• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.53-63
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• 2004

Recurrent-Cascade-Correlation(RCC) is a supervised teaming algorithm that automatically determines the size and topology of the network. RCC adds new hidden neurons one by one and creates a multi-layer structure in which each hidden layer has only one neuron. By second order RCC, new hidden neurons are added to only one hidden layer. These created neurons are not connected to each other. We present a generalization of the RCC Architecture by combining the standard RCC Architecture and the second order RCC Architecture. Whenever a hidden neuron has to be added, the new RCC teaming algorithm automatically determines whether the network topology grows vertically or horizontally. This new algorithm using sigmoid, tanh and new activation functions was tested with the morse-benchmark-problem. Therefore we recognized that the number of hidden neurons was decreased by the experiments of the RCC network generalization which used the activation functions.

• 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.

• Coupled systems mechanics
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• v.1 no.4
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• pp.361-379
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• 2012

This paper presents a fully coupled three-dimensional solver for the analysis of interaction between pulsatile flow and large deformation structure. A partitioned time marching algorithm is employed for the solution of the time dependent coupled discretised problem, enabling the use of highly developed, robust and well-tested solvers for each field. Conservative transfer of information at the fluid-structure interface is combined with an effective multi-predict-correct iterative scheme to enable implicit coupling of the interacting fields at each time increment. The three-dimensional unsteady incompressible fluid is solved using a powerful implicit time stepping technique and an ALE formulation for moving boundaries with second-order time accurate is used. A full spectrum of total variational diminishing (TVD) schemes in unstructured grids is allowed implementation for the advection terms and finite element shape functions are used to evaluate the solution and its variation within mesh elements. A finite element dynamic analysis of the highly deformable structure is carried out with a numerical strategy combining the implicit Newmark time integration algorithm with a Newton-Raphson second-order optimisation method. The proposed model is used to predict the wave flow fields of a particular flow-induced vibrational phenomenon, and comparison of the numerical results with available experimental data validates the methodology and assesses its accuracy. Another test case about three-dimensional biomedical model with pulsatile inflow is presented to benchmark the algorithm and to demonstrate the potential applications of this method.

• Earthquakes and Structures
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• v.11 no.4
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• pp.583-607
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• 2016

One of the main applications of seismic risk assessment is that an specific design could be selected for a bridge from different alternatives by considering damage losses alongside primary construction costs. Therefore, in this paper, the focus is on selecting the shape of pylon, which is a changeable component in the design of a cable-stayed bridge, as a double criterion decision-making problem. Different shapes of pylons include H, A, Y, and diamond shape, and the two criterion are construction costs and probable earthquake losses. In this research, decision-making is performed by using developed seismic risk assessment process as a powerful method. Considering the existing uncertainties in seismic risk assessment process, the combined incremental dynamic analysis (IDA) and uniform design (UD) based fragility assessment method is proposed, in which the UD method is utilized to provide the logical capacity models of the structure, and the IDA method is employed to give the probabilistic seismic demand model of structure. Using the aforementioned models and by defining damage states, the fragility curves of the bridge system are obtained for the different pylon shapes usage. Finally, by combining the fragility curves with damage losses and implementing the proposed cost-loss-benefit (CLB) method, the seismic risk assessment process is developed with financial-comparative approach. Thus, the optimal shape of the pylon can be determined using double criterion decision-making. The final results of decision-making study indicate that the optimal pylon shapes for the studied span of cable-stayed bridge are, respectively, H shape, diamond shape, Y shape, and A shape.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.359-366
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• 2009

Analysis of 3-dimensional (3D) protein structure plays an important role of structural bioinformatics. The protein structure alignment is the main subjects of the structural bioinformatics and the most fundamental problem. Protein Structures are flexible and undergo structural changes as part of their function, and most existing protein structure comparison methods treat them as rigid bodies, which may lead to incorrect alignment. We present a new method that carries out the flexible structure alignment by means of finding SSPs(Similar Substructure Pairs) and flexible points of the protein. In order to find SSPs, we encode the coordinates of atoms in the backbone of protein into RDA(Relative Direction Angle) using local similarity of protein structure. We connect the SSPs with Floyd-Warshall algorithm and make compatible SSPs. We compare the two compatible SSPs and find optimal flexible point in the protein. On our well defined performance experiment, 68 benchmark data set is used and our method is better than three widely used methods (DALI, CE, FATCAT) in terms of alignment accuracy.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.2
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• pp.65-77
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• 2000

