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SOME WAITING TIME ANALYSIS FOR CERTAIN QUEUEING POLICIES

  • Lim, Jong-Seul
    • Journal of applied mathematics & informatics
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    • v.29 no.1_2
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    • pp.469-474
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    • 2011
  • In a M/G/I queue where the server alternates between busy and idle periods, we assume that firstly customers arrive at the system according to a Poisson process and the arrival process and customer service times are mutually independent, secondly the system has infinite waiting room, thirdly the server utilization is less than 1 and the system has reached a steady state. With these assumptions, we analyze waiting times on the systems where some vacation policies are considered.

Breast Cancer in India: Where Do We Stand and Where Do We Go?

  • Khokhar, Anita
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.10
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    • pp.4861-4866
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    • 2012
  • This is a review article which looks into details what the actual scenario of the problem of breast cancer in our country is. As the problem is on the rise, what is the level of the preparedness at our end to tackle the problem. The articles reviews the epidemiology of breast, high risk factors, detection, diagnosis and treatment facilities also along with that screening facilities and their ground reality, awareness of the women from different walks regarding various issues of breast cancer and what intervention can be made to combat the disease.

Bootstrap Confidence Intervals for Reliability in 1-way ANOVA Random Model

  • Dal Ho Kim;Jang Sik Cho
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.87-99
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    • 1996
  • We construct bootstrap confidence intervals for reliability, R= P{X>Y}, where X and Y are independent normal random variables. One way ANOVA random effect models are assumed for the populations of X and Y, where standard deviations $\sigma_{x}$ and $\sigma_{y}$ are unequal. We investigate the accuracy of the proposed bootstrap confidence intervals and classical confidence intervals work better than classical confidence interval for small sample and/or large value of R.

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Nonparametric Estimators for Percentile Regression Functions

  • Jee, Eun-Sook
    • The Mathematical Education
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    • v.30 no.1
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    • pp.47-50
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    • 1991
  • We consider the .regression model H = h(x) + E, where h is an unknown smooth regression function ard E is the random error with unknown distribution F. in this context we present and eamine the asymptotic behavior of some nonparametric estimators for the percentile functions ζ$\_$p/(x)+ζ$\_$p/, where 0 < p < 1 and ζ$\_$p/ = inf {x : F{x} $\geq$ p}

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LPT Scheduling for Multipurpose Machines (여러 종류의 작업 처리가 가능한 기계 시스템에 대한 LPT 스케줄링)

  • Hwang, Hark-Chin
    • IE interfaces
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    • v.16 no.spc
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    • pp.132-137
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    • 2003
  • We consider scheduling jobs on multipurpose machines where jobs can be processed by a subset of the machines operated in parallel with the objective of minimizing makespan. We apply LPT(Longest Processing Time first) algorithm and prove that its posterior worst-case performance ratio is at most $log_24m/(1+{\lambda})$, where \lambda is the number of machines eligible for processing the job with the latest completion time. In general, LPT is shown to always find a schedule with makespan at most $log_24m/3$ times optimum.

THE INCLUSION THEOREMS FOR GENERALIZED VARIABLE EXPONENT GRAND LEBESGUE SPACES

  • Aydin, Ismail;Unal, Cihan
    • Korean Journal of Mathematics
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    • v.29 no.3
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    • pp.581-591
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    • 2021
  • In this paper, we discuss and investigate the existence of the inclusion Lp(.),𝜃 (𝜇) ⊆ Lq(.),𝜃 (𝜈), where 𝜇 and 𝜈 are two finite measures on (X, Σ). Moreover, we show that the generalized variable exponent grand Lebesgue space Lp(.),𝜃 (Ω) has a potential-type approximate identity, where Ω is a bounded open subset of ℝd.

Keyed learning: An adversarial learning framework-formalization, challenges, and anomaly detection applications

  • Bergadano, Francesco
    • ETRI Journal
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    • v.41 no.5
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    • pp.608-618
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    • 2019
  • We propose a general framework for keyed learning, where a secret key is used as an additional input of an adversarial learning system. We also define models and formal challenges for an adversary who knows the learning algorithm and its input data but has no access to the key value. This adversarial learning framework is subsequently applied to a more specific context of anomaly detection, where the secret key finds additional practical uses and guides the entire learning and alarm-generating procedure.

On the Design of Delay based Admission Control in Hierarchical Networks

  • Shin, Seungjae;Kim, Namgi;Lee, Byoung-Dai;Choi, Yoon-Ho;Yoon, Hyunsoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.3
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    • pp.997-1010
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    • 2014
  • Today, as the hierarchical cellular system is getting more attention than before, some recent studies introduce delay based admission control (AC) scheme which delays the admission to the macro-embedded small cell for a relatively short time to prevent unnecessary handover caused by the short-term visitors of the small cell area. In such delay based ACs, when we use improper delay parameter, the system frequently makes incorrect handover decisions such as where unnecessary handover is allowed due to too short delaying, or where necessary handover is denied due to too long delaying. In order to avoid these undesirable situations as much as possible, we develop a new delay parameter decision method based on probabilistic cell residence time approximations. By the extensive numerical and analytical evaluations, we determine the proper delay parameter which prevents the incorrect handover decision as much as possible. We expect our delay parameter decision method can be useful system administration tips in hierarchical cellular system where delay based AC is adopted.

Performance Analysis And Optimization For AF Two-Way Relaying With Relay Selection Over Mixed Rician And Rayleigh Fading

  • Fan, Zhangjun;Guo, Daoxing;Zhang, Bangning;Zeng, Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.12
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    • pp.3275-3295
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    • 2012
  • In this paper, we analyze the performance of an amplify-and-forward (AF) two-way relaying system, where two sources exchange information via the aid of an intermediate relay that is selected among multiple relays according to max-min criterion. We consider a practical scenario, where one source-relay link undergoes Rician fading, and the other source-relay link is subject to Rayleigh fading. To be specific, we derive a tight lower bound for the outage probability. From this lower bound, the asymptotic outage probability and average symbol error rate (SER) expressions are derived to gain insight into the system performance at high signal-to-noise ratio (SNR) region. Furthermore, we investigate the optimal power allocation (PA) with fixed relay location (RL), optimal RL with fixed PA and joint optimization of PA and RL to minimize the outage probability and average SER. The analytical expressions are verified through Monte Carlo simulations, where the positive impact of Rician factor on the system performance is also illustrated. Simulation results also validate the effectiveness of the proposed PA and relay positioning schemes.

Bayesian Methods for Wavelet Series in Single-Index Models

  • Park, Chun-Gun;Vannucci, Marina;Hart, Jeffrey D.
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.83-126
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    • 2005
  • Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. Here we propose a nonparametric estimation approach that combines wavelet methods for non-equispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.

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