• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.183-192
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• 2001

In this paper, the decoupling H(sub)$\infty$ controller which minimizes the maximum energy in the output signal is designed to reduce the coupling properties between the input/output variables which make it difficult to control a system efficiently. The state-space formulas corresponding to the existing transfer matrix formulas of the controller are derived for computational efficiency. And for a given decoupling $H_{\infty}$ problem, an efficient method are sought to find the controller coefficients through the LMI(Linear Matrix Inequalities) method by which the problem is formulated into a convex optimization problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2153-2169
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• 2012

Femtocells provide high quality indoor communications with low transmit power. However, when femtocells are applied in cellular systems, a co-channel interference problem between macrocells and femtocells occurs because femtocells use the same spectrum as do the macrocells. To solve the co-channel interference problem, a previous study suggested a resource allocation scheme in LTE cellular systems using FFR. However, this conventional resource allocation scheme still has interference problems between macrocells and femtocells near the boundary of the sub-areas. In this paper, we define an optimization problem for resource allocation to femtocells and propose a femtocell resource allocation scheme to solve the optimization problem and the interference problems of the conventional scheme. The evaluation of the proposed scheme is conducted by System Level Simulation while varying the simulation environments. The simulation results show that the proposed scheme is superior to the conventional scheme and that it improves the overall performance of cellular systems.

• Convergence Security Journal
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• v.14 no.7
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• pp.59-64
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• 2014

We investigate $p(n){\cdot}2^{O(\sqrt{n})}$ algorithm for 0/1 knapsack problem where x is the total bit length of a list of sizes of n objects. The algorithm is adaptable of method that achieves a similar complexity for the partition and Subset Sum problem. The method can be applied to other optimization or decision problem based on a list of numerics sizes or weights. 0/1 knapsack problem can be used to solve NP-Complete Problems with pseudo-polynomial time algorithm. We try to apply this technique to bio-informatics problem which has pseudo-polynomial time complexity.

• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.477-485
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• 2020

Finite element (FE) model based structural damage detection (SDD) methods play vital roles in effectively locating and quantifying structural damages. Among these methods, structural model updating should be conducted before SDD to obtain benchmark models of real structures. However, the characteristics of updating parameters are not reasonably considered in existing studies. Inspired by the l_∞ norm regularization, a novel anti-sparse representation method is proposed for structural model updating in this study. Based on sensitivity analysis, both frequencies and mode shapes are used to define an objective function at first. Then, by adding l_∞ norm penalty, an optimization problem is established for structural model updating. As a result, the optimization problem can be solved by the fast iterative shrinkage thresholding algorithm (FISTA). Moreover, comparative studies with classical regularization strategy, i.e. the l₂ norm regularization method, are conducted as well. To intuitively illustrate the effectiveness of the proposed method, a 2-DOF spring-mass model is taken as an example in numerical simulations. The updating results show that the proposed method has a good robustness to measurement noises. Finally, to further verify the applicability of the proposed method, a six-storey aluminum alloy frame is designed and fabricated in laboratory. The added mass on each storey is taken as updating parameter. The updating results provide a good agreement with the true values, which indicates that the proposed method can effectively update the model parameters with a high accuracy.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.380-385
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• 2001

The paper presents a new multidisciplinary design optimization architecture using optimal sensitivity and coordination of interdisciplinary design variables. Original design problem is decomposed into a number of sub-problems that represent individual engineering analysis. The coupled effects between sub-problems are computed by interdisciplinary design variables. System level coordination is determined by optimal parameter sensitivity calculated by finite difference method. The proposed. MDO strategy is applied to a simplified model of rotorcraft blade design associated with structures and aerodynamic disciplines.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.4
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• pp.372-378
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• 2013

An acoustical shape optimization problem is formulated for optimal design of a perforated reactive muffler with offset inlet/outlet. The mean transmission loss value in a target frequency range is maximized for an allowed pressure drop value between an inlet and an outlet. Partitions in the chamber are divided into several sub-partitions, whose lengths are selected as design variables. Each sub-partition has the same number of holes, whose sizes are equal. A finite element model is employed for acoustical and flow analyses. A gradient-based optimization algorithm is used to obtain an optimal muffler. The acoustical and fluidic characteristics of the optimal muffler are compared with those of a reference muffler. Validation experiment is carried out to support the effectiveness of our suggested method.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.37-50
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• 2021

Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4604-4622
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• 2015

It is not easy to reconstruct the geometrical characteristics of the distorted images captured by the devices. One of the most popular optimization methods is fast iterative shrinkage/ thresholding algorithm. In this paper, to deal with its approximation error and the turbulence of the decrease process, an adaptive proximal conjugate gradient (APCG) framework is proposed. It contains three stages. At first stage, a series of adaptive penalty matrices are generated iterate-to-iterate. Second, to trade off the reconstruction accuracy and the computational complexity of the resulting sub-problem, a practical solution is presented, which is characterized by solving the variable ellipsoidal-norm based sub-problem through exploiting the structure of the problem. Third, a correction step is introduced to improve the estimated accuracy. The numerical experiments of the proposed algorithm, in comparison to the favorable state-of-the-art methods, demonstrate the advantages of the proposed method and its potential.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.11
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• pp.3398-3407
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• 1996

In this paper, we derive an algorithm and develope a computer program which analyze rapidly and precisely the inverse kinematics of robotic mechanism with spatial complex chain structure based on the relative coordinates. We represent the inverse kinematic problem as an optimization problem with the kinematic constraint equations. The inverse kinematic analysis algorithm, therefore, consists of two algorithms, the main, an optimization algorithm finding the motion of independent joints from that of an end-effector and the sub, a forward kinematic analysis algorithm computing the motion of dependent joints. We accomplish simulations for the investigation upon the accuracy and efficiency of the algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4081-4098
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• 2022

With the aim of tackling the contradiction between computation intensive industrial applications and resource-weak Edge Devices (EDs) in Industrial Internet of Things (IIoT), a novel computation task offloading scheme in SDIN-enabled MEC based IIoT is proposed in this paper. With the aim of reducing the task accomplished latency and energy consumption of EDs, a joint optimization method is proposed for optimizing the local CPU-cycle frequency, offloading decision, and wireless and computation resources allocation jointly. Based on the optimization, the task offloading problem is formulated into a Mixed Integer Nonlinear Programming (MINLP) problem which is a large-scale NP-hard problem. In order to solve this problem in an accessible time complexity, a sub-optimal algorithm GPCOA, which is based on hybrid evolutionary computation, is proposed. Outcomes of emulation revel that the proposed method outperforms other baseline methods, and the optimization result shows that the latency-related weight is efficient for reducing the task execution delay and improving the energy efficiency.