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Modeling the Air Pollution Index based on its structure and descriptive status

AIR QUALITY ATMOSPHERE AND HEALTH 2018年第2期11卷 171-179页

作者： AL-Dhurafi, Nasr Ahmed Masseran, Nurulkamal Zamzuri, Zamira Hasanah Safari, Muhammad Aslam Mohd Univ Kebangsaan Malaysia Fac Sci & Technol Sch Math Sci Bangi 43600 Selangor Malaysia

Accurate air pollution modeling is essential for estimating the Air Pollution Index (api) effectively. The air quality assessment relies on the ability of the selected probability density function (PDF) to describe the observed air pollution data. This study characterizes the api data in Klang, Malaysia, for the period of January 2005 to December 2014. The study proposed three different approaches in modeling api characteristics, including conventional models, api structure models, and descriptive status models. The first approach is the conventional models, which are the most common distributions used for modeling the api and its pollutants. The fitted distributions of the observed and generated api data are used for comparisons to other proposed models. In addition, the selected distributions of pollutants were used as a basis in the construction of api structure models. The second approach is the api structure models, which involve a mixture of distributions for the critical pollutants. Finally, the third approach was based on the descriptive status of the api. The results show that the healthy status is able to be described using the conventional fitted models, while the generalized Pareto distribution (GPD) is found to be a good fitted model for the unhealthy status. In fact, based on the selection criteria, it was found that the api structure models are superior for modeling the api data. In addition, the api descriptive status models are useful for evaluating the unhealthy api return level. In summary, we conclude that the mixture distribution of the api components should be considered as a better method for simulating the api data.

关键词： api structure Descriptive status Conventional distributions Mixture models

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Web apis structures and Data Models Analysis 19

Web APIs Structures and Data Models Analysis

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19th IEEE International Conference on Software Architecture (ICSA)

作者： Serbout, Souhaila Di Lauro, Fabio Pautasso, Cesare Univ Svizzera Italiana Software Inst Lugano Switzerland

ISBN: (纸本)9781665494939

Microservice architectures emphasize keeping components small, to foster autonomy, low coupling and independent evolution. In this large-scale empirical study we measure the size of Web api specifications mined from open source repositories. These apis are modeled using the Openapi Specification (OAS), which, in addition to documenting the offered operations, also contain schemas definitions for the data exchanged with the api request and response message payloads. This study has as a goal to build empirical knowledge about: (1) How big and diverse are real-world web apis both in terms of their operations and data, (2) How different api structures use and reuse schema definitions. By mining public software repositories on Github, we gathered 42,194 valid OAS specifications published between 2014-2021. These specifications include descriptions of Web apis of well-known services providers such as Google, VMware (Avi Networks), Twilio, Amazon. After measuring the size of api structures and their data model schemas, we found that most apis are rather small. Also there is a medium correlation between the size of the apis' functional structures and their data models. api developers do reuse schema definitions within the same api model.

关键词： Web api Openapi Data Model Schemas api Size Metrics api structure

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