer specific parameters, but also incurs time complexity. SOS is a newly developed metaheuristic optimization technique for solving numerical optimization problems. In this paper, the basic SOS algorithm is reduced, and chaotic local search (CLS) is integrated into the reduced SOS to improve the convergence rate. Simulated annealing (SA) is also added to help the SOS algorithm avoid being trapped in a local minimum. The performance of the proposed SA-CLS-SOS algorithm is evaluated by extensive simulation using the Matlab framework, and is compared with SOS, SA-SOS, and CLS-SOS algorithms. Simulation results show that the improved hybrid SOS performs better than SOS, SA-SOS, and CLS-SOS in terms of convergence speed and makespan.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.515-518
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• 1998

This paper proposes a new hybrid algorithm for auto-tuning fuzzy controllers improving the performance. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a genetic-MGM algorithm. The object of the proposed algorithm is to promote search efficiency by a genetic and modified gradient optimization techniques. The proposed genetic and MGM algorithm is based on both the standard genetic algorithm and a gradient method. If a maximum point don't be changed around an optimal value at the end of performance during given generation, the genetic-MGM algorithm searches for an optimal value using the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algorithms. Simulation results verify the validity of the presented method.

• Structural Engineering and Mechanics
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• v.58 no.5
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• pp.905-929
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• 2016

This paper assesses efficiency of the continuum method as the idealized system of building structures. A modified Coupled Two-Beam (CTB) model equipped with classical and non-classical damping has been proposed and solved analytically. In this system, complementary (non-classical) damping models composed of bending and shear mechanisms have been defined. A spatial shear damping model which is non-homogeneously distributed has been adopted in the CTB formulation and used to equivalently model passive dampers, viscous and viscoelastic devices, embedded in building systems. The application of continuum-based models for the dynamic analysis of shear wall systems has been further discussed. A reference example has been numerically analyzed to evaluate the efficiency of the presented CTB, and the optimization problems of the shear damping have been finally ascertained using local and global performance indices. The results reveal the superior performance of non-classical damping models against the classical damping. They show that the critical position of the first modal rotation in the CTB is reliable as the optimum placement of the shear damping. The results also prove the good efficiency of such a continuum model, in addition to its simplicity, for the fast estimation of dynamic responses and damping optimization issues in building systems.

• Spatial Information Research
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• v.16 no.2
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• pp.207-218
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• 2008

Providing services in a wireless environment with existing wired-based GIS solutions have many limitations such as slow communication, processing rates and screen size. This study suggested data optimization techniques in a mobile environment to overcome those limitations in four steps. In order to test the methods suggested in the study, experiments are conducted using Gangnam-gu as a test site. An existing GIS engine built in a wired environment was compared with the optimized GIS engine from the study in terms of performance in the same environment. They were also compared and analyzed in terms of response data size, number of requests processed per second, and average time to process a request. The results proved that the proposed engine shows significant improvements in performance compared with the wired GIS.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.115-125
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• 2015

This paper presents a Cuckoo search algorithm to secure adversaries misdirecting multi-hop routing in Mobile ad hoc networks (MANETs) using a robust Trust Predicated Routing Framework with an optimized cluster head selection. The clustering technique designed in this framework leads to efficient routing in MANETs. The heavy work load in the node causes an energy drop in cluster head, which leads to re-clustering of the group, and another cluster head is selected to avoid packet loss during data transmission. The problem in the re-clustering process is that the overall efficiency of the routing process is reduced and the processing time is increased. A Cuckoo search based optimization algorithm is proposed to solve the problem of re-clustering by selecting the secondary cluster head within the initially formed cluster group and eliminating the reclustering process. The proposed framework enables a node to select a reliable and secure route for MANET and the performance can be evaluated by comparing the simulated results with the AODV routing protocol, which shows that the performance of the proposed routing protocol are improved significantly.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.391-406
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• 2014

The performance of General-Purpose computation on Graphics Processing Units (GPGPU) is heavily dependent on the memory access behavior. This sensitivity is due to a combination of the underlying Massively Parallel Processing (MPP) execution model present on GPUs and the lack of architectural support to handle irregular memory access patterns. Application performance can be significantly improved by applying memory-access-pattern-aware optimizations that can exploit knowledge of the characteristics of each access pattern. In this paper, we present an algorithmic methodology to semi-automatically find the best mapping of memory accesses present in serial loop nest to underlying data-parallel architectures based on a comprehensive static memory access pattern analysis. To that end we present a simple, yet powerful, mathematical model that captures all memory access pattern information present in serial data-parallel loop nests. We then show how this model is used in practice to select the most appropriate memory space for data and to search for an appropriate thread mapping and work group size from a large design space. To evaluate the effectiveness of our methodology, we report on execution speedup using selected benchmark kernels that cover a wide range of memory access patterns commonly found in GPGPU workloads. Our experimental results are reported using the industry standard heterogeneous programming language, OpenCL, targeting the NVIDIA GT200 architecture.