Abstract:Two-dimensional crystal has been achieved and controlled with the aid of DC electric field applied between two electrodes at 5 millimeters separating distance between them. Sol-gel method has been used to prepared nanosilica particle which used in this work as well as TiO2 nanopaowder. The assembly of the silica particles is due to the interaction between the electrical force, the particles dipole, and the interaction between the particles themselves. When a DC voltage is applied, the particles accumulated and crystallized on the surface between the electrodes. The Light diffraction demonstrates that the hexagonal crystal is always oriented with one axis along the direction of the field. The particles disassemble when the field is

This investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

In this study, plain concrete simply supported beams subjected to two points loading were analyzed for the flexure. The numerical model of the beam was constructed in the meso-scale representation of concrete as a two phasic material (aggregate, and mortar). The fracture process of the concrete beams under loading was investigated in the laboratory as well as by the numerical models. The Extended Finite Element Method (XFEM) was employed for the treatment of the discontinuities that appeared during the fracture process in concrete. Finite element method with the feature standard/explicitlywas utilized for the numerical analysis. Aggregate particles were assumedof elliptic shape. Other properties such as grading and sizes of the aggr

AlPO4 solid acid catalyst was prepared in order to use it in transesterification reaction of edible oil after supporting it with tungsten oxide. The maximum conversion of edible oil was obtained 78.78% at catalyst concentration (5gm.), temperature 70°Ϲ, 30/1 methanol/edible oil molar ratio, and time 5hr. The study of kinetics of the transesterification reaction of edible oil indicates that the reaction has an order of 3/2, while the value of activation energy for  transesterification reaction is 51.367 kJ/mole and frequency factor equal 26219.13(L/ mol.minute).

This review investigates the practice and influence of chatbots and ChatGPT as employable tools in writing for scientific academic purposes. A primary collection of 150 articles was gathered from academic databases, but it was systematically chosen and refined to include 30 studies that focused on the use of ChatGPT and chatbot technology in academic writing contexts. Chatbots and ChatGPT in writing enhancement, support for student learning at higher education institutions, scientific and medical writing, and the evolution of research and academic publishing are some of the topics covered in the reviewed literature. The review finds these tools helpful, with their greatest advantages being in areas such as structuring writings, gram

This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result