• Title/Summary/Keyword: random number generation algorithm

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A New Dynamic Prediction Algorithm for Highway Traffic Rate (고속도로 통행량 예측을 위한 새로운 동적 알고리즘)

  • Lee, Gwangyeon;Park, Kisoeb
    • Journal of the Korea Society for Simulation
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    • v.29 no.3
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    • pp.41-48
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    • 2020
  • In this paper, a dynamic prediction algorithm using the cumulative distribution function for traffic volume is presented as a new method for predicting highway traffic rate more accurately, where an approximation function of the cumulative distribution function is obtained through numerical methods such as natural cubic spline interpolation and Levenberg-Marquardt method. This algorithm is a new structure of random number generation algorithm using the cumulative distribution function used in financial mathematics to be suitable for predicting traffic flow. It can be confirmed that if the highway traffic rate is simulated with this algorithm, the result is very similar to the actual traffic volume. Therefore, this algorithm is a new one that can be used in a variety of areas that require traffic forecasting as well as highways.

A Study on the OTP Generation Algorithm for User Authentication (사용자 인증에 적합한 OTP 생성 알고리즘에 관한 연구)

  • Kim, Dong-Ryool
    • Journal of Digital Convergence
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    • v.13 no.1
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    • pp.283-288
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    • 2015
  • A disposable password is necessary to avoid any danger by the use of a static password and reinforce the user's authentication. In order to prevent personal information from being exposed, OTP generation algorithm is regarded as important. The OTP generation algorithm we suggest in this thesis generates 256-bit-size OTP Data by using Seed value and Time value. This value that the generated OTP Data are arranged with a matrix and a 32-bit-value is extracted on an irregular basis becomes the final value. We can find out that the more OTP generation frequency we have, the lower probability of clash tolerance we get in our suggested algorithm, compared to the previous algorithm.

Secret Key Generation Using Reciprocity in Ultra-wideband Outdoor Wireless Channels

  • Huang, Jing Jing;Jiang, Ting
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.2
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    • pp.524-539
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    • 2014
  • To investigate schemes of secret key generation from Ultra-wideband (UWB) channel, we study a statistical characterization of UWB outdoor channel for a campus playground scenario based on extensive measurements. Moreover, an efficient secret key generation mechanism exploiting multipath relative delay is developed, and verification of this algorithm is conducted in UWB Line-of-sight (LOS) outdoor channels. For the first time, we compare key-mismatch probability of UWB indoor and outdoor environments. Simulation results demonstrate that the number of multipath proportionally affects key generation rate and key-mismatch probability. In comparison to the conventional method using received signal strength (RSS) as a common random source, our mechanism achieves better performance in terms of common secret bit generation. Simultaneously, security analysis indicates that the proposed scheme can still guarantee security even in the sparse outdoor physical environment free of many reflectors.

Adaptive Random Testing for Integrated System based on Output Distribution Estimation (통합 시스템을 위한 출력 분포 기반 적응적 랜덤 테스팅)

  • Shin, Seung-Hun;Park, Seung-Kyu;Choi, Kyung-Hee;Jung, Ki-Hyun
    • Journal of the Korea Society for Simulation
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    • v.20 no.3
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    • pp.19-28
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    • 2011
  • Adaptive Random Testing (ART) aims to enhance the performance of pure random testing by detecting failure region in a software. The ART algorithm generates effective test cases which requires less number of test cases than that of pure random testing. However, all ART algorithms currently proposed are designed for the tests of monolithic system or unit level. In case of integrated system tests, ART approaches do not achieve same performances as those of ARTs applied to the unit or monolithic system. In this paper, we propose an extended ART algorithm which can be applied to the integrated system testing environment without degradation of performance. The proposed approach investigates an input distribution of the unit under a test with limited number of seed input data and generates information to be used to resizing input domain partitions. The simulation results show that our approach in an integration environment could achieve similar level of performance as an ART is applied to a unit testing. Results also show resilient effectiveness for various failure rates.

