• Transactions of Materials Processing
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• v.26 no.1
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• pp.28-34
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• 2017

Multi-pass shape rolling is performed to produce long products of arbitrary cross-sectional shapes. In the past, the multi-pass shape rolling process has been designed by the trial and error method or the experience of experts based on the empirical approach. Particularly, the design of roll caliber in shape rolling is important to improve product quality and dimensional accuracy. In this paper, the caliber design and pass schedule of multi-pass shape rolling were proposed for manufacturing piston ring wire. In order to design roll caliber, major shape parameter and dimension was determined by analysis of various caliber design. FE-simulation was conducted to verify effectiveness of proposed process design. At first, forming simulation was performed to predict shape of the product. Then, fracture of the wire was evaluated by critical damage value using normalized Cockcroft-Latham criteria. The experiment was carried out and the results are within the allowable tolerance.

• Smart Structures and Systems
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• v.25 no.3
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• pp.345-368
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• 2020

The present work proposes a self-controlled multi-stage optimization method for damage identification of structures utilizing standard particle swarm optimization (PSO) algorithm. Damage identification problem is formulated as an inverse optimization problem where damage severity in each element of the structure is considered as optimization variables. An efficient objective function is formed using the first few frequencies and mode shapes of the structure. This objective function is minimized by a self-controlled multi-stage strategy to identify and quantify the damage extent of the structural members. In the first stage, standard PSO is utilized to get an initial solution to the problem. Subsequently, the algorithm identifies the most damage-prone elements of the structure using an adaptable threshold value of damage severity. These identified elements are included in the search space of the standard PSO at the next stage. Thus, the algorithm reduces the dimension of the search space and subsequently increases the accuracy of damage prediction with a considerable reduction in computational cost. The efficiency of the proposed method is investigated and compared with available results through three numerical examples considering both with and without noise. The obtained results demonstrate the accuracy of the present method can accurately estimate the location and severity of multi-damage cases in the structural systems with less computational cost.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.63-70
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• 2009

BCI technology is to control communication systems or machines by brain signal among biological signals followed by signal processing. For the implementation of BCI systems, it is required that the characteristics of brain signal are learned and analyzed in real-time and the learned characteristics are applied. In this paper, we detect feature vector of EEG signal on left and right hand movements based on incremental approach and dimension reduction using the detected feature vector. In addition, we show that the reduced dimension can improve the classification performance by removing unnecessary features. The processed data including sufficient features of input data can reduce the time of processing and boost performance of classification by removing unwanted features. Our experiments using K-NN classifier show the proposed approach 5% outperforms the PCA based dimension reduction.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.2
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• pp.96-115
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• 2007

Background and Purpose: Electroencephalogram(EEG) is a multi-scaled signal consisting of several components of time series with different origins. Recently, because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to chaos theory, irregular signals of EEG can also result from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the correlation dimension. The aim of this study is to analyze correlation between the correlation dimension of EEG and psychological Test (TCI). Methods: Before and after moxibustion treatment, EEG raw data were measured by moving windows during 15 minutes. The correlation dimension(D2) was calculated from stabilized 40 seconds in 15 minutes data. 8 channels EEG study on the Fp, F, T, P was carried out in 30 subjects. Results: Correlation analysis of TCI test is calculated with deterministic non-linear data and stochastic non-linear data. 1. Novelty seeking in temperament is positive correlated with D2 of EEG on Fp. 2. reward dependence in temperament is positive correlated with D2 of EEG on T3,T4 and negative correlated with D2 of EEG on P3,P4. 3. self directedness in character is positive correlated with D2 of EEG on F4, P3. 4. Harm avoidance is negative correlated with D2 of EEG on Fp2, T3, P3. Conclusion: These results suggest that nonlinear analysis of EEG can quantify dynamic state of brain abolut psychological Test (TCI).

