With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

Cities have witnessed great changes since the planning of the first cities. This is due to the increase in population and problems in services that affect urban security. As such, urban security is directed and affected by the nature of city planning and the types of services. Besides, the kind of services plays an imminent place in providing urban security at all levels. Other factors that influence urban security can be limited to the increase of population, economic and social changes. This leads to losing urban control. This study will explore the historical chronology to identify weaknesses in urban planning since its dawn and reaching solutions to protect urban security. The importance of the research lies in achieving urban securi

Cities have witnessed great changes since the planning of the first cities. This is due to the increase in population and problems in services which affect urban security. As such, urban security is directed and affected by the nature of city planning and the types of services. Besides, the kind of services plays an imminent place in providing urban security at all levels. Other factors that influence urban security can be limited to the increase of population, economic and social changes. This leads to losing urban control. This study will explore the historical chronology to identify weaknesses in urban planning since its dawn and reaching solutions to protect urban security. The importance of the research lies in achieving urban secur

The buildup factor of cylindrical samples (shields) for Brass, Copper & lead (Brass, Cu, Pb (was studied, where buildup factor were calculated with thickness between (0-12) m.f.p. for Co60 and Cs137sources with activities (30) & (41) MBq respectively , using scintillation detector NaI(T?) with (3"×3")volume .The results shows increases of buildup factor for low atomic number(Z) samples where the energy of radiation source was constant, also shows increases of buildup factor with decreases the energy of radiation source. An empirical equation was obtained using Matlab7 program this equation have agreements with most obtained data for 96%.

Internal conversion coefficients (ICC) and electron–positron pair conversion coefficients (PCC) for multipole transition of the core nucleus 88Sr have been calculated theoretically. The calculation is based on the relativistic Dirac–Fock (DF) solutions using the so called ‘‘Frozen Orbital’’ approximation, takes into account the effect of atomic vacancies created in the conversion process, covering a transition energies of 1–5000 keV. A large number of points were used to minimize any errors due to mesh-size effects. The internal conversion coefficients display a smooth monotonic dependence on transition energy, multipolarity and atomic shell. Comparing the values of PCC to ICC, it is interesting to note, that the energy dep

لا شك أن الموسيقى هي أقدر الفنون على خدمة الإنسان، وهي أرقى أنواع منشطات الحياة والصحة النفسية والعضوية، فالصحة النفسية والعضوية هي تناسق الشيء مع كل شيء الخلية مع الخلايا، والروح مع الأرواح، والإنسان مع الكون، كما تتناسق النغمة مع النغمات، والآلة مع الآلات .

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se