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A guideline for the statistical analysis of compositional data in immunology
유진경,Zequn Sun,Michael Greenacre,Qin Ma,정동준,Young Min Kim 한국통계학회 2022 Communications for statistical applications and me Vol.29 No.4
The study of immune cellular composition has been of great scientific interest in immunology because of the generation of multiple large-scale data. From the statistical point of view, such immune cellular data should be treated as compositional. In compositional data, each element is positive, and all the elements sum to a constant, which can be set to one in general. Standard statistical methods are not directly applicable for the analysis of compositional data because they do not appropriately handle correlations between the compositional elements. In this paper, we review statistical methods for compositional data analysis and illustrate them in the context of immunology. Specifically, we focus on regression analyses using log-ratio transformations and the alternative approach using Dirichlet regression analysis, discuss their theoretical foundations, and illustrate their applications with immune cellular fraction data generated from colorectal cancer patients.
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Efficient End-to-End Failure Probing Matrix Construction in Data Center Networks
Jia, Zequn,Liu, Qiang,He, Ying,Wu, Qianqian,Liu, Ren Ping,Sun, Yantao 한국통신학회 2023 Journal of communications and networks Vol.25 No.4
Data centers play an essential role in the functioningof modern society. However, failures are unavoidable in datacenter networks (DCN) and will lead to negative impact on allapplications. Therefore, researchers are interested in the rapiddetection and localization of failures in DCNs. In this paper, we present a theoretical model to analyze theend-to-end failure detection methods in data center networks. Our numerical results verify that the proposed theoretical modelis accurate. In addition, we propose an algorithm to constructprobing matrices based on an enhanced probing path selectionindicator. We also introduce deep reinforcement learning (DRL)method to solve the problem and propose a DRL-based probingmatrix construction algorithm. Our experimental results showthat both of the proposed algorithms for constructing probingmatrices achieve better performance in detection accuracy thanexisting methods. We discussed different scenarios that thealgorithms are applicable to that can improve detection accuracyor construction speed performance.
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