• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.638-641
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• 2006

In this paper, A calculating cost method of maintenance and repair for bridge which is built up by new construction technique named Up-Down Precast Concrete(UDPSC). After 2000, 109 Bridges which are using UDPSC technique have been built up, 37 bridges's construction work are processing, and 194 designs are presented for construction. Because this technology has developed recently, there are few field data for analyzing the maintenance and repair cost. Therefore, the maintenance and repair cost is computed using Construction and Transportation Ministry's guide line for computation and former research's data.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.11
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• pp.137-141
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• 2007

This paper proposes a cost-effective architecture design of an angle-of-arrival (AOA) estimator based on the multiple signal identification and classification (MUSIC) algerian in UWB systems adapting Multi-band OFDM (MB-OFDM) techniques with two-receive antennas. In the proposed method, by modifying the equations of algorithm in order to remove the high computational functions, the computation power can be significantly reduced without significant performance degradation. The proposed architecture is designed and verified by Verilog HDL, and implemented into 0.13um CMOS standard cell and Xilinx FPGA circuits for the estimation of hardware complexity and computation power. From the results of the implementations, we can find that the proposed circuits reduces the hardware complexity by about 43% and the estimated computation power by about 23%, respectively, compared to the architecture employing the original MUSIC algorithm.

• Convergence Security Journal
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• v.19 no.3
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• pp.61-70
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• 2019

Recently, developments on quantum computers and cloud computing have been actively conducted. Quantum computers have been known to show tremendous computing power and Cloud computing has high accessibility for information and low cost. For quantum computers, quantum error correcting codes are essential. Similarly, cloud computing requires homomorphic encryption to ensure security. These two techniques, which are used for different purposes, are based on similar assumptions. Then, there have been studies to construct quantum homomorphic encryption based on quantum error correction code. Therefore, in this paper, we propose a scheme which can process the homomorphic encryption like quantum computation by modifying the QECCs. Conventional quantum homomorphic encryption schemes based on quantum error correcting codes does not have error correction capability. However, using the proposed scheme, it is possible to process the homomorphic encryption like quantum computation and correct the errors during computation and storage of quantum information unlike the homogeneous encryption scheme with quantum error correction code.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1996.06a
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• pp.97-109
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• 1996

In the present work computations are carried out for analysis of complicated sheet metal forming process such as forming of a rear hinge. Finite element formulation using dynamic explicit time integration scheme and step-wise combined Implicit/Explicit scheme are introduced for numerical analysis of sheet metal forming process. The rigid-plastic finite element method based on membrane elements has long been employed as a useful numerical technique for the analysis of sheet metal forming because of its time effectiveness. The explicit scheme in general use is based on the elastic-plastic modelling of material requiring large computation time. In finite element simulation of sheet metal forming processes, the robustness and stability of computation are important requirements since the computation time and convergency become major points of consideration besides the solution accuracy due to the complexity of geometry and boundary conditions. The implicit scheme employs a more reliable and rigorous scheme in considering the equilibrium at each step of deformation, while in the explicit scheme the problem of convergency is eliminated at the cost of solution accuracy. The explicit approach and the implicit approach have merits and demerits, respectively. In order to combine the merits of these two methods a step-wise combined implicit/explicit scheme has been developed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3339-3352
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• 2016

In ciphertext-policy attribute-based encryption (CP-ABE) scheme, a user's secret key is associated with a set of attributes, and the ciphertext is associated with an access policy. The user can decrypt the ciphertext if and only if the attribute set of his secret key satisfies the access policy specified in the ciphertext. In the present schemes, access policy is sent to the decryptor along with the ciphertext, which means that the privacy of the encryptor is revealed. In order to solve such problem, we propose a CP-ABE scheme with hidden access policy, which is able to preserve the privacy of the encryptor and decryptor. And what's more in the present schemes, the users need to do excessive calculation for decryption to check whether their attributes match the access policy specified in the ciphertext or not, which makes the users do useless computation if the attributes don't match the hidden access policy. In order to solve efficiency issue, our scheme adds a testing phase to avoid the unnecessary operation above before decryption. The computation cost for the testing phase is much less than the decryption computation so that the efficiency in our scheme is improved. Meanwhile, our new scheme is proved to be selectively secure against chosen-plaintext attack under DDH assumption.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• Journal of Power Electronics
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• v.19 no.2
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• pp.529-539
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• 2019

The modular multilevel converter (MMC) has become a promising topology for high-voltage direct current (HVDC) transmission systems. To control a MMC system properly, the ac-side current, circulating current and submodule (SM) capacitor voltage are taken into consideration. This paper proposes a low-computation indirect model predictive control (IMPC) strategy that takes advantages of the conventional MPC and has no weighting factors. The cost function and duty cycle are introduced to minimize the tracking error of the ac-side current and to eliminate the circulating current. An optimized merge sort (OMS) algorithm is applied to keep the SM capacitor voltages balanced. The proposed IMPC strategy effectively reduces the controller complexity and computational burden. In this paper, a discrete-time mathematical model of a MMC system is developed and the duty ratio of switching state is designed. In addition, a simulation of an eleven-level MMC system based on MATLAB/Simulink and a five-level experimental setup are built to evaluate the feasibility and performance of the proposed low-computation IMPC strategy.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.75-86
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• 2008

A remarshalling is one of the operational strategies considered importantly at a port container terminal for the fast ship operations and heighten efficiency of slacking yard. The remarshalling rearranges the containers scattered at a yard block in order to reduce the transfer time and the rehandling time of container handling equipments. This Paper deals with the rearrangement problem, which decides to where containers are transported considering time value of each operations. We propose the mixed integer programming model minimizing the weighted total operation cost. This model is a NP-hard problem. Therefore we develope the heuristic algorithm for rearrangement problem to real world adaption. We compare the heuristic algorithm with the optimum model in terms of the computation times and total cost. For the sensitivity analysis of configuration of storage and cost weight, a variety of scenarios are experimented.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.74-83
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• 2011

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.