In this work, we construct projectively distinct (k,3)-arcs in the projective plane PG(2,9) by applying a geometrical method. The cubic curves have been been constructed by using the general equation of the cubic. We found that there are complete (13,3)-arcs, complete (15,3)-arcs and we found that the only (16,3)-arcs lead to maximum completeness

Baqubah city has grown extremely rapidly. The rate of growth exceeds the growth of services that must grow side by side with the growth of population. There are natural features that affect the growth of Baqubah city such as Dieyala river, Alssariya river, in addition to agricultural areas .All these natural features affect the growth of Baqubah city in the running form being seen . In this research the remote sensing and geographic information system (GIS) techniques are used for monitoring urban expansion and forecasting the probable axes to the growth of the city, and found that the probability of Baqubah growth to east is preferred due to Baqubah growth to the east would never interfere with natural features. Also in this res

Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined. There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements. The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more accurate t

Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined.
There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements.
The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more a

The aim of the current study is to identify the effectiveness of cognitive conflict strategy in comprehending reading among literary fifth students in literature and literature texts. The researcher uses experimental method with partial control. The sample consisted of (80) students distributed into control and experimental groups. The scientific material, the behavioral goals, the teaching plans, and the instrument of the research have been prepared (reading comprehension test) by the researcher.

The instrument's validity and reliability have been calculated and then applied to the sample. After treating the data statistically by using SPSS, the results have revealed that there is a statistically significant difference at the si

The Current research aims to identify ( the effect of Carin model in the achievement of the first intermediate Grade Students and their Reflective Thinking in physics Subject ) the researcher selected the experimental design with a partial adjust , The research sample consisted of ( 47 ) Students with ( 23 ) Students in the experimental group and ( 24 ) Students in the control group , The two groups rewarded in the variables chronological age in months , Reflective Thinking and the degrees in physics in the first course. The researcher coined the purposes of behavioral which belong to chapter fifth, sixth, and seventh of physics books scheduled of the school year ( 2015-2016 ) and prepared appropriate lesson plans for the two experimenta

ZnS:Ce3+ nanoparticles were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of ZnS:Ce3+ quantum dots were zinc acetate (R & M Chemical) as zinc source, thioacetamide as a sulfur source, cerium chloride as cerium source and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The quantum dots of ZnS:Ce3+ with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by scanning electron microscopy (SEM) also by field effect scanning electron microscopy (FESEM) and XRD. Upon exposure to 460 nm light at zero bias voltage, ZnS:Ce3+/p-Si showed a high sensitivity of 4000% an

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class