In this study, different methods were used for estimating location parameter  and scale parameter for extreme value distribution, such as maximum likelihood estimation (MLE) , method of moment  estimation (ME),and approximation  estimators based on percentiles which is called white method in estimation, as the extreme value distribution is one of exponential distributions. Least squares estimation (OLS) was used, weighted least squares estimation (WLS), ridge regression estimation (Rig), and adjusted ridge regression estimation (ARig) were used. Two parameters for expected value to the percentile  as estimation for distribution f

Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and ge

Background: As the development of zirconia crown using CAD/CAM technology, the usage of full zirconia crown is gradually increased. The aim of this in-vitro study was to evaluate and contrast the vertical marginal fit of single all-ceramic translucent zirconia crowns constructed from different brands translucent zirconia blanks. Materials and Methods: An acrylic resin model of a left maxillary premolar was prepared all around the tooth with (1 mm) depth and 3D scanning to get fifteen STL files, then distributed into three groups (Imes-icor, Whitepeaks and Dental direct), 3D scanning and milling machine by Imes-icor CAD/CAM devise. Marginal gaps along vertical planes were measured at four indentations at the (mid mesial, mid distal, mid bucc

The concept of strong soft  pre-open set was initiated by Biswas and Parsanann.We utilize this notion to study several characterizations and properties of this set. We investigate the relationships between this set and other types of soft open sets. Moreover, the properties of the strong soft  pre-interior and closure are discussed. Furthermore, we define a new concept by using strong soft  pre-closed that we denote as locally strong soft  pre-closed, in which several results are obtained. We establish a new type of soft pre-open set, namely soft  pre-open. Also, we continue to study pre-  soft open set and discuss the relationships among all these sets. Some counter examples are given to show some relations

    The paper starts with the main properties of the class of soft somewhere dense open functions and follows their connections with other types of soft open functions. Then preimages of soft sets with Baire property and images of soft Baire spaces under certain classes of soft functions are discussed. Some examples are presented that support the obtained results. Further properties of somewhere dense open functions related to different types of soft functions are found under some soft topological properties.

Non thermal argon plasma needle at atmospheric pressure was generated. The experimental set up is based on very simple and low cost electric components that generate electrical field sufficiently high at the electrodes to ionize various gases, which flow at atmospheric pressure. The high d.c power supply is 7.5kV peak to peak, the frequency of the electrical field is 28kHz, and the plasma power less than 15W. The plasma is generated using only one electrode. In the present work the voltage and current discharge waveform are measured. Also the temperature of the working Ar gas at different gas flow and distances from the plasma electrode tip was recorded

In this paper, we have derived Bayesian estimation for the parameters and reliability function of Perks distribution based on two different loss functions, Lindley’s approximation has been used to obtain those values. It is assumed that the parameter behaves as a random variable have a Gumbell Type P prior with non-informative is used. And after the derivation of mathematical formulas of those estimations, the simulation method was used for comparison depending on mean square error (MSE) values and integrated mean absolute percentage error (IMAPE) values respectively. Among of conclusion that have been reached, it is observed that, the LE-NR estimate introduced the best perform for estimating the parameter λ.

The main purpose of the research is to study the significance of the event in the explicit source and its significance in the Mimi source and to explain the difference between them in the Holy Quran, especially since most linguists were not interested in what the Mime source indicates in the text, but focused on its form and form, as they defined it as the name Linguists and grammarians did not mention a difference in meaning between the explicit source and the Mimi source, and they interpret the second in the first sense, which led me to choose this topic, to know the significance of each source through Appeal to the maqam and occasion in a challenge D The exact meaning.

This paper presents a numerical simulation of the flow around elliptic groynes by using CFD ‎software. The flow was simulated in a flume with 4m long, 0.4m wide, ‎and 0.175m ‎high ‎‎with a constant bed slope. Moreover, the first Groyne placed at 1m from the flow ‎‎inlet with a ‎constant the Groyne height of 10cm and a 1cm thickness, and the ‎width of Groynes equals ‎7cm‎. A submergence ratio of the elliptic Groynes of 75% was assumed, corresponding to a discharge of ‎0.0057‎m³/sec. The CFD ‎model showed a good ability to simulate the flow ‎around ‎Groynes with ‎ good accuracy. The results of ‎CFD software showed that when using double elliptic Groy

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a