• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.406-411
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• 2005

In this paper, we present the area-based Q-learning to search a target object using multiple robot. To search the target in Markovian space, the robots should recognize their surrounding at where they are located and generate some rules to act upon by themselves. Under area-based Q-learning, a robot, first of all, obtains 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to search for a target object while navigating in a unknown hallway where some obstacles were placed. In the end of this paper, we presents the results of three algorithms - a random search, area-based action making (ABAM), and hexagonal area-based Q-teaming.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.25-31
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• 2014

When the public key e and the composite number n=pq are disclosed but not the private key d in an asymmetric-key RSA, message decryption is carried out by obtaining ${\phi}(n)=(p-1)(q-1)=n+1-(p+q)$ and subsequently computing $d=e^{-1}(mod{\phi}(n))$. The most commonly used decryption algorithm is integer factorization of n/p=q or $a^2{\equiv}b^2$(mod n), a=(p+q)/2, b=(q-p)/2. But many of the RSA numbers remain unfactorable. This paper therefore applies baby-step giant-step discrete logarithm and $2^k$-ary modular exponentiation to directly obtain ${\phi}(n)$. The proposed algorithm performs a reverse baby-step and $2^k$-ary adult-step. As a results, it reduces the execution time of basic adult-step to $1/2^k$ times and the memory $m={\lceil}\sqrt{n}{\rceil}$ to l, $a^l$ > n, hence obtaining ${\phi}(n)$ by executing within l times.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.297-300
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• 2001

Artificial neural networks have become important tools in many fields. This paper describes a new algorithm fur training an RBF network. This algorithm has two main advantages: higher accuracy and a too stable learning process. In addition, it can be used as a good classifier in pattern recognition.

• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.71-76
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• 2014

There is to be virtually impossible to solve the very large digits of prime number p and q from composite number n=pq using integer factorization in typical public-key cryptosystems, RSA. When the public key e and the composite number n are known but the private key d remains unknown in an asymmetric-key RSA, message decryption is carried out by first obtaining ${\phi}(n)=(p-1)(q-1)=n+1-(p+q)$ and then using a reverse function of $d=e^{-1}(mod{\phi}(n))$. Integer factorization from n to p,q is most widely used to produce ${\phi}(n)$, which has been regarded as mathematically hard. Among various integer factorization methods, the most popularly used is the congruence of squares of $a^2{\equiv}b^2(mod\;n)$, a=(p+q)/2,b=(q-p)/2 which is more commonly used then n/p=q trial division. Despite the availability of a number of congruence of scares methods, however, many of the RSA numbers remain unfactorable. This paper thus proposes an algorithm that directly and immediately obtains ${\phi}(n)$. The proposed algorithm computes $2^k{\beta}_j{\equiv}2^i(mod\;n)$, $0{\leq}i{\leq}{\gamma}-1$, $k=1,2,{\ldots}$ or $2^k{\beta}_j=2{\beta}_j$ for $2^j{\equiv}{\beta}_j(mod\;n)$, $2^{{\gamma}-1}$ < n < $2^{\gamma}$, $j={\gamma}-1,{\gamma},{\gamma}+1$ to obtain the solution. It has been found to be capable of finding an arbitrarily located ${\phi}(n)$ in a range of $n-10{\lfloor}{\sqrt{n}}{\rfloor}$ < ${\phi}(n){\leq}n-2{\lfloor}{\sqrt{n}}{\rfloor}$ much more efficiently than conventional algorithms.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.245-254
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• 2021

Purpose: In order to accurately reach an underwater projectile to a target point, reliable INS and accurate arrangement of INS between master and slave INS is paramount. Unlike terrestrial and aerial environments, underwater projectile will operates in a restricted environment where location information cannot be received or sent through satellites. In this report, we review the factors affecting the transfer alignment of master and slave INS, as well as how to improve the positional error between INS through improved transfer alignment algorithms. Methods: In this work, we propose an improvement algorithm and verify it through simulation and driving test. The simulation confirmed the difference in the transfer alignment azimuth by fitting the MINS and SINS indoors, displacement in posture, and the process of transfer alignment between MINS and SINS through a driving test to confirm algorithm can improve the arrangement. Results: According to this study, reason for the error in the transfer alignment between MINS/SINS is the factors of the system where movements such as roll, pitch, yaw are not inter locked in real time due to the delay in transmit/receive system. And confirm that the improved algorithm has a desirable effect on accuracy. Conclusion: Through this work, it is possible to identify ways to improve the accuracy of underwater projectiles to reach their target points under various underwater environments and launch condition.

