Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

We have provided in this research model multi assignment  with  fuzzy function goal has been to build programming model is correct Integer Programming fogging  after removing the case from the objective function data and convert it to real data .Pascal triangular graded mean using Pascal way to the center of the triangular.

The data processing to get rid of the case fogging which is surrounded by using an Excel 2007 either model multi assignment  has been used program LNDO to reach the optimal solution, which represents less than what can be from time to accomplish a number of tasks by the number of employees on the specific amount of the Internet, also included a search on some of the

The immune infertility caused by anti-sperm antibodies (ASAs) represented about 10–20% of infertility among the couples. The ASAs interfere with sperm parameters such as sperm motility and sperm ability to penetrate cervical mucus, sperm-oocyte binding, and fertilization and embryo development. Objectives: The present study designed to assess semen analysis, presence of ASAs and DNA fragmentation index as well as correlation within these parameters in normzoospermic Iraqi subjects Patients, Materials, and Methods: A total number of Iraqi subjects (116) with range of age (20-51) years and their mean duration of infertility (4.70 ± 2.77). Seminal fluid for macroscopic and microscopic assessments done according to WHO 2010 criteria. The

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

To evaluate impact the difference in stages ofage and related incidence of hemodialysis patients.Two hundred and fifty patients undergoing hemodialysis were collected from general hospital in Baghdad city /Iraq. The samples with renal failure before hemodialysis were divided into (138) male,( 112)female. The sera were separated from samples to physiological investigation. We found that renal failure was more predominant among the patients ages group ranging from (51-70) years old. The results shows A significant increase in the levels of urea, creatinine, in younger patients (≤ 30 years) when compared with older patients (>70 years). Furthermore a significant decrease in serum levels of total protein in patients in older patients (>7