The magnetic properties of a pure Nickel metal and Nickel-Zinc-Manganese ferrites having the chemical formula Ni_0.1(Zn_0.4Mn_0.6)_0.9Fe₂O₄ were studied. The phase formation and crystal structure was studied by using x-ray diffraction which confirmed the formation of pure single spinel cubic phase with space group (Fd3m) in the ferrite. The samples microstructure was studied with scanning electron microstructure and EDX. The magnetic properties of the ferrite and nickel metal were characterized by using a laboratory setup with a magnetic field in the range from 0-500 G. The ferrite showed perfect soft spinel phase behavior while the nickel sample showed higher magnetic loss an

Magnetic Abrasive Finishing (MAF) is an advanced finishing method, which improves the quality of surfaces and performance of the products. The finishing technology for flat surfaces by MAF method is very economical in manufacturing fields an electromagnetic inductor was designed and manufactured for flat surface finishing formed in vertical milling machine. Magnetic abrasive powder was also produced under controlled condition. There are various parameters, such as the coil current, working gap, the volume of powder portion and feed rate, that are known to have a large impact on surface quality. This paper describes how Taguchi design of experiments is applied to find out important parameters influencing the surface quality generated during

The effect of the magnetic abrasive finishing (MAF) method on the temperature rise (TR), and material removal rate (MRR) has been investigated in this paper. Sixteen runs were to determine the optimum temperature in the contact area (between the abrasive powder and surface of workpiece) and the MRR according to Taguchi orthogonal array (OA). Four variable technological parameters (cutting speed, finishing time, working gap, and the current in the inductor) with four levels for each parameter were used, the matrix is known as a L16 (4⁴) OA. The signal to noise ratio (S/N) ratio and analysis of the variance (ANOVA) were utilized to analyze the results using (MINITAB17) to find the optimum condition and identify the significant p

In this paper, a theoretical study of the energy spectra and the heat capacity of one electron quantum dot with Gaussian Confinement in an external magnetic field are presented. Using the exact diagonalization technique, the Hamiltonian of the Gaussian Quantum Dot (GQD) including the electron spin is solved. All the elements in the energy matrix are found in closed form. The eigenenergies of the electron were displayed as a function of magnetic field, Gaussian confinement potential depth and quantum dot size. Explanations to the behavior of the quantum dot heat capacity curve, as a function of external applied magnetic field and temperature, are presented.

This study evaluates the performance of magnetic abrasive finishing (MAF) of aluminum alloy in terms of achieving materials removal (MR). A vertical milling machine is used to perform the finishing process using a developed MAF unit that consists of an inductor made out of a 150 mm long and 20 mm diameter iron core wound with 1500 turns and 0.5 mm copper wire. The commutator and magnetic pole are attached at the top and bottom of the inductor, respectively. The required current is supplied using a DC power supply. The South Pole workpiece is a 100×50×3 mm³ plate of AA 1100 aluminum alloy, whereas the magnetic pole represented the North Pole. Pole rotational speed, applied current, and abrasive finishing time was selected as

We have studied the effect of applying an external magnetic field on the characteristics of iron oxide (IO) nanoparticles (NPs) synthesized by pulsed laser ablation in dimethylformamide (DMF). The NPs synthesized with and without applying of magnetic field were characterized by Fourier transformation infrared spectroscopy (FT-IR), UV–Vis absorption, scanning electron microscope (SEM), atomic force microscope (AFM), and X-ray diffraction (XRD). SEM results confirmed that the particle size was decreased after applying magnetic field.

In recent years, the steady stream of artificial intelligence into economic systems has become a torrent. It is changing how we generate wealth and grow anew. Manufacturing, finance, health care energy, agriculture and education are just a few of the areas where AI may result in dramatic increases in productivity as well as innovation and sustainability. Predictive analytics, AI, robotics and natural language processing have significantly contributed in the improvement of resource allocation mechanisms and decision making as well as reaching SDGs. The concept of Artificial Humanity is also introduced in the paper. It shows how AI could become a global cognitive network to foster knowledge. By comparison and references of the literature, thi

Wireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB8

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi