X-ray Diffraction and Fourier Transform Analysis of Corrosive Components of Crude Oils Used by Kaduna Refinery for Corrosion Control

Kaduna refinery is a critical segment of the Nigerian economy but is subject to costly corrosion problems. The refinery obtains crude oils from various sources and processes them under peculiar conditions into essential chemical products. This research was undertaken in order to gain insight into the component proportions of the refinery’s employed crude oils that contribute to corrosion problems. The component proportions of a homogeneous admixture of the employed crudes at the refinery were analyzed using XRD and FTIR techniques. Obtained results and analysis indicate that crude oils employed at the refinery are generally significantly corrosive to most materials due to their appreciable total component contents of sulfur, carbon, idrialite, refikite, flagstaffite, and silicon dioxide up to 35%, which can be corrosive per se or can undergo reactions, especially at higher refining temperatures, to produce abundant quantities of corrosion agents that include acids, chlorides, water, carbon dioxide, hydrogen sulfide, etc

Pentagon Patch Antenna for WLAN at 2.6 GHz

In this paper an antenna with a pentagonal patch design is being prototype on FR-4 epoxy material fed by a microstrip line with a hexagonal parasitic element for bandwidth enhancement. A pentagon microstrip antenna with hexagonal  parasitic elements is designed and analyzed its properties for WLAN application at 2.52 GHz. The pentagon microstrip antenna with hexagonal parasitic element is being analyzed in terms of return loss, gain in dB and VSWR, etc. The experimental result shows a patch antenna is operating frequency at 2.52 GHz, with the return loss parameter is observed as -9.84 dB, and the VSWR ratio is < 2 respectively

Application of the EEMD Algorithm for the Monitoring of the Cutting Tool wear

In this work, it is a question of a monitoring of cutting tool wear in mechanical turning. This monitoring is carried out in three phases which correspond to the life of the tool. To achieve this objective of improving the monitoring of the cutting tool, we have proposed the EEMD processing algorithm which decomposes a large signal into small signals (IMFs) by comparing it to the EMD algorithm, which is an algorithm used in the analysis of non-linear and non-stationary signals. The phenomenon of mode mixing is one of the major drawbacks of EMD. The EEMD eliminates the mode mixing effect. The EEMD principle is to add extra white noise to the signal with a certain number of tries

Substituent analysis for accurate prediction of the acidity constants of phosphonic acids

This study aims to develop simple and reliable models to predict the pKa of phosphonic acids using empirical substituent effects descriptors. The effects of substituents on the acidity and basicity of organic acids have been examined using various approaches, such as the Taft-Topsom model. This study used linear regression methods to construct equations that predict the acidity constants of phosphonic acids. The validity of the linear regressions was confirmed through statistical analysis of parameters and residuals. However, it is essential to note that the models are limited to substituents with tabulated Taft parameters. Despite these limitations, the developed models provide a simple and effective method for estimating the acidity constants of phosphonic acids with a confidence interval greater than 95%. This study aims to analyze the effect of substituents on the dissociation of phosphonic acid and propose prediction models for new phosphonic derivative

Fault Detection Analysis in Ball Bearings using Machine Learning Techniques

The Bearing element is very essential component of any rotating equipment. Any defect in the bearings lead to instable performance of the machinery. To avoid such malfunction and breakdown of the machinery equipment due to misalignment is review critically in this research paper and various machine learning techniques to tackle the issue is highlighted. This review article finds the basis for developing an effective system in order to reduce the breakdown of machinery or equipment. Conventional Machine Learning methods, like Artificial neural network, Decision Tree, Random Forest, Support Vector Machines(SVM) have been applied to detecting categorizing fault, while the application of Deep Learning methods has ignited great interest in the industry

Behavior of Masonry Walls with Respect to Seismic Stress, Analysis and Recommendation

Structures with masonry infill panels and reinforced concrete frame are widely used structural systems and by lack of knowledge considered secondary, masonry infill walls are considered until now as non-load-bearing elements, therefore the role of taking and transmitting vertical and horizontal loads (seismic)  is  ensured  only  by  the  reinforced  concrete  structure.  However, experience from past earthquakes around the world has shown that this calculation approach is simplifying and approximate, because we have found during the analysis of earthquake damage that the neglect of masonry walls in calculations can decisively influence and even upset the response of structures to seismic forces. The tests carried out in our research and the numerical modelling carried out on several cases have shown that the effect of shear stress on gantry masonry structures can be taken into account by replacing in the numerical modelling the masonry with equivalent diagonals  whose  thickness  will  be  calculated  according  to  the  physical  and mechanical characteristics of the gantry and the masonry

Design and Development of a Low-Cost Multi-Channel Re-Programmable Electro-Pneumatic Actuator Kit

The objective of the research was to develop a low-cost, multi-channel electro-pneumatic actuator kit that would be conveniently accessible for students' learning experiences, trainings, and research at the individual and academic level. The essential feature of this kit was the inclusion of multi-channel outputs, which implies that the student may not only examine the behavior of basic pneumatic actuators but also train their minds to operate complicated actuation systems. With this electro-pneumatic actuation kit, a student can build and utilize it in a variety of research areas, as well as regulate a system synchronously or asynchronously with greater efficiency. The device is portable, inexpensive, and simple to use. It has a power source of 12 VDC for the electrical circuit and can provide a maximum pressure of 90 kPa as well as vacuum of -40 kPa. Relays were being integrated to satisfy the smooth automation of the kit. It features the MPX700 differential pressure sensor, which allows the user to measure and manage the needed pressure. All of the components were controlled by the Arduino Board, which is affordable and can be programmed to do the required function. With this research, academic institutions will be able to create their own kits for their students, allowing them to discover numerous new inventive concepts

Light and its usefulness in astronomy

Light has numerous uses in several areas of research and this work aims to show the importance of its usefulness particularly in the field of astronomy. Initially, humanity had a way of measuring celestial objects and with technological advancement and in-depth studies of light itself, its ability to transmit data is observed, which are key factors for analyzing and controlling the dynamics of the universe and its constituent elements. The work emphasizes the structure of light in terms of its spectrum, as well as favoring astronomy in data collection through the use of tools, such as optical fibers and spectroscopy

An Efficient Logarithmic Ratio Type Estimator of Finite Population Mean under Simple Random Sampling

The use of auxiliary information has become indispensable for improving the exact of estimators of population parameters like the mean and variance of the variable under study. A great variety of the techniques such as the ratio, product, and regression methods of estimation are commonly known in this esteem. In this paper, we propose an efficient logarithmic ratio type estimator for finite population mean estimation under simple random sampling. The expression for the bias and mean squared error (MSE) of the proposed estimator is obtained up to the first order of approximation. The conditions under which the proposed estimator is more efficient than the existing ones are established. An empirical study using three data sets is also conducted to validate the theoretical findings and the results revealed that the suggested estimator is better than the existing estimators considered in the study

Empowering Flexible Learning: The Role of Embedded Systems in Remote Laboratories

This paper explores developing and implementing a practical work remote control operational architecture using embedded systems. This architecture is particularly relevant to electronics university courses, offering innovative approaches to low-cost remote laboratories. Students through the university’s local network at their convenience, providing a more flexible learning approach compared to traditional fixed schedules, can access these virtual labs. This strategy addresses the challenges posed by the high number of enrollees in Moroccan Faculties, especially in open-access institutions.The study presents a detailed examination of this prototype's hardware and software components, with the potential for application across various disciplines. The hardware element comprises an Arduino microcontroller, responsible for managing electronic experiments involving a single-phase rectifier, chosen as an illustrative example of remote-controlled manipulation.To evaluate the efficacy of this educational system, it underwent testing by students in the field of electronics and industrial systems. The outcomes of this evaluation highlight the numerous advantages of this innovation