We propose a new formulation by quadratic boolean programming to partition circuits for FPGA based reconfigurable circuit boards, in which the routing topology among IC chips are predetermined. The formulation is to minimize the sum of the wire length by considering the nets passing through IC chips for the interconnections between chips which are not adjacent, in addition to the constraints considered by the previous partition methods. We also describe a heuristic method, which consist of module assignment method to efficiently solve the problem. Experimental results show that our method generates the partitions in which the given constraints are all satisfied for all the benchmark circuits tested. The pin utilization are reduced for the most of the circuits and the total wire length of the routed nets are improved up to 34.7% compared to the previous method.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.4 s.44
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• pp.43-54
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• 2005

This paper presents cost-effectiveness evaluation of semi-active control system for cable-stayed bridge under earthquake excitations with various magnitudes and frequency contents. Semi-active control system, which is operated by using Bi-stale control method on the basis of linear quadratic Gaussian (LQG) optimal controller, is designed for the benchmark control problem proposed by Dyke et at. The cost-effectiveness of the proposed control system is defined by the ratio of life-cycle costs between a bridge structure with shock transmission units and a bridge structure with the semi-active control devices. The simulated results show that the damper cost has little influence on the cost-effectiveness of the semi-active control system while the cost-effectiveness is quite sensitive to the damage cost induced by the bridge failure. It is also found that the semi-active control system guarantees relatively high cost-effectiveness for the cable-stayed bridge subject to the ground motions in the regions of moderate seismicity with soft soil condition and strong seismicity with stiff soil condition.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.167-173
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• 2017

As the increasing use of the cloud computing, virtualization technology have been combined and applied a variety of requirements. Cloud computing has the advantage that the support computing resource by a flexible and scalable to users as they want and it utilized in a variety of distributed computing. To do this, it is especially important to ensure the stability of the cloud computing. In this paper, we analyzed a variety of component measurement using open-source tools for ensuring the performance of the system on the education system to build cloud testbed environment. And we extract the performance that may affect the virtualization environment from processor, memory, cache, network, etc on each of the host machine(Host Machine) and a virtual machine (Virtual Machine). Using this result, we can clearly grasp the state of the system and also it is possible to quickly diagnose the problem. Furthermore, the cloud computing can be guaranteed the SLA(Service Level Agreement).

• Bulletin of the Korean Chemical Society
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• v.35 no.3
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• pp.858-864
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• 2014

Recently, many researches have shown that even photosynthetic light-harvesting pigment-protein complexes can have quantum coherence in their excitonic energy transfer at cryogenic and physiological temperatures. Because the protein supplies such noisy environment around pigments that conventional wisdom expects very short lived quantum coherence, elucidating the mechanism and searching for an applicability of the coherence have become an interesting topic in both experiment and theory. We have previously studied the quantum coherence of a phycocyanin 645 complex in a marine algae harvesting light system, using Poisson mapping bracket equation (PBME). PBME is one of the applicable methods for solving quantum-classical Liouville equation, for following the dynamics of such pigment-protein complexes. However, it may suffer from many defects mostly from mapping quantum degrees of freedom into classical ones. To make improvements against such defects, benchmarking targets with more accurately described dynamics is highly needed. Here, we fall back to reduced hierarchical equation of motion (HEOM), for such a purpose. Even though HEOM is known to applicable only to simplified system that is coupled to a set of harmonic oscillators, it can provide ultimate accuracy within the regime of quantum-classical description, thus providing perfect benchmark targets for certain systems. We compare the evolution of the density matrix of pigment excited states by HEOM against the PBME results at physiological temperature, and observe more sophisticated changes of density matrix elements from HEOM. In PBME, the population of states with intermediate energies display only monotonically increasing behaviors. Most importantly, PBME suffers a serious issue of wrong population in the long time limit, likely generated by the zero-point energy leaking problem. Future prospects for developments are briefly discussed as a concluding remark.

• Journal of IKEEE
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• v.12 no.1
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• pp.65-74
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• 2008

One of the popular methods used for pattern classification is the MBR (Memory-Based Reasoning) algorithm. Since it simply computes distances between a test pattern and training patterns or hyperplanes stored in memory, and then assigns the class of the nearest training pattern, it is notorious for memory usage and can't learn additional information from new data. In order to overcome this problem, we propose an incremental learning algorithm (iMPA). iMPA divides the entire pattern space into fixed number partitions, and generates representatives from each partition. Also, due to the fact that it can not learn additional information from new data, we present iMPA which can learn additional information from new data and not require access to the original data, used to train. Proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory using benchmark data sets from UCI Machine Learning Repository.