• Title/Summary/Keyword: Q-algorithm

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A Dynamic OHT Routing Algorithm in Automated Material Handling Systems (자동화 물류시스템 내 차량 혼잡도를 고려한 무인운반차량의 동적 경로 결정 알고리즘)

  • Kang, Bonggwon;Kang, Byeong Min;Hong, Soondo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.45 no.3
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    • pp.40-48
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    • 2022
  • An automated material handling system (AMHS) has been emerging as an important factor in the semiconductor wafer manufacturing industry. In general, an automated guided vehicle (AGV) in the Fab's AMHS travels hundreds of miles on guided paths to transport a lot through hundreds of operations. The AMHS aims to transfer wafers while ensuring a short delivery time and high operational reliability. Many linear and analytic approaches have evaluated and improved the performance of the AMHS under a deterministic environment. However, the analytic approaches cannot consider a non-linear, non-convex, and black-box performance measurement of the AMHS owing to the AMHS's complexity and uncertainty. Unexpected vehicle congestion increases the delivery time and deteriorates the Fab's production efficiency. In this study, we propose a Q-Learning based dynamic routing algorithm considering vehicle congestion to reduce the delivery time. The proposed algorithm captures time-variant vehicle traffic and decreases vehicle congestion. Through simulation experiments, we confirm that the proposed algorithm finds an efficient path for the vehicles compared to benchmark algorithms with a reduced mean and decreased standard deviation of the delivery time in the Fab's AMHS.

ON COMPLEXITY ANALYSIS OF THE PRIMAL-DUAL INTERIOR-POINT METHOD FOR SECOND-ORDER CONE OPTIMIZATION PROBLEM

  • Choi, Bo-Kyung;Lee, Gue-Myung
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.14 no.2
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    • pp.93-111
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    • 2010
  • The purpose of this paper is to obtain new complexity results for a second-order cone optimization (SOCO) problem. We define a proximity function for the SOCO by a kernel function. Furthermore we formulate an algorithm for a large-update primal-dual interior-point method (IPM) for the SOCO by using the proximity function and give its complexity analysis, and then we show that the new worst-case iteration bound for the IPM is $O(q\sqrt{N}(logN)^{\frac{q+1}{q}}log{\frac{N}{\epsilon})$, where $q{\geqq}1$.

Quantitative Structure-Activity Relationships for Radical Scavenging Activities of Flavonoid Compounds by GA-MLR Technique

  • Om, Ae-Son;Ryu, Jae-Chun;Kim, Jae-Hyoun
    • Molecular & Cellular Toxicology
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    • v.4 no.2
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    • pp.170-176
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    • 2008
  • The quantitative structure-activity relationship (QSAR) of a set of 35 flavonoid compounds presenting antioxidant activity was established by means of Genetic Algorithm-Multiple Linear Regression (GA-MLR) technique. Four-parametric models for two sets of data, the 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity $(R^2=0.788,\;Q^2_{cv}=0.699\;and\;Q^2_{ext}=0.577)$ and scavenging activity of reactive oxgen species (ROS) induced by $H_2O_2 (R^=0.829,\;Q^2_{cv}=0.754\;and\;Q^2_{ext}=0.573)$ were obtained with low external predictive ability on a mass basis, respectively. Each model gave some different mechanistic aspects of the flavonoid compounds tested in terms of the radical scavenging activity. Topological charge, H-bonding complex and deprotonation processes were likely to be involved in the radical scavenging activity.

The Application of Industrial Inspection of LED

  • Xi, Wang;Chong, Kil-To
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.91-93
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    • 2009
  • In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

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EXTRAPOLATED CRANK-NICOLSON APPROXIMATION FOR A LINEAR STEFAN PROBLEM WITH A FORCING TERM

  • Ahn, Min-Jung;Lee, Hyun-Young
    • Journal of applied mathematics & informatics
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    • v.8 no.3
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    • pp.773-793
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    • 2001
  • The explicit expressions for the 2n+1 primitive idempotents in R/sub pⁿ/ = F[x]/< x/sup pⁿ/ -1>, where F is the field of prime power order q and the multiplicative order of q modulo pⁿ is ø(pⁿ)/2(n≥1 and p is an odd prime), are obtained. An algorithm for computing the generating polynomials of the minimal QR cyclic codes of length pⁿ, generated by these primitive idempotents, is given and hence some bounds on the minimum distance of some QR codes of prime length over GF(q)(q=2, 3, ...) are obtained.

Enhanced Machine Learning Algorithms: Deep Learning, Reinforcement Learning, and Q-Learning

  • Park, Ji Su;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • v.16 no.5
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    • pp.1001-1007
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    • 2020
  • In recent years, machine learning algorithms are continuously being used and expanded in various fields, such as facial recognition, signal processing, personal authentication, and stock prediction. In particular, various algorithms, such as deep learning, reinforcement learning, and Q-learning, are continuously being improved. Among these algorithms, the expansion of deep learning is rapidly changing. Nevertheless, machine learning algorithms have not yet been applied in several fields, such as personal authentication technology. This technology is an essential tool in the digital information era, walking recognition technology as promising biometrics, and technology for solving state-space problems. Therefore, algorithm technologies of deep learning, reinforcement learning, and Q-learning, which are typical machine learning algorithms in various fields, such as agricultural technology, personal authentication, wireless network, game, biometric recognition, and image recognition, are being improved and expanded in this paper.

An Efficient String Similarity Search Technique based on Generating Inverted Lists of Variable-Length Grams (가변길이 그램의 역리스트 생성을 이용한 효율적인 유사 문자열 검색 기법)

  • Kim, Jongik
    • Journal of KIISE
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    • v.43 no.11
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    • pp.1275-1280
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    • 2016
  • Existing techniques for string similarity search first generate a set of candidate strings and then verify the candidates. The efficiency of string similarity search is highly dependent on candidate generation methods. State of the art techniques select fixed length q-grams from a query string and generate candidates using inverted lists of the selected q-grams. In this paper, we propose a technique to generate candidates using variable length grams of a query string and develop a dynamic programming algorithm that selects an optimal combination of variable length grams from a query string. Experimental results show that the proposed technique improves the performance of string similarity search compared with the existing techniques.

Quality Control Algorithm of Rainfall Radar Image for Uncertainty of Rainfall (강우의 불확실성에 관한 강우레이더 영상 품질관리 알고리즘)

  • Choi, Jeongho;Yoo, Chulsang;Lim, Sanghun;Han, Myoungsun;Lee, Baekyu
    • Journal of Korea Multimedia Society
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    • v.20 no.12
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    • pp.1874-1889
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    • 2017
  • The paper aims to analyze structure of I/Q data observed from radar and reliably estimate rainfall through quality control of I/Q data that can quantify uncertainty of I/Q data occurring due to resultant errors. Radar rainfall data have strong uncertainty due to various factors influencing quality. In order to reduce this uncertainty, previously enumerated errors in quality need to be eliminated. However, errors cannot be completely eliminated in some cases as seen in random errors, so uncertainty is necessarily involved in radar rainfall data. Multi-Lag Method, one of I/Q data quality control methods, was applied to estimate precipitation with regard to I/Q data of rainfall radar in Mt. Sobaek.

A Parallel Implementation of the Order-Preserving Multiple Pattern Matching Algorithm using Fingerprints of Texts (텍스트의 핑거프린트를 이용한 순위다중패턴매칭 알고리즘 병렬 구현)

  • Park, Somin;Kim, Youngho;Sim, Jeong Seop
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.57-60
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    • 2020
  • 순위다중패턴매칭문제는 길이가 n인 텍스트 T와 패턴들의 집합 P' = {P1,P2…,Pk}가 주어졌을 때, P'에 속하는 패턴들과 상대적인 순위가 일치하는 T의 모든 부분문자열들의 위치를 찾는 문제이다. P'에서 가장 짧은 패턴의 길이가 m, 가장 긴 패턴의 길이를 $\bar{m}$, 모든 패턴들의 길이의 합을 M, q개의 연속된 문자들을 q-그램이라 할 때, 기존에 텍스트의 핑거프린트를 이용하여 순위다중패턴매칭문제를 $O(q!+nqlogq+Mlog\bar{m}+nM)$ 시간에 해결하는 알고리즘이 제시되었다. 본 논문에서는 텍스트의 핑거프린트를 활용하여 O(max(q!,M,n))개의 스레드를 이용하여 순위다중패턴매칭문제를 평균적으로 $O(\bar{m}+qlogq+n/q!)$ 시간에 해결하는 병렬 구현 방법을 제시한다. 실험 결과, n = 1,000,000, k = 1,000, m = 5, q = 3일 때, 본 논문에서 제시하는 병렬 구현 방법은 기존의 순차 알고리즘보다 약 19.8배 빠르게 수행되었다.

Integer Factorization Algorithm of Pollard's Rho Based on Multiple Initial Values (다중 초기치 Pollards's Rho 소인수분해 알고리즘)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.6
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    • pp.19-25
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    • 2017
  • This paper deals with integer factorization of two prime p,q of SHA-256 secure hash value n for Bit coin mining. This paper proposes an algorithm that greatly reduces the execution time of Pollard's rho integer factorization algorithm. Rho(${\rho}$) algorithm computes $x_i=x^2_{i-1}+1(mod\;n)$ and $y_i=[(y^2_{i-1}+1)^2+1](mod\;n)$ for intial values $(x_0,y_0)=(2,2)$ to find the factor 1 < $gcd({\mid}x_i-y_i{\mid},n)$ < n. It however fails to factorize some particular composite numbers. The algorithm proposed in this paper applies multiple initial values $(x_0,y_0)=(2^k,2^k)$ and ($2^k,2$), $2{\leq}k{\leq}10$ to the existing Pollard's Rho algorithm. As a results, the proposed algorithm achieves both the factorization of all the composite numbers and the reduction of the execution time of Pollard's Rho by 67.94%.