• The Journal of Information Technology
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• v.5 no.4
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• pp.129-137
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• 2002

In this paper, a public key knapsack cryptosystem algorithm is based on the security to a difficulty of polynomial factorization in computer communication networks is proposed. For the proposed public key knapsack cryptosystem, a polynomial vector Q(x,y,z) is formed by transform of superincreasing vector P, a polynomial g(x,y,z) is selected. Next then, the two polynomials Q(x,y,z) and g(x,y,z) is decided on the public key. The enciphering first selects plaintext vector. Then the ciphertext R(x,y,z) is computed using the public key polynomials and a random integer $\alpha$. For the deciphering of ciphertext R(x,y,z), the plaintext is determined using the roots x, y, z of a polynomial g(x,y,z)=0 and the increasing property of secrety key vector. Therefore a public key knapsack cryptosystem is based on the security to a difficulty of factorization of a polynomial g(x,y,z)=0 with three variables. The propriety of the proposed public key cryptosystem algorithm is verified with the computer simulation.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.672-680
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• 2003

A shopbot is a software agent whose goal is to maximize buyer´s satisfaction through automatically gathering the price and quality information of goods as well as the services from on-line sellers. In the response to shopbots´ activities, sellers on the Internet need the agents called pricebots that can help them maximize their own profits. In this paper we adopts Q-learning, one of the model-free reinforcement learning methods as a price-setting algorithm of pricebots. A Q-learned agent increases profitability and eliminates the cyclic price wars when compared with the agents using the myoptimal (myopically optimal) pricing strategy Q-teaming needs to select a sequence of state-action fairs for the convergence of Q-teaming. When the uniform random method in selecting state-action pairs is used, the number of accesses to the Q-tables to obtain the optimal Q-values is quite large. Therefore, it is not appropriate for universal on-line learning in a real world environment. This phenomenon occurs because the uniform random selection reflects the uncertainty of exploitation for the optimal policy. In this paper, we propose a Mixed Nonstationary Policy (MNP), which consists of both the auxiliary Markov process and the original Markov process. MNP tries to keep balance of exploration and exploitation in reinforcement learning. Our experiment results show that the Q-learning agent using MNP converges to the optimal Q-values about 2.6 time faster than the uniform random selection on the average.

• Journal of KSNVE
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• v.7 no.4
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• pp.645-653
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• 1997

For high performance rotating machinery, unstable vibrations may occur caused by hydrodynamic forces such as oil film forces, clearance excitation forces generated by the working fluid, and etc. In order to improve the availability one has to take into account the vibrations very accurately. When designing a rotating machinery, the stability behavior and the resonance response can be obtained by calculation of the complex eigenvalues. A suitable modifications of seal and/or bearing design may effectively improve the stability and the response of a rotor system. This paper deals with the optimum length and clearance of seals and bearings to minimize the resonance response(Q factor) and to maximize the logarithmic decrement in the operating speed under the constraints of design variables. Also, for an avoidance of resonance region from the operating speed, an optimization technique has been used to yield the critical speeds as far from the operating speed as possible. The optimization method is used by the genetic algorithm, which is a search algorithm based on the mechanics of natural selection and natural genetics. The results show that the optimum design of seals and bearings can significantly improve the resonance and the stability of the pump rotor system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3702-3707
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• 2009

In this paper, a new approximated MAP algorithm for soft bit decision from QAM symbols is proposed for Gray Coded QAM signals, based on the Max-Log-MAP and a Gray coded QAM signal can be separated into independent two Gray coded PAM signal, M-PAM on I axis with M symbols and N-PAM on Q axis with N symbols. The Max-Log-MAP used distance comparisons between symbols to get the soft bit decision instead of mathematical exponential or logarithm functions. But in accordance with the increase of the number of symbols, the number of comparisons also increase with high complexity. The proposed algorithm is used with the Euclidean distance and constituted with plain arithmetic functions, thus we can know intuitively that the algorithm has low implementing complexity comparing to conventional ones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3C
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• pp.250-257
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• 2006