Performance Improvement of Multi-Start in uDEAS Using Guided Random Bit Generation (유도된 이진난수 생성법을 이용한 uDEAS의 Multi-start 성능 개선)

  • Kim, Eun-Su;Kim, Man-Seak;Kim, Jong-Wook
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.4
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    • pp.840-848
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    • 2009
  • This paper proposes a new multi-start scheme that generates guided random bits in selecting initial search points for global optimization with univariate dynamic encoding algorithm for searches (uDEAS). The proposed method counts the number of 1 in each bit position from all the previously generated initial search matrices and, based on this information, generates 0 in proportion with the probability of selecting 1. This rule is simple and effective for improving diversity of initial search points. The performance improvement of the proposed multi-start is validated through implementation in uDEAS and function optimization experiments.

A Study on Mobile OTP Generation Model (모바일 OTP 생성 모델에 관한 연구)

  • Jeong, Yoon-Su;Han, Sang-Ho;Shin, Seung-Soo
    • Journal of Digital Convergence
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    • v.10 no.2
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    • pp.183-191
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    • 2012
  • This study proposes dual certification model using both what users know and what users own. In detail, this mobile OTP generation model is made up of mobile OTP generation and extraction algorithm satisfying the conditions for reviewing mobile OTP implementation. In order to improve the security of the existing OTP-based systems, the suggested method utilizes user's ID and random number at the mobile OTP generation stage.

Genetic algorithm-based content distribution strategy for F-RAN architectures

  • Li, Xujie;Wang, Ziya;Sun, Ying;Zhou, Siyuan;Xu, Yanli;Tan, Guoping
    • ETRI Journal
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    • v.41 no.3
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    • pp.348-357
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    • 2019
  • Fog radio access network (F-RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm-based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F-RAN. First, an F-RAN system model is presented that includes a certain number of randomly distributed fog access points (F-APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F-RANs is described. Third, the details of the proposed optimal genetic algorithm-based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.

Efficient Weighted Random Pattern Generation Using Weight Set Optimization (가중치 집합 최적화를 통한 효율적인 가중 무작위 패턴 생성)

  • 이항규;김홍식;강성호
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.9
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    • pp.29-37
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    • 1998
  • In weighted random pattern testing it is an important issue to find the optimal weight sets for achieving a high fault coverage using a small number of weighted random patterns. In this paper, a new weight set optimization algorithm is developed, which can generate the optimal weight sets in an efficient way using the sampling probabilities of deterministic tests patterns. In addition, the simulation based method of finding the proper maximum Hamming distance is presented. Experimental results for ISCAS 85 benchmark circuits prove the effectiveness of the new weight set optimization algorithm and the method of finding the proper maximum Hamming distance.

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Large eddy simulation of a square cylinder flow: Modelling of inflow turbulence

  • Tutar, M.;Celik, I.
    • Wind and Structures
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    • v.10 no.6
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    • pp.511-532
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    • 2007
  • The present study aims to generate turbulent inflow data to more accurately represent the turbulent flow around a square cylinder when the inflow turbulence level is significant. The modified random flow generation (RFG) technique in conjunction with a previously developed LES code is successfully adopted into a finite element based fluid flow solver to generate the required inflow turbulence boundary conditions for the three-dimensional (3-D) LES computations of transitional turbulent flow around a square cylinder at Reynolds number of 22,000. The near wall region is modelled without using wall approximate conditions and a wall damping coefficient is introduced into the calculation of sub-grid length scale in the boundary layer of the cylinder wall. The numerical results obtained from simulations are compared with each other and with the experimental data for different inflow turbulence boundary conditions in order to discuss the issues such as the synthetic inflow turbulence effects on the 3-D transitional flow behaviour in the near wake and the free shear layer, the basic mechanism by which stream turbulence interacts with the mean flow over the cylinder body and the prediction of integral flow parameters. The comparison among the LES results with and without inflow turbulence and the experimental data emphasizes that the turbulent inflow data generated by the present RFG technique for the LES computation can be a viable approach in accurately predicting the effects of inflow turbulence on the near wake turbulent flow characteristics around a bluff body.

Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response

  • Oh, S.H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.25 no.3
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    • pp.299-303
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    • 2012
  • Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ($\bar{r_j}$) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, $EBV^*=EBV_j(1-k\bar{{r}_j})$ Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs.