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Testing of Poisson Incidence Rate Restriction
Singh, Karan,Shanmugam, Ramalingam The Korean Reliability Society 2001 International Journal of Reliability and Applicati Vol.2 No.4
Shanmugam(1991) generalized the Poisson distribution to capture a restriction on the incidence rate $\theta$ (i.e. $\theta$ < $\beta$, an unknown upper limit), and named it incidence rate restricted Poisson (IRRP) distribution. Using Neyman's C($\alpha$) concept, Shanmugam then devised a hypothesis testing procedure for $\beta$ when $\theta$ remains unknown nuisance parameter. Shanmugam's C ($\alpha$) based .results involve inverse moments which are not easy tools, This article presents an alternate testing procedure based on likelihood ratio concept. It turns out that likelihood ratio test statistic offers more power than the C($\alpha$) test statistic. Numerical examples are included.
A Characterization of Negative Binomial Distribution Truncated at Zero
Shanmugam, R. The Korean Statistical Society 1982 Journal of the Korean Statistical Society Vol.11 No.2
Analogous to Singh's (1978) characterization of positive-Poisson distributioin and Shanmugam and Singh's (1992) characterization of logarithmic series distribution, a characterization and its statistical application of the negative binomial distribution truncated at zero are given in this paper. While it is known that under certain conditions the negative binomial distribution truncted at zero approaches the positive-Poisson and the logarithmic series distributions, we show here that the results of this paper approach in limit the results of Singh, and Shanmugam and Singh, respectively. Using the biologicla data from Sampford (1955), we illusrate our results. Also, expressions are explicitly given to test the hypothesis whether a random sample is indeed from a geometric distribution.
Shanmugam, Palanisamy,Ahn, Yu-Hwan,Sanjeevi , Shanmugam The Korean Society of Remote Sensing 2005 大韓遠隔探査學會誌 Vol.21 No.3
This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.
Shanmugam Chandrasekar,Rajangam Sivakumar,Ramasamy Mathialagan,Jayachandran Subburaj,Muthusamy Thangaraj 국립중앙과학관 2019 Journal of Asia-Pacific Biodiversity Vol.12 No.3
Indian estuarine and coastal water habitats have reduced in recent decades because of anthropogenic activities such as coastal development. The pearlspot cichlid Etroplus suratensis is designated as Least Concern, given its wide distribution and presumably large overall population size in South India, despite the declining trend observed in wild populations. To assess the genetic diversity and connectivity among South Indian coastal populations, mitochondrial displacement loop sequence analysis was conducted to provide fundamental information for future conservation studies and an understanding of population dynamics by calculating the haplotype diversity of local populations. The haplotype (h) and nucleotide (π) diversity were very low at most localities, with values ranging from 0.56061 to 0.87879 and from 0.0014 to 0.0046, respectively, which may have resulted from recent population bottlenecks or founder events. The results also revealed a clear genetic differentiation between East and West coast populations, suggesting the existence of a gene flow barrier between them. As the maintenance of genetic connectivity is a prerequisite for local population stability, the preservation of extant habitats and the restoration of water bodies along the coast of India may be the most effective measures for the sustainable maintenance of this species.
Shanmugam, Gnanendra,Dubey, Akanksha,Ponpandian, Lakshmi Narayanan,Rim, Soon Ok,Seo, Sang-Tae,Bae, Hanhong,Jeon, Junhyun The Korean Society of Plant Pathology 2018 Plant Pathology Journal Vol.34 No.3
Pine wilt disease, caused by the nematode Bursaphelenchus xylophilus, is one of the most devastating conifer diseases decimating several species of pine trees on a global scale. Here, we report the draft genome of Raoultella ornithinolytica MG, which is isolated from mountain-cultivated ginseng plant as an bacterial endophyte and shows nematicidal activity against B. xylophilus. Our analysis of R. ornithinolytica MG genome showed that it possesses many genes encoding potential nematicidal factors in addition to some secondary metabolite biosynthetic gene clusters that may contribute to the observed nematicidal activity of the strain. Furthermore, the genome was lacking key components of avermectin gene cluster, suggesting that nematicidal activity of the bacterium is not likely due to the famous anthelmintic agent of wide-spread use, avermectin. This genomic information of R. ornithinolytica will provide basis for identification and engineering of genes and their products toward control of pine wilt disease.
Shanmugam, Ashokraj,Hossain, Mohammad Rashed,Natarajan, Sathishkumar,Jung, Hee-Jeong,Song, Jae-Young,Kim, Hoy-Taek,Nou, Ill-Sup The Korean Society of Plant Biotechnology 2017 식물생명공학회지 Vol.26 No.4
$Fragaria{\times}ananassa$, a strawberry evolved from hybridization between F. virginiana and F. chiloensis, is a globally cultivated and consumed fruit crop valued for its flavor and nutritional value. Flavor and quality of fruits are determined by factors such as sugars and organic acids present during fruit development. These characteristics are highly subjective in different genotypes and affected by various environmental factors. In this study, we analyzed contents of major sugar compounds including fructose, glucose and sucrose by HPLC analysis in four cultivars namely, Maehyang, Seolhyang, Festival and Sweet Charlie. We identified 55 genes related to fructose, glucose, sucrose and soluble sugar regulation whose expression were analyzed in four cultivars at three developmental stages of the fruit namely, green, white and ripened stages. Expression of these genes across these progressive fruit developmental stages varied among cultivars. Among the 55 genes, genes FaFru3, FaSuc11 and FaGlu8 revealed differential patterns of expression along developmental stages of the fruit in high and low sugar-containing genotypes, respectively and may be putative candidates for sugar content in strawberries. Expression of genes are discussed with regard to corresponding sugar content in these genotypes. Further analysis and application of these genes may be valuable in developing high sugar containing cultivars via marker-assisted breeding.