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1693-1713
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• 2018

An important technique used by database administrators (DBAs) is to improve performance in decision-support workloads associated with a Star schema is multi-level partitioning. Queries will then benefit from performance improvements via partition elimination, due to constraints on queries expressed on the dimension tables. As the task of multi-level partitioning can be overwhelming for a DBA we are proposing a wizard that facilitates the task by calculating a partitioning scheme for a particular workload. The system resides completely on a client and interacts with the costing estimation subsystem of the query optimizer via an API over the network, thereby eliminating any need to make changes to the optimizer. In addition, since only cost estimates are needed the wizard overhead is very low. By using a greedy algorithm for search space enumeration over the query predicates in the workload the wizard is efficient with worst-case polynomial complexity. The technology proposed can be applied to any clustering or partitioning scheme in any database management system that provides an interface to the query optimizer. Applied to the Teradata database the technology provides recommendations that outperform a human expert's solution as measured by the total execution time of the workload. We also demonstrate the scalability of our approach when the fact table (and workload) size increases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.921-940
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• 2015

In this paper, we investigate the multi-resource allocation problem, a unique feature of which is that the multiple resources can compensate each other while achieving the desired system performance. In particular, power and time allocations are jointly optimized with the target of energy efficiency under the resource-limited constraints. Different from previous studies on the power-time tradeoff, we consider a multi-server case where the concurrent serving users are quantitatively restricted. Therefore user selection is investigated accompanying the resource allocation, making the power-time tradeoff occur not only between the users in the same server but also in different servers. The complex multivariate optimization problem can be modeled as a variant of 2-Dimension Bin Packing Problem (V2D-BPP), which is a joint non-linear and integer programming problem. Though we use state decomposition model to transform it into a convex optimization problem, the variables are still coupled. Therefore, we propose an Iterative Dual Optimization (IDO) algorithm to obtain its optimal solution. Simulations show that the joint multi-resource allocation algorithm outperforms two existing non-joint algorithms from the perspective of energy efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1278-1284
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• 2010

In this paper, we propose a new mura detection algorithm for TFT-LCD effectively, which is based on multi-point, 2-dimensional FFT. Since mura in TFT-LCD has a certain area shape, it is seen as a sin wave in a LCD line. Since shapes of mura can be seen a circle, horizontal oval, or vertical oval, it is shown that they can be detected by 2-dimensional FFT easily. Through simulation for test image, it is shown that proposed algorithm can detect various sizes of mura. The proposed algorithm can be utilized in automatic test equipment for effective TFT-LCD mura detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2275-2293
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• 2020

This paper focuses on the simplified receiver design for multi-user circular block oversampled filter bank (CB-OSFB) uplink systems. Through application of discrete Fourier transform (DFT), the special banded structure and circular properties of the modulation matrix in the frequency domain of each user are derived. By exploiting the newly derived properties, a simplified zero-forcing (ZF) receiver is proposed for multi-user CB-OSFB uplink systems in the multipath channels. In the proposed receiver, the matrix inversion operation of the large dimension multi-user equivalent channel matrix is transformed into DFTs and smaller size matrix inversion operations. Simulation is given to show that the proposed ZF receiver can dramatically reduce the computational complexity while with almost the same symbol error rate as that of the traditional ZF receiver.

• Nuclear Engineering and Technology
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• v.41 no.10
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• pp.1347-1360
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• 2009

A multi-dimensional component for the thermal-hydraulic system analysis code, MARS, was developed for a more realistic three-dimensional analysis of nuclear systems. A three-dimensional and two-fluid model for a two-phase flow in Cartesian and cylindrical coordinates was employed. The governing equations and physical constitutive relationships were extended from those of a one-dimensional version. The numerical solution method adopted a semi-implicit and finite-difference method based on a staggered-grid mesh and a donor-cell scheme. The relevant length scale was very coarse compared to commercial computational fluid dynamics tools. Thus a simple Prandtl's mixing length turbulence model was applied to interpret the turbulent induced momentum and energy diffusivity. Non drag interfacial forces were not considered as in the general nuclear system codes. Several conceptual cases with analytic solutions were chosen and analyzed to assess the fundamental terms. RPI air-water and UPTF 7 tests were simulated and compared to the experimental data. The simulation results for the RPI air-water two-phase flow experiment showed good agreement with the measured void fraction. The simulation results for the UPTF downcomer test 7 were compared to the experiment data and the results from other multi-dimensional system codes for the ECC delivery flow.