This work is concerned with building a three-dimensional (3D) ab-initio models that is capable of predicting the thermal distribution of laser direct joining processes between Polymethylmethacrylate (PMMA) and stainless steel 304(st.st.304). ANSYS® simulation based on finite element analysis (FEA) was implemented for materials joining in two modes; laser transmission joining (LTJ) and conduction joining (CJ). ANSYS® simulator was used to explore the thermal environment of the joints during joining (heating time) and after joining (cooling time). For both modes, the investigation is carried out when the laser spot is at the middle of the joint width, at 15 mm from the commencement point (joint edge) at traveling time of 3.75 s. Process par

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.

Pleomorphic adenoma (PA) is the most frequent benign epithelial neoplasm of salivary glands, displaying a remarkable degree of morphological variety. The aim of the study is to illustrate the clinicopathological characteristics of PA with particular emphases on epithelial cell morphology and mesenchymal elements. Materials and Methods: A total of 132 PA collected between 2002 and 2017 were recruited from Al Shahid Ghazi Al Hariri Hospital and the Department of Oral Pathology, College of Dentistry, Baghdad University, Baghdad, Iraq, and analyzed for their demographic and histopathological features. All data were analyzed using descriptive statistics. A slightly higher incidence of PA was detected in females (52.3%) compared to male subject

DBNRAAK Mohammed, International Journal of Research in Social Sciences and Humanities, 2020

This research aims to choose the appropriate  probability ‎ distribution  ‎‏‎ to the reliability‎        analysis‎ for  an   item through ‎ collected data for operating and stoppage  time of  the case  study.

    Appropriate choice for .probability distribution   is when  the data look to be on or  close the form fitting line for probability plot and test the data  for  goodness of fit .

     Minitab’s 17 software  was used ‎  for this  purpose after  arranging collected data and setting it in the the program‎.

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PVC membrane sensor for the selective determination of Mefenamic acid (MFA) was constructed. The sensor is based on ion association of MFA with Dodecaphospho molybdic acid (PMA) and Dodeca–Tungstophosphoric acid(PTA) as ion pairs. Nitro benzene (NB) and di-butyl phthalate (DBPH) were used as plasticizing agents in PVC matrix membranes. The specification of sensor based on PMA showed a linear response of a concentration range 1.0 × 10–2 –1.0 × 10–5 M, Nernstian slopes of 17.1-18.86 mV/ decade, detection limit of 7 × 10-5 -9.5 × 10 -7M, pH range 3 – 8 , with correlation coefficients lying between 0.9992 and 0.9976, respectively. By using the ionphore based on PTA gives a concentration range of 1.0 × 10–4 –1.0 × 10–5 M,