In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using  the simulation.

After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph

Background: Esthetic correction represents one of the clinical conditions that required the use of laminate veneers in premolars region. Aim of the study: The purpose of this study was to evaluate the fracture strength of the laminate veneers in maxillary first premolars, fabricated from either composite (direct and indirect techniques) or ceramic CAD/CAM blocks. Materials and Methods: Fifty sound human maxillary premolar teeth were used in this in vitro study. Teeth were divided randomly into one control group and four experimental groups of ten teeth each; Group A: Restored with direct composite veneer (Filtek Z250 XT), Group B: Restored with indirect composite veneers (Filtek Z250 XT), Group C: Restored with lithium disilicate ceramic CA

Light has already becomes a popular means of communication, and the high-bandwidth data into free space without the use of wires. A great idea took us to design a new system for transmitting sound through free space at (650, 532) nm wavelengths using reflective mirrors under different atmospheric conditions. The study showed us the effect of various weather factors (temperature, wind speed and humidity) on these wavelengths for different distances. As well as studying the attenuation caused by long-distance laser and beam divergence, A reflective dish was used to focus the spot of the laser beam on the photocell. Results were discussed under the effect of these factors and the attenuation resulting from the beam divergence. Thus, the sys

Background: The aims of the study were to evaluate the unclean/clean root canal surface areas with a histopathological cross section view of the root canal and the isthmus and to evaluate the efficiency of instrumentation to the isthmus using different rotary instrumentation techniques. Materials and Methods:The mesial roots of thirty human mandibular molars were divided into six groups, each group was composed of five roots (10 root canals)which prepared and irrigated as: Group one A: Protaper system to size F2 and hypodermic syringe, Group one B: Protaper system to size F2 and endoactivator system, Group two A:Wave One small then primary file and hypodermic syringe, Group two B:Wave One small then primary file and endoactivator system, Gr

Finding the shortest route in wireless mesh networks is an important aspect. Many techniques are used to solve this problem like dynamic programming, evolutionary algorithms, weighted-sum techniques, and others. In this paper, we use dynamic programming techniques to find the shortest path in wireless mesh networks due to their generality, reduction of complexity and facilitation of numerical computation, simplicity in incorporating constraints, and their onformity to the stochastic nature of some problems. The routing problem is a multi-objective optimization problem with some constraints such as path capacity and end-to-end delay. Single-constraint routing problems and solutions using Dijkstra, Bellman-Ford, and Floyd-Warshall algorith

The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app

In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables