Gastropod species belonging to Qamchuqa Formation (Aptian-Cenomanian) in the North of Iraq are studied. These species  are Harpagodes nodosus (J.de C. Sowerby,1823),  Ampullina sp.1 (Hannaa and Furisch, 2011), Ampullina sp.2 (Hannaa and Furisch, 2011), Tylostoma pallaryi (Peron and Fourtau, 1904), Calliomphalus orientalis (Douville,1916), and Pyrgulifera (Meek, 1871). They are recorded in the Upper Cretaceous succession of Northern Iraq for the first time. Most of these species are internal moulds and not abundant at any stratigraphic level but irregularly scattered in the formation.

The specialized Journalism plays an important role in our daily lives using all of its different ways, including news, caricature, commentary and dialogue. The specialized Journalism deserves vigilance and interest for it is caring about having a new media system. It is meant by “specialization”, first: identifying the areas of work in which the person concerned possesses great knowledge in the specialty resulting from a long experience, it also means being able to continuously develop required skills in that specialty. The specialization is not only a feature of the press, but also a feature of human development; thousands of years ago, the primitive society consisted of people from different specializations: fishermen, farmers, her

Radon concentrations are measured for water samples collected from twenty wells which were drilled in Hashimiya area in addition to twelve samples of surface water using Alpha Gaurd. 140 samples, 7 for each well, were collected represent wet season in continuous pumping and 20 samples, one for each well, were collected represent dry season. Concentration of radon in groundwater is many times of its concentration in surface water. The minimum concentration in groundwater is about (7) Bq/L and (5) Bq/L while the maximum concentration is about (31) Bq/L and (19) Bq/L in wet season and dry season respectively. The range of radon concentrations in river water is between (1.06) Bq/L and (1.21) Bq/L. This study has indicated that there is a flo

In this paper, the fuzzy logic and the trapezoidal fuzzy intuitionistic number were presented, as well as some properties of the trapezoidal fuzzy intuitionistic number and semi- parametric logistic regression model when using the trapezoidal fuzzy intuitionistic number. The output variable represents the dependent variable sometimes cannot be determined in only two cases (response, non-response)or (success, failure) and more than two responses, especially in medical studies; therefore so, use a semi parametric logistic regression model with the output variable (dependent variable) representing a trapezoidal fuzzy intuitionistic number.

the model was estimated on simulati

Objective: This study aimed to assessing new suggested technique of Physical Growth Curves (PGC) charts in
children under two years old of a non-probability sample.
Methodology: A non-probability sample of size (420) children under two years selected from 12 Primary
Health Care Centers in Diyala governorate during the period from 15th Nov. 2010 to 13th Mar. 2011
according to admix of a different properties together in one chart/or growth curve chart included in at least
weight, Height, and Head circumference.
Results: the results showed different properties that can be admix together in one chart/or growth curve
chart included in at least weight, Height, and Head circumference. And to overtake the problem of the norm

    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t

The 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

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c