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Depth-Based rank test for multivariate two-sample scale problem
Digambar Tukaram Shirke,Swapnil Dattatray Khorate The Korean Statistical Society 2023 Communications for statistical applications and me Vol.30 No.3
In this paper, a depth-based nonparametric test for a multivariate two-sample scale problem is proposed. The proposed test statistic is based on the depth-induced ranks and is thus distribution-free. In this article, the depth values of data points of one sample are calculated with respect to the other sample or distribution and vice versa. A comprehensive simulation study is used to examine the performance of the proposed test for symmetric as well as skewed distributions. Comparison of the proposed test with the existing depth-based nonparametric tests is accomplished through empirical powers over different depth functions. The simulation study admits that the proposed test outperforms existing nonparametric depth-based tests for symmetric and skewed distributions. Finally, an actual life data set is used to demonstrate the applicability of the proposed test.
Yogita M.shirke,Seong-Jun Cho,Soon Jin Kwon,Won-Kil Choi,Seong Uk Hong,Jae-Deok Jeon 한국에너지기후변화학회 2021 한국에너지기후변화학회 학술대회 Vol.2021 No.11
Power generation in recent decades has been carried out by coal-fired power plants, which use coal to generate electricity. Burning of coal is generated large quantities of flue gas which contains N₂, O₂, CO₂, nitrogen oxides (NOx), sulfur oxides (SOx), fly ash, and water vapor. Lots of water vapor discharged from stacks and cooling towers of factories into the atmosphere is a serious crisis, as global warming is growing and more consumption of the limited water resources. In addition, white flume produced by condensing water vapor from flue gas becomes a cause of visual pollution. In the presence of a large amount of water vapor in the stack, condensation can readily occur, resulting in corrosion. For these reasons, water vapor is preferably removed from flue gas. On the other hand, volatile organic compounds (VOCs) are a generic term for liquid or gaseous hydrocarbon compounds that are easily evaporated into the atmosphere due to their high vapor pressure. These VOCs are emitted from public power generation facilities, district heating facilities, petroleum refining facilities, private power generation facilities, organic chemical product manufacturing industries, and other combustible or noncombustible sources, resulting in leading to compromised air quality. Therefore, it is necessary to create a clean environment by removing not only water vapor but also VOCs. Many technologies are used to remove water vapor and VOCs, but they have their own characteristics. For example, heat treatment technology is more suitable for high VOC concentrations (preferred for large and medium-sized workplace), adsorption treatment technology is more suitable for low VOC concentrations (preferred for small and medium-sized workplace). Membrane-based technology does not require thermal regeneration and phase change, and thus consumes less energy. Furthermore, it is compact, energy-efficient, easy to scale, low initial investment and simple to use and maintain. Therefore, membrane-based technology can be an attractive alternative that is used as a hybrid with existing technologies or to replace existing technologies to remove water vapor and VOCs. In this study, we propose a method of removing water vapor and VOCs together by using polymeric hollow fiber membranes. The polymeric membranes are coated with hydrophilic materials and hydrophobic materials to remove water vapor and VOCs, respectively. In order to further improve their performance, thin film nanocomposite (TFN) membranes with nanoparticles are also developed and tested the separation performance for environmental care.
Nonparametric two sample tests for scale parameters of multivariate distributions
Chavan, Atul R,Shirke, Digambar T The Korean Statistical Society 2020 Communications for statistical applications and me Vol.27 No.4
In this paper, a notion of data depth is used to propose nonparametric multivariate two sample tests for difference between scale parameters. Data depth can be used to measure the centrality or outlying-ness of the multivariate data point relative to data cloud. A difference in the scale parameters indicates the difference in the depth values of a multivariate data point. By observing this fact on a depth vs depth plot (DD-plot), we propose nonparametric multivariate two sample tests for scale parameters of multivariate distributions. The p-values of these proposed tests are obtained by using Fisher's permutation approach. The power performance of these proposed tests has been reported for few symmetric and skewed multivariate distributions with the existing tests. Illustration with real-life data is also provided.
Abou-Elanwar, Ali M.,Shirke, Yogita M.,Ingole, Pravin G.,Choi, Won-Kil,Lee, Hyojin,Hong, Seong Uk,Lee, Hyung Keun,Jeon, Jae-Deok The Royal Society of Chemistry 2018 Journal of materials chemistry. A, Materials for e Vol.6 No.47
<P>Recyclable βCD-Fe3O4nanoparticles are successfully synthesized by the co-precipitation method and incorporated into thin-film polyamide membranes by interfacial polymerization reaction between diethylene triamine (DETA) and trimesoyl chloride (TMC) on the surface of polysulfone (PSf) hollow fibers, forming thin-film nanocomposite (TFN) membranes. The structural and morphological features of the synthesized nanoparticles and fabricated TFN membranes are characterized using various techniques. The high-resolution transmission electron microscopy (HR-TEM) mapping data show that the core of the nanoparticles consists of iron and oxygen and their shells are surrounded by βCD. The energy dispersive X-ray (EDX) data reveal that the iron content increases from 0 to 0.07 atomic% when the βCD-Fe3O4loading increases from 0 to 1.0 wt%. Water vapor/nitrogen gas permeation tests indicate that the addition of nanoparticles in the polyamide membranes increases the water vapor permeation due to the enhanced sorption sites and surface area provided by the nanoparticles. The best performance of TFN membranes includes a water vapor permeance of 2237 GPU and a water vapor/nitrogen selectivity of 774 when the content of βCD-Fe3O4nanoparticles is 0.2 w/w% with respect to the DETA monomer. Further research on these βCD-Fe3O4nanoparticles can potentially lead to a promising candidate material for water vapor separation membranes.</P>