OALib Journal
  OALib Journal is an all-in-one open access journal (ISSN Print: 2333-9705, ISSN Online: 2333-9721). It accepts a manuscript for the peer-review processing, typesetting, publication and then allocated to one of the 322 subject areas. The article processing charge for publishing in OALib journal is Only $99. For more details, please contact service@oalib.com. Submit now
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Jun 24, 2020Open    AccessArticle

Study on Patterns of Human Cancer Using SSN Method

Chaoyu Zhang
Human cancer, which has complex pathogenesis, is generally relative to the dysfunction of biological systems. Thus, our research is not at molecular level, but at system level, i.e. molecular network. In this paper, specially, we use PPI network. In order to construct a PPI network, we used the SSN method which is proposed by Professor X. Liu and others. The SSN method is distinct from the traditional network methods, especially in screening differential expressed genes. Besides, the traditional...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106453


May 29, 2020Open    AccessArticle

Octave Analysis of Logistic Growth Model for Pig Pen: Its Economic Viability

I. S. S. Abang, O. N. Nze, O. A. Oriola, I. S. Amasiatu
Pig pen is fast becoming a very lucrative system of farming in Nigeria, most especially in the South-Eastern region of the country. This form of animal farming is very cost effective and does not need much training before someone ventures into it, as pigs are a very special breed of animals that can eat almost any kind of food, and they do not fall sick easily when compared with chicken poultry or fish poultry business. This paper also discussed how swine breeding could help in addressing enviro...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106215


Apr 26, 2020Open    AccessArticle

The Interaction of Time with Split-Plot Using Survival Function

Hasan I. Khadher, Kawla M. Sadiq
It seems that most work has been done for continuous time random variables. Our grouped time models that are used for inference are chosen to relate to these we known continuous time models. We have generalized by the cox (1972) model to include main unit variability to time model.
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106179


Oct 28, 2019Open    AccessArticle

Statistical Parametric Analysis on Democracy Data

A. K. M. Raquibul Bashar, Chris P. Tsokos
The Economist Intelligence Unit (EIU), collected information from 167 countries of the world to classify each of the countries into four categories of Democracy and they have classified those countries based on the Democracy Index Score (DIS). EIU derived the DIS from the subject data and proceeded descriptively to use the DIS score to classify each of the countries into one of the four types of democracy
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Open Access Library J. Vol.6, 2019
Doi:10.4236/oalib.1105828


Aug 13, 2019Open    AccessArticle

Testing the Equality Hypothesis on a Cross-Covariance Matrix

Xiaomei Chen, Shibin Zhang
This paper is concerned about testing whether a cross-covariance matrix deviates from a pre-assigned one or not. For this purpose, a new test statistic is constructed based on the Frobenius norm of the difference between the sample cross-covariance matrix and the pre-assigned matrix. The test is implemented by applying the parametric bootstrap scheme. We conduct a simulation study to examine the performance of the test and compare
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Open Access Library J. Vol.6, 2019
Doi:10.4236/oalib.1105584


Aug 15, 2018Open    AccessArticle

Bayesian Predictive Analyses for Logarithmic Non-Homogeneous Poisson Process in Software Reliability

Nickson Cheruiyot, Luke Akong’o Orawo, Ali Salim Islam
This paper discusses the Bayesian approach to estimation and prediction of the reliability of software systems during the testing process. A Non-Homogeneous Poisson Process (NHPP) arising from the Musa-Okumoto (1984) software reliability model is proposed for the software failures. The Musa-Okumoto NHPP reliability model consists of two components—the execution time component and the calendar time component, and is a popular model
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Open Access Library J. Vol.5, 2018
Doi:10.4236/oalib.1104767


May 17, 2018Open    AccessArticle

Resilient Back-Propagation Algorithm in the Prediction of Mother to Child Transmission of HIV

T. O. James, S. U. Gulumbe, A. Danbaba
Prediction of a child HIV status poses real challenges in medical research. Even though there are different statistical techniques and machine learning algorithms that have been used to predict models like HIV for the clinical data with binary outcome variables, yet neural network techniques are major participants for prediction purposes. HIV is the primary cause of mortality among women of reproductive age globally an
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Open Access Library J. Vol.5, 2018
Doi:10.4236/oalib.1104538


Apr 24, 2018Open    AccessArticle

Stability of a Non-Linear Exponential Autoregressive Model

Abdulghafoor Jasem Salem, Abeer Abdulkhaleq Ahmad
In this paper, a non-linear exponential autoregressive model has been studied by applying the local linearization technique. The obtained results have been implemented in a time series which represents number of diabetic patients for ten years period.
Open Access Library J. Vol.5, 2018
Doi:10.4236/oalib.1104482


Apr 20, 2018Open    AccessArticle

A Predictive Model for Graduate Application to Enrollment

Vahid Lotfi, Bradley Maki
This study involved an investigation of factors that affect a graduate applicant in accepting an offer of admission and enrolling in a graduate program of study at a mid-sized public university. A predictive model was developed, using Decision Tree methodology to assess the probability that an admitted student would enroll in the program during the semester following acceptance. The study included actual application information su
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Open Access Library J. Vol.5, 2018
Doi:10.4236/oalib.1104499


Feb 27, 2018Open    AccessArticle

Working with Color Readings: Application of Regression Models for Determining the Concentration of Substance

Xinyuan Pan, Yan Cui
This study first considered using 5 dimensions/variables of color readings (including blue, green, saturation, red, hue) to predict the concentration of matter. The procedure was demonstrated using internet acquired data in the public domain. A stepwise regression method based on software MATLAB was used to build a model to predict the concentration of the sulfur dioxide. In the course of the study, we also discussed other linear
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Open Access Library J. Vol.5, 2018
Doi:10.4236/oalib.1104377


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