In this paper, we propose an efficient algorithm for the RDO mode decision in H.264/AVC encoder. Based on the properties of DCT coefficients and the RDO mode decision processing, we derive a new condition for detecting an error block having all-zero DCT coefficient (AZCB). (I)DCT, (I)Q, and entropy coding are skipped for AZCBs in the proposed algorithm. It makes the reduction of the computational complexity for the RDO mode decision. Simulation results show that the proposed algorithm achieves computational saving over 40% compared to the conventional method.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.3
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• pp.206-212
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• 2008

This paper proposes the PLL(Phase-Locked Loop) algorithm by a new FFT(Fast Fourier Transform) in a grid-connected PV PCS(Photovoltaics Power Conditionning System). The grid-connected inverter that is applied in a new renewable energy field needs the grid phase information for synchronism. Unlike the PLL which is normally used by three phase D-Q conversion, the preposed PLL algorithm using FFT has non-gain tuning and the powerful noise elimination by the characteristics of FFT. Both simulation and experimental result show that proposed algorithm has the good capacity.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.1
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• pp.62-69
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• 2011

A novel QEGT codebook index searching algorithm for long tenn evolution (LTE) system is proposed. The proposed algorithm divides the Q precoding vectors into M groups, and selects the optimal precoding vector from the selected group at the receiver. This algorithm reduced the calculation for searching the optimal precoding vector index compared to the previous algorithms. The index searching algorithm is implemented for TI's TMS320C6713 DSP board. When the number of transmit antenna is 4, the number of clock cycles is reduced to 25%.

• Journal of Mechanical Science and Technology
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• v.17 no.1
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• pp.146-156
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• 2003

A numerical algorithm is developed to analyze the performance of a Unit-injector (UI) System for a diesel engine. The fundamental theory of the algorithm is based on the continuity equation of fluid dynamics. The loss factors that should be seriously regarded on the continuity equation are the compressibility effect of liquid fuel, the wall friction loss in high-pressure fuel lines of the system, the kinetic energy loss of fuel in the system, and the leakage of fuel out of the control volume. For an evaluation of the developed simulation algorithm, the calculation results are compared with the experimental outputs provided by the Technical Research Center of Doowon Precision Industry Co. (DPICO) ； the maximum pressure in the plunger chamber (P$\_$p/) and total amount of fuel injected into a cylinder per cycle (Q$\_$f/) at each operational condition. The result shows that the average error rate (%) of P$\_$p/ and Q$\_$f/ are 2.90% and 4.87%, respectively, in the specified operational conditions. Hence, it can be concluded that the analytical simulation algorithm developed in this study can be reasonably applied to the performance prediction of newly designed UI system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.215-219
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• 2021

In this paper, we propose a deep reinforcement learning algorithm-based bi-directional electricity negotiation scheme that adjusts and propose the price they want to exchange for negotiation over smart building and utility grid. By employing a deep Q network algorithm, which is a kind of deep reinforcement learning algorithm, the proposed scheme adjusts the price proposal of smart building and utility grid. From the simulation results, it can be verified that consensus on electricity price negotiation requires average of 43.78 negotiation process. The negotiation process under simulation settings and scenario can also be confirmed through the simulation results.

• Journal of Korean Association for Spatial Structures
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• v.21 no.4
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• pp.73-80
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• 2021

A mid-story isolation system was proposed for seismic response reduction of high-rise buildings and presented good control performance. Control performance of a mid-story isolation system was enhanced by introducing semi-active control devices into isolation systems. Seismic response reduction capacity of a semi-active mid-story isolation system mainly depends on effect of control algorithm. AI(Artificial Intelligence)-based control algorithm was developed for control of a semi-active mid-story isolation system in this study. For this research, an practical structure of Shiodome Sumitomo building in Japan which has a mid-story isolation system was used as an example structure. An MR (magnetorheological) damper was used to make a semi-active mid-story isolation system in example model. In numerical simulation, seismic response prediction model was generated by one of supervised learning model, i.e. an RNN (Recurrent Neural Network). Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm The numerical simulation results presented that the DQN algorithm can effectively control a semi-active mid-story isolation system resulting in successful reduction of seismic responses.