• Journal of IKEEE
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• v.26 no.1
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• pp.27-35
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• 2022

This paper proposes an ultrasound vessel-pattern imaging algorithm with low computational complexity. The proposed imaging algorithm reconstructs blood-vessel patterns by only detecting blood flow, and can be applied to a real-time signal processing hardware that extracts an ultrasonic finger-vessel pattern. Unlike a blood-flow imaging mode of typical ultrasound medical imaging device, the proposed imaging algorithm only reconstructs a presence of blood flow as an image. That is, since the proposed algorithm does not use an I/Q demodulation and detects a presence of blood flow by accumulating an absolute value of the clutter-filter output, a structure of the algorithm is relatively simple. To verify a complexity of the proposed algorithm, a simulation model for finger vessel was implemented using Field-II program. Through the behavioral simulation, it was confirmed that the processing time of the proposed algorithm is around 54 times less than that of the typical color-flow mode. Considering the required main building blocks and the amount of computation, the proposed algorithm is simple to implement in hardware such as an FPGA and an ASIC.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.157-166
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• 2016

In this paper, a new sag and peak voltage detector is proposed for a single-phase inverter using delta square operation. The conventional sag detector is from a single-phase digital phase-locked loop (DPLL) that is based on d-q transformations using an all-pass filter (APF). The d-q transformation is typically used in the three-phase coordinate system. The APF generates a virtual q-axis voltage component with a 90° phase delay, but this virtual phase cannot reflect a sudden change in the grid voltage at the instant the voltage sag occurs. As a result, the peak value is drastically distorted, and it settles down slowly. A modified APF generates the virtual q-axis voltage component from the difference between the current and the previous values of the d-axis voltage component in the stationary reference frame. However, the modified APF cannot detect the voltage sag and peak value when the sag occurs around the zero crossing points such as 0° and 180°, because the difference voltage is not sufficient to detect the voltage sag. The proposed algorithm detects the sag voltage through all regions including the zero crossing voltage. Moreover, the exact voltage drop can be acquired by calculating the q-axis component that is proportional to the d-axis component. To verify the feasibility of the proposed system, the conventional and proposed methods are compared using simulations and experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.1-5
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• 2005

The purpose of reinforcement learning is to maximize rewards from environment, and reinforcement learning agents learn by interacting with external environment through trial and error. Q-Learning, a representative reinforcement learning algorithm, is a type of TD-learning that exploits difference in suitability according to the change of time in learning. The method obtains the optimal policy through repeated experience of evaluation of all state-action pairs in the state space. This study chose n-Queen problem as an example, to which we apply reinforcement learning, and used Q-Learning as a problem solving algorithm. This study compared the proposed method using reinforcement learning with existing methods for solving n-Queen problem and found that the proposed method improves the convergence rate to the optimal solution by reducing the number of state transitions to reach the goal.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.191-196
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• 2002

It is one of the important measures in the area of algorithm design that any interconnection network should be embedded into another interconnection network for the practical use of algorithm. A HCN(n, n), HFN(n, n) graph also has such a good properties of a hypercube and has a lower network cost than a hypercube. In this paper, we propose a method to embed between hypercube $Q_2n$ and HCN(n, n), HFN(n, n) graph. We show that hypercube $Q_2n$ can be embedded into an HCN(n, n) and KFN(n, n) with dilation 3, and average dilation is smaller than 2. Also, we has a result that the embedding cost, a HCN(n, n) and KFN(n, n) can be embedded into a hypercube, is O(n)

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.9
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• pp.628-636
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• 2015

In this study, theoretical and experimental analyses were performed for creating and moving the zone of quiet(ZoQ) to the ear location of a sitter by using active sound control technique. As the ZoQ is actively created at the location of the error microphone basically with an active sound control system using an algorithm such as the filtered-x least mean square(FxLMS), the virtual microphone control(VMC) method was considered to move the location of the ZoQ to around the sitter`s ear. A chair system with microphones and loudspeakers on both sides was manufactured for the experiment and thus an active headrest against the swept narrowband noise as the primary noise was implemented with a real-time controller in which the VMC algorithm was embedded. After the control experiment with and without the VMC method, the location variation of the ZoQ by analyzing the error signals measured by the error and the virtual microphones. Therefore, it is observed that the FxLMS with the VMC technique can provide the re-location of the ZoQ from the error microphone location to the virtual microphone location. Also it is found that the amount of the attenuation difference between the two locations was small.