Although its wide utilization in microbial cultures, the one factor-at-a-time method, failed to find the true optimum, this is due to the interaction between optimized parameters which is not taken into account. Therefore, in order to find the true optimum conditions, it is necessary to repeat the one factor-at-a-time method in many sequential experimental runs, which is extremely time-consuming and expensive for many variables. This work is an attempt to enhance bioactive yellow pigment production by Streptomyces thinghirensis based on a statistical design. The yellow pigment demonstrated inhibitory effects against Escherichia coli and Staphylococcus aureus and was characterized by UV-vis spectroscopy which showed lambda maximum of

Carbonized nonwoven nanofibers composite were fabricated using the electrospinning method of a polymeric solution composite followed by heat treatment including stabilization and calcination steps. The spun polymeric solution was a binary polymer mixture/organic solvent. In this study, two types of polymers (Polymethylmethacrylate (PMMA) and Polyethylene glycol (PEG)) were used separately as a copolymer with the base polymer (Polyacrylonitrile (PAN)) to prepare a binary polymer mixture in a mixing ratio of 50:50. The prepared precursor solutions were used to prepare the precursor nanofibers composite (PAN: PMMA) and (PAN: PEG).  The fabricated precursors nonwoven fibers composite were stabilized and carbonized to produce carbon nonw

Skills learning is considered as an important factor in learning any subject as well as mathematics . Mathematical skills have a number of steps that should be learned and understood faster and with more accuracy . The practical or applied skills are type of learning which includes educational preparation and hand on skills is acquired which conducted by organized educational institutions. The sample included (120) students (males and females) first year / dept.of electrical technigues . The mathematical skills are implemented to wire up the electrical circuts. Test is implemented with questions concerned with the skills .statistical operations were conducted as well as the validity and standard deviation for the test .The results showed

In this work was prepared three different types of modified screen printed carbon electrode (SPCEs) with drops casted method, the used carbone nanomaterials were the MWCNT, functionalized –MWCNT (f-MWCNT) and After several experiments were made to find an appropriate ratio to make good GOT/f-MWCNT nanocomposite, and found the suspension mixture (1:1) from GOT/f-MWCNT (f-MWCNT-GOT). The electrical and physical properties were performed with cyclic voltammeter technique, and studied the maximum current response, the effective surface area, effect of the pH value and the determination of active surface area for MWCNT-SPCE , f-MWCNT-SPCE and f-MWCNT-GOT/SPCE as (0.04 cm2), (0.119 cm2) and (0.115 cm2) respectively, the surface coverage concent

DC planar sputtering system is characterized by varying discharge potential of (250-2000 volt) and Argon gas pressures of (3.5×10-2 – 1.5) mbar. The breakdown voltage for silver electrode was studied with a uniform electric field at different discharge distances, as well as plasma parameters. The breakdown voltage is a product of the Argon gas pressure inside the chamber and gab distance between the electrodes, represent as Paschen curve. The Current-voltage characteristics curves indicate that the electrical discharge plasma is working in the abnormal glow region. Plasma parameters were found from the current-voltage characteristics of a single probe positioned at the inter-cathode space. Typical values of the electron temperature an

Ag₂O (Silver Oxide) is an important p-type (in chasm to most oxides which were n-type), with a high conductivity semiconductor. From the optical absorbance data, the energy gap value of the Ag₂O thin films was 1.93 eV, where this value substantially depends on the production method, vacuum evaporation of silver, and optical properties of Ag₂O thin films are also affected by the precipitation conditions. The n-type and p-type silicon substrates were used  with porous silicon wafers to precipitate  ±125 nm, as thick Ag₂O thin film by thermal evaporation techniques in vacuum and via rapid thermal oxidation of 400^oC and oxidation time 95 s, then characterized by measurement of

Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials

Abstract
An optoelectronic system for fog detection and visibility technique is presented .The idea of this research is based on the measurement of the atmospheric visibility by using an infrared beam emitter from LED diode. The optical scattering is used as a method to calculate the visibility. This method is applied at forward scattering within a foggy atmosphere, which is modern and has great importance for measuring visibility in seaports, airports, public roads and highways. In this paper we focus on the description of the system, principles of its operation and some results of field tests.
Keywords: fog sensor, visibility sensor, backscattering, forward scattering.

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog