Culmination
发表于 2025-3-25 04:24:22
Lidia Z. Filus,Jerzy K. Filus to change the data rates dynamically. By eliminating costly optical components and keeping the core optical router passive and static, the power consumption, hardware cost, and operation cost are reduced. The fine granularity bandwidth sharing and MIMO switching through PSD are verified experimenta
陪审团每个人
发表于 2025-3-25 08:18:15
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伙伴
发表于 2025-3-25 11:39:59
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TERRA
发表于 2025-3-25 19:08:42
Statistical Analysis of Modern Reliability Datae also provided using examples from industry. We also provide a brief review on recent developments of test planning and then focus on illustrating the sequential Bayesian designs with examples of fatigue testing for polymer composites. The chapter is concluded with some discussions and remarks.
柏树
发表于 2025-3-25 20:34:48
D-Efficient Mixed-Level Foldover Designs for Screening Experimentstion, the paper also provides an alternative class of D-efficient MLFODs and an exhaustive algorithm for constructing the new designs. A case study comparing two candidate MLFODs for a large mixed-level screening experiment with 17 factors used is used to demonstrate the properties of the new designs.
裁决
发表于 2025-3-26 03:27:58
Censored Data Prediction Based on Model Selection Approachesd three model selection approaches perform well when more than one candidate distributions are competing for the best underlying model. Finally, the proposed approaches are applied to three data sets. This chapter is based on Chiang et al. (Math Probl Eng, 3465909, 2018).
高原
发表于 2025-3-26 04:30:32
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B-cell
发表于 2025-3-26 08:32:42
Progressive Censoring Methodologye type I and type II censoring, we present related models like adaptive and hybrid censoring as well as, e.g., stress-strength and competing risk models for progressively censored data. Focusing on exponentially and Weibull distributed lifetimes, an extensive bibliography emphasizing recent developments is provided.
食物
发表于 2025-3-26 15:34:35
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潜移默化
发表于 2025-3-26 20:17:16
Generalized Statistical Distributionslative distribution. This mechanism has proved to be useful to make the generated distributions more flexible especially for studying tail properties than existing distributions and for improving their goodness-of-fit statistics to the data under study. Let .(.) be the cumulative distribution functi