Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

<p>Photovoltaic (PV) systems are becoming increasingly popular; however, arc faults on the direct current (DC) side are becoming more widespread as a result of the effects of aging as well as the trend toward higher DC voltage levels, posing severe risk to human safety and system stability. The parallel arc faults present higher level of current as compared with the series arc faults, making it more difficult to spot the series arc. In this paper and for the aim of condition monitoring, the features of a DC series arc fault are analyzed by analysing the arc features, performing model’s simulation in PSCAD, and carrying out experimental studies. Various arc models are simulated and investigated; for low current arcs, the heur

The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio

In her poetry, Carol Ann Duffy looks into the concerns of the disregarded and humiliated people. Approaching facts fearlessly and disclosing realities in a way highly characteristic of her, she establishes the world newly and reframes it honestly. This research shows how Duffy reframes the world in her own peculiar terms, starting with her own creative use of the language, in particular, when the forms of things of the world are distorted, thus our perception of things will be reframed too.
As regards relations among people, the research elucidates how Duffy’s strained characters abandon real life and reframe an eccentric way of living, while respecting faith, wherein Duffy notices that religious rituals confine the intellect, she r

A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

Heuristic approaches are traditionally applied to find the optimal size and optimal location of Flexible AC Transmission Systems (FACTS) devices in power systems. Genetic Algorithm (GA) technique has been applied to solve power engineering optimization problems giving better results than classical methods. This paper shows the application of GA for optimal sizing and allocation of a Static Compensator (STATCOM) in a power system. STATCOM devices used to increase transmission systems capacity and enhance voltage stability by regulate the voltages at its terminal by controlling the amount of reactive power injected into or absorbed from the power system. IEEE 5-bus standard system is used as an example to illustrate the te

Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.

This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.

The Mishrif formation was

 

            This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.