In this paper, the Mars orbital elements were calculated. These orbital elements—the major axis, the inclination (i), the longitude of the ascending node (W), the argument of the perigee (w), and the eccentricity (e)—are essential to knowing the size and shape of Mars' orbit. The quick basic program was used to calculate the orbital elements and distance of Mars from the Earth from 25/5/1950 over 10000 days. These were calculated using the empirical formula of Meeus, which depended on the Julian date, which slightly changed for 10000 days; Kepler's equation was solved to find Mars' position and its distance from the Sun. The ecliptic and equatorial coordinates of Mars were calculated. The distance between Mars and the center of the E

Background: Osteoporosis is a systemic skeletal disorder affects general health in addition to effect on salivary physical and chemical composition which lead to an adverse effect on oral health status. This study was conducted to evaluate the concentration of glycoprotein (osteonectin) in saliva and its effect on dental caries in relation to salivary flow rate and viscosity among osteoporotic women and compared to control group. Materials and Methods: The total sample composed of 60 females aged 60-65 years attending Al-Yarmook Teaching Hospital, 30 females diagnosed with osteoporosis by measuring bone density at the spine and femur with a dual-energy X-ray absorptiometry at T-score of >2.5, and 30 women without osteoporosis with T-score o

<p> Traditionally, wireless networks and optical fiber Networks are independent of each other. Wireless networks are designed to meet specific service requirements, while dealing with weak physical transmission, and maximize system resources to ensure cost effectiveness and satisfaction for the end user. In optical fiber networks, on the other hand, search efforts instead concentrated on simple low-cost, future-proofness against inheritance and high services and applications through optical transparency. The ultimate goal of providing access to information when needed, was considered significantly. Whatever form it is required, not only increases the requirement sees technology convergence of wireless and optical networks but

Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The

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,

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

The study deals with China's soft power and diplomacy in the Middle East, and it focuses specifically on the tools and foundations of China's soft diplomacy and how it achieves its goals in the region in addition to its challenges in the region. In this regard, the study also focuses on the Chinese Belt and Road Initiative and its soft foundations and how they serve China’s diplomacy and soft power in the region. The study ends with a set of conclusions, perhaps the most prominent of which is that diplomacy and soft power have become a fundamental pillar of China's foreign policy to achieve its foreign goals and to establish an international system compatible with China's principles. As for the Middle East, China has established a poli

              -convex sets and -convex functions, which are considered as an important class of generalized convex sets and convex functions, have been introduced and studied by Youness [5] and other researchers. This class has recently extended, by Youness, to strongly -convex sets and strongly -convex functions. In these generalized classes, the definitions of the classical convex sets and convex functions are relaxed and introduced with respect to a mapping . In this paper, new properties of strongly -convex sets are presented. We define strongly -convex hull, strongly -convex cone, and strongly -convex cone hull and we proof some of their properties.  Some examples to illustrate the aforementioned concepts and to cl

An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co