It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna
... Show More
It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna
... Show MoreKeywords provide the reader with a summary of the contents of the document and play a significant role in information retrieval systems, especially in search engine optimization and bibliographic databases. Furthermore keywords help to classify the document into the related topic. Keywords extraction included manual extracting depends on the content of the document or article and the judgment of its author. Manual extracting of keywords is costly, consumes effort and time, and error probability. In this research an automatic Arabic keywords extraction model based on deep learning algorithms is proposed. The model consists of three main steps: preprocessing, feature extraction and classification to classify the document
... Show MoreVisual media is a better way to deliver the information than the old way of "reading". For that reason with the wide propagation of multimedia websites, there are large video library’s archives, which came to be a main resource for humans. This research puts its eyes on the existing development in applying classical phrase search methods to a linked vocal transcript and after that it retrieves the video, this an easier way to search any visual media. This system has been implemented using JSP and Java language for searching the speech in the videos
In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.
Developed countries are facing many challenges to convert large areas of existing services to electronic modes, reflecting the current nature of workflow and the equipment utilized for achieving such services. For instance, electricity bill collection still tend to be based on traditional approaches (paper-based and relying on human interaction) making them comparatively time-consuming and prone to human error.
This research aims to recognize numbers in mechanical electricity meters and convert them to digital figures utilizing Optical Character Recognition (OCR) in Matlab. The research utilized the location of red region in color electricity meters image to determine the crop region that contain the meters numbers, then
... Show MoreThe last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of
... Show MoreThe cancer is one of the biggest health problems that facing the world . And the bladder cancer has a special place among the most spread cancers in Arab countries specially in Iraq and Egypt(2) . It is one of the diseases which can be treated and cured if it is diagnosed early . This research is aimed at studying the assistant factors that diagnose bladder cancer such as (patient's age , gender , and other major complains of hematuria , burning or pain during urination and micturition disorders) and then determine which factors are the most effective in the possibility of diagnosing this disease by using the statistical model (logistic regression model) and depending on a random sample of (128) patients . After
... Show MoreSewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the
... Show More