من الضروري اجراء تحليل الحساسية للمشاريع الاستثمارية التي يتبناها القطاع  العام أو الخاص وذلك لسببين ، الاول هو تضمين عامل المخاطرة واللاتاكد عند تقييم المشروع من الناحية الاقتصادية ، حيث لابد من يكون نسبة مخاطرة وعدم تاكد عند تقييم أي مشروع لمجابهة احداث المستقبل الغير متوقعة ، الثاني المنافسة الشديدة بين المنتجات المحلية والمستوردة  ، حيث ان تحليل الحساسية يعطينا صورة عن مدى حساسية القيمة الحالية

Algeria is one of the states that are important to the Ottoman state, because of its geographic location is important to the Mediterranean Sea, as well as the economic resources of the nature of its soil geography and climate,diverse, making it the focus of attention of the Ottomans, along with the van, which has increased the interest of the Ottomans in Algeriais the fall Andalusat the hands of the Spaniardsin1492, and force the Muslims to get out of them, and did not Only Europeans do it, butrushed to the prosecution of Muslims tothe coast of North Africa and seizing control of manyofits ports and cities, prompting the Ottoman state to go forth and back to the barn Muslims,Especially after hehad appealed to the Arabs of the Ottoman sta

The research topic is summarized in the importance of studying the measuring the extent of the university youth’s exposure in the Emirati Society to those series and the resulting achieved satisfaction. The most important results and recommendations of the study are as follows: a high rate of the respondents’, sample individuals, exposure to the dubbed Turkish series since it is evident that almost three-fourths of the study individuals watch the dubbed Turkish series,.”. The most significant positive aspects of the dubbed Turkish series are: “they focus on the most important tourist attractions in Turkey” and “ improving the audience›s knowledge and information on the traditions of the Turkish society”. The most apparent

أن التقدم والتطور العلمي اللذين حدثا خلال القرن العشرين كان لهما اثر كبير في المسيرة العلمية ، حيث أن من المفترض على أفراد مجتمع المتعلمين أن يتزودوا بمهارات التفكير العلمي لكي تمكنهم من العيش في العصر الحالي وليشاركوا فيه بذكاء وفاعلية حتى يحققوا لذاتهم ملائمة أفضل مع التغييرات والتطورات المختلفة التي حدثت في العالم لذا فان طرائق التدريس أصبحت حاجة ملحة لا تقل أهميتها عن المدرس والمادة الدراسية حيث أ

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu