This research includes problems that facing the philosophy of education in the variables of knowledge and Informatics society (techno _ social).

 The problematic research included three questions:

 1- What are the concepts and characterization related to the problematic of relationship between the philosophy of education and informatics variables (techno - social).

2-What kind of problems facing speech philosophy of education in the variables information (techno - social)

  3 - What are the perceptions of educational proposed to address problematic philosophy of education in the scope of human (human nature) and (values ​​and morals), in addition the research may explain the co

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

In this work, the antibacterial effectiveness of face masks made from polypropylene, against Candida albicans and Pseudomonas aeruginosa pathogenic was improved by soaking in gold nanoparticles suspension prepared by a one-step precipitation method. The fabricated nanoparticles at different concentrations were characterized by UV-visible absorption and showed a broad surface Plasmon band at around 520 nm. The FE-SEM images showed the polypropylene fibres highly attached with the spherical AuNPs of diameters around 25 nm over the surfaces of the soaked fibres. The Fourier Transform Infrared Spectroscopy (FTIR) of pure and treated face masks in AuNPs conform to the characteristics bands for the polypropylene bands. There are some differences

Sulphated zirconia (SZ) is one of the most important solid acid catalysts was synthesize at different operating conditions, different calcination temperature and sulfonating time has been used. The prepared catalyst was distinguished by X-ray Diffraction (XRD), particle size and morphology of catalyst were checked by atomic force microscopy (AFM) and scanning electron microscopy (SEM) respectively, in addition to analysis by (DTA) Differential thermally and Energy Dispersive X-Ray (EDX). Finally, the N2 adsorption-desorption was used to measure the surface area (BET) and pore volume. High degree of tetragonal crystallinity was obtained 90 %, and surface area of 169 m2/g and pore volume of 0.39 cm3g-1 at 600°C calcination temperature for 3

Semi-active suspension systems have emerged as an attractive alternative to fully active suspensions because they offer a superior capacity to improve vehicle ride comfort and handling performance with significantly lower energy consumption. Conventional semi-active control strategies, however, such as skyhook damping, often cannot accommodate the nonlinear and time-varying dynamics of vehicles in operation under impulse or severe road disturbances. In this context, an intelligent smart-damper controller is proposed in this paper by incorporating a Modified Fuzzy Adaptive Fuzzy Logic Control framework in a half-car suspension model. In the developed controller, the effective damping force is adaptively tuned using real-time measurements of

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that