The present study aims to investigate the various request constructions used in Classical Arabic and Modern Arabic language by identifying the differences in their usage in these two different genres. Also, the study attempts to trace the cases of felicitous and infelicitous requests in the Arabic language. Methodologically, the current study employs a web-based corpus tool (Sketch Engine) to analyze different corpora: the first one is Classical Arabic, represented by King Saud University Corpus of Classical Arabic, while the second is The Arabic Web Corpus “arTenTen” representing Modern Arabic. To do so, the study relies on felicity conditions to qualitatively interpret the quantitative data, i.e., following a mixed mode method

Free-Space Optical (FSO) can provide high-speed communications when the effect of turbulence is not serious. However, Space-Time-Block-Code (STBC) is a good candidate to mitigate this seriousness. This paper proposes a hybrid of an Optical Code Division Multiple Access (OCDMA) and STBC in FSO communication for last mile solutions, where access to remote areas is complicated. The main weakness effecting a FSO link is the atmospheric turbulence. The feasibility of employing STBC in OCDMA is to mitigate these effects. The current work evaluates the Bit-Error-Rate (BER) performance of OCDMA operating under the scintillation effect, where this effect can be described by the gamma-gamma model. The most obvious finding to emerge from the analysis

The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence^. The techniques used in this paper are:

• Apparent resistivity R_wa
• R_xo /R_t

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

Background: Scientific education aims to be inclusive and to improve students learning achievements, through appropriate teaching and learning. Problem Based Learning (PBL) system, a student centered method, started in the second half of the previous century and is expanding progressively, organizes learning around problems and students learn about a subject through the experience of solving these problems.Objectives:To assess the opinions of undergraduate medical students regarding learning outcomes of PBL in small group teaching and to explore their views about the role of tutors and methods of evaluation. Type of the study: A cross-sectional study.Methods: This study was conducted in Kerbala Medical Colleges among second year students

This paper demonstrates the design of an algorithm to represent the design stages of fixturing system that serve in increasing the flexibility and automation of fixturing system planning for uniform polyhedral part. This system requires building a manufacturing feature recognition algorithm to present or describe inputs such as (configuration of workpiece) and built database system to represents (production plan and fixturing system exiting) to this algorithm. Also knowledge – base system was building or developed to find the best fixturing analysis (workpiece setup, constraints of workpiece and arrangement the contact on this workpiece) to workpiece.

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s