A New Predictive Analytical Model for Software Vulnerability Discovery Process.

A software Vulnerability is defined as a flaw that exists in computer resources or control that can be exploited by one or more threats. In this presentation, we examine the existing models on the subject area and propose a new time-based differential equation model. We apply the proposed model in cumulative quarterly vulnerability data for three Operating Systems: Mac OS X, Windows 7, and Linux Kernel. Our model performs significantly better when compared with the existing models in terms of fitting and prediction capabilities

Study on the Solutions of Kawahara, and Complex-valued Burgers and Kdv-burgers Equations

The KdV equation is a nonlinear partial differential equation. The real-valued as well as complex-valued KdV equations have wide physical applications and very rich mathematical theory. The work in this dissertation studies two important problems. First, the initial- and boundary-value problem for the Kawahara equation, a fifth-order KdV type equation, is studied in weighted Sobolev spaces. This functional framework is based on the dual-Petrov-Galerkin algorithm, a numerical method proposed by Shen to solve third and higher odd-order partial differential equations. The theory presented here includes the existence and uniqueness of a local mild solution and of a global strong solution in these weighted spaces. If the L^2-norm of the initial data is sufficiently small, these solutions decay exponentially in time. Numerical computations are performed to complement the theory. Second, spatially periodic complex-valued solutions of the Burgers and KdV-Burgers equations are studied in detail. It is shown that for aDepartment of Mathematic

Agro-morphological analysis of yield and yield attributing traits of wheat under heat stress condition

Wheat is the most important cereal crop worldwide and ranks third in Nepal. Improvements in wheat yield can be done effectively by selection for yield attributing traits. In this experiment, twenty wheat genotypes were evaluated in the terai region of Nepal at Paklihawa, Rupandehi in Alpha lattice design under heat stress conditions. The characters were evaluated to find their correlation and direct and indirect effects on yield. Positive significant correlation of grain yield with No. of spikes m-2 (0.405) and harvest index (0.647) were found whereas Spike weight (-0.322) showed a significant negative correlation with grain yield. Similarly, Path analysis showed that the Harvest index (0.5511) and No. of spikelets per spike (0.3365) had a high direct effect, whereas Thousand kernel weight, Spike m-2, and Plant height showed a lower positive direct effect on grain yield. Ten spikes weight, spike length, and No. of grains per spike showed low negative direct effects. The conclusions drawn from this analysis can be useful for breeding programs under heat stress by providing information on which characteristics significantly affect the yield. However, multi-locations and multi-year trials need to be done for further verifications on the selection of such traits for improving yield

Invitro analysis of antifungal effects of botanicals on sclerotinia sclerotiorum causing white mold disease

White mold, Sclerotinia sclerotiorum, is a devastating fungal plant pathogen that has affected many crop species worldwide. Using chemicals to control the disease has been practiced over the years, whose prolonged application has negatively impacted the environment, thus finding an organic solution is crucial. The analysis quantifies the effect of 5 different local plants that have been proven to have fungicidal properties; Artemisia vulgaris L., Azadirachta indica L., Zingiber officinale Roscoe, Allium sativum L., and Lantana camara L. Poisoned food technique was used to study the inhibition effect, carried out by inoculating and growing the fungus on PDA media infused with botanical extracts. The data of mycelial mat diameter was recorded till the control plates were fully occupied. The growth-inhibiting capacity was found as 100% by Allium sativum, 28% & 43% by Azadirachta indica, 22.44% & 44% by Zingiber officinale, and 16.33% & 8.55% by Lantana camara at 10% and 20% concentrations respectively. Only a slight difference between the overall inhibition effect of the two concentrations was found with 37.22% inhibition by 20% concentration and 33.38% inhibition by 10% concentration. No inhibition effect was observed from Artemisia vulgaris which could be due to heat neutralization of the active constituent during sterilization. Further research needs to be conducted using the botanical with different sterilization techniques. This in-vitro study identified garlic as a critical antifungal alternative to conventional fungicides. Field experiments need to be done to prove its effectiveness

Complex-valued Burgers and KdV-Burgers equations

Spatially periodic complex-valued solutions of the Burgers and KdV-Burgers equations are studied in this paper. It is shown that for any sufficiently large time T, there exists an explicit initial data such that its corresponding solution of the Burgers equation blows up at T. In addition, the global convergence and regularity of series solutions is established for initial data satisfying mild conditions

Predicting the potential distribution and habitat variables associated with pangolins in Nepal

Pangolins are highly-threatened due to illegal hunting and poaching, and by the loss, degradation, and fragmentation of their habitats. In Nepal, effective conservation actions for pangolins are scarce due to limited information on the distribution of pangolins in many areas of the country. To identify the nationwide distribution of pangolins in Nepal, and assess the environmental variables associated with their habitat, we conducted an extensive literature review to collate data from previous studies, canvassed information from key informant interviews and expert opinion, and conducted transect surveys and sign surveys. The occurrence of pangolins was recorded based on sightings and indirect signs (such as burrows, digs, tracks, and scats) along 115 belt transects of 500-m length with a fixed width of 50-m, and habitat parameters were surveyed using 347 quadrats of 10 m*10 m. Pangolin presence was confirmed from 61 out of 75 districts from the eastern to the far western parts of the country. The highest frequency of burrows (74%) was observed in the forested habitat constituting brown soil with medium texture (0.02–2 mm) within an elevation range of 500–1500 m above sea level. Logistic regression suggested that the occurrence of pangolin was highly influenced by ground cover and canopy cover of 50–75%, litter depth, and the distance to termite mounds and roads. We used 4136 occurrence GPS points of pangolin burrows that were compiled and collected from the literature review and field surveys in order to predict the potential habitat distribution of pangolin using maximum entropy algorithm (MaxEnt 3.4.1). The model predicted 15.2% (22,393 km2) of the total land of Nepal as potentially suitable habitat for pangolin, with 38.3% (8574 km2) of potential habitat in the eastern region, followed by 37.6% (8432 km2) in the central and 24.1% (5,387 km2) in the western regions. The results of this study present a national baseline for pangolin distribution and serve as an important document for developing and executing conservation actions and management plans for the long-term conservation of pangolins in Nepal

Bayesian Joinpoint Regression Model for Childhood Brain Cancer Mortality

The Bayesian approach of joinpoint regression is widely used to analyze trends in cancer mortality, incidence and survival data. The Bayesian joinpoint regression model was used to study the childhood brain cancer mortality rate and its average percentage change (APC) per year. Annual observed mortality counts of children ages 0-19 from 1969-2009 obtained from Surveillance Epidemiology and End Results (SEER) database of National Cancer Institute (NCI) were analyzed. It was assumed that death counts are probabilistically characterized by the Poisson distribution and they were modeled using log link function. Results were compared with the mortality trend obtained using joinpoint software of NCI

Outside Member

iii ACKNOWLEDGMENTS The writing of this dissertation would not be possible without the support of numerous people. My sincere gratitude goes to my parents who hail from the mountain of Nepal, encourage me for my higher education, and support me in every steps of my academic career. My deepest gratitude goes to my advisor Dr. Jiahong Wu for his continuous and expert guidance throughout my graduate studies. His patience, genuine caring and concern, and availability for all of his students is incredible. I thank him for his motivating, encouraging, and enlightening teaching that guided me to pursue a career in Applied Mathematics. I am forever grateful to him for his faith in me. I am thankful to Dr. Juan-Ming Yuan from Providence University of Taiwan for teaching me numerical computations. My thanks also go out to my collaborators Dr. Bingyu Zhang from University of Cincinnatti and Ramjee Sharma from OSU. I also extend my appreciation to Dr. David Wright for teaching a topic in number theory that guided me to an important result of my dissertation. My special thank

McDonald-G Poisson Family of Distributions

In this article, we utilize the method proposed by Tahir and Cordeiro (2016) to study a new family of distributions called the McDonald Generalized Poisson (McGP) family. This family is defined by using the genesis of the McDonald distribution and the zero truncated Poisson (ZTP) distribution. We provide some mathematical properties and parameter estimation procedures of the McGP family. Three real-life data are analyzed to illustrate the potential applications of the McGP family. Our examples illustrate that the development of new probability distributions is of great interest to capture the nature of the data under study. However, one can’t guarantee a better fit just because a probability distribution possesses a larger number of parameters than its sub-model