Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

The piled raft is a geotechnical composite construction consisting of three elements: piles, raft and soil.
In the design of piled rafts, the load shared between the piles and the raft, and the piles are used up to a
load level that can be of the same order of magnitude as the bearing capacity of a comparable single
pile or even greater. Therefore, the piled raft foundation allows reduction of settlements in a very
economic way as compared to traditional foundation concepts.
This paper presents experimental study to investigate the behavior of piled raft system in sandy
soil. A small scale “prototype” model was tested in a sand box with load applied to the system through
a compression machine. The settlement was

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

Hydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil at dif

This paper focuses on the optimization of drilling parameters by utilizing “Taguchi method” to obtain the minimum surface roughness. Nine drilling experiments were performed on Al 5050 alloy using high speed steel twist drills. Three drilling parameters (feed rates, cutting speeds, and cutting tools) were used as control factors, and L9 (3³) “orthogonal array” was specified for the experimental trials. Signal to Noise (S/N) Ratio and “Analysis of Variance” (ANOVA) were utilized to set the optimum control factors which minimized the surface roughness. The results were tested with the aid of statistical software package MINITAB-17. After the experimental trails, the tool diameter was found as the most important facto

This study was conducted in a laboratory experiment at the University of Baghdad, College of Science, computing Department, 5 km from the center of Baghdad city, in 2021 to evaluate the sorting method for the tomato crop. The experiments were conducted in a factorial experiment under a complete randomized design with three replications and using SAS analysis, artificial neural network, image processing, the study of external characteristics, and physical features; fruit surface area and fruit circumference were 1334.46 cm2,57.53 cm2 and free diseases. The error value was less than zero, while training with outputs recorded the highest value and which was 5. The neural network's performance between the input and the mean square of th

In this paper, the solar attraction effect on the Moon orbital elements had been studied. The solar attraction considered a third body perturbation. The initial values of the Moon orbital elements at 2015-1-21.5 which are used (semi major axis=380963.78 km, eccentricity =0.056o, Eular angles (Ω=30°, ω=40°, , i=18.4°). The Moon in a perigee of its orbit at the initial time. A program which designed, was used to calculate the Moon position ,velocity and orbital elements through the years (2015-2035). The position and velocity components of the Moon were calculated by solving the equation of Kepler for elliptical orbit using Newton Raphson's method for (1000) periods and hundred steps of time for each period. The results show a secular

The archaeological and religious sites play a prominent role in the rest of the other tourist activities as cultural and spiritual needs that can not be dispensed with. Archaeological sites represent cultural origins of the nation. Religious sites represent the state of man's orientation to God in places of worship . The focus was on the city of Babylon because it is an ancient city and tourist because of its characteristics and elements. The importance of the city of Babylon is illustrated by highlighting its archeological and religious status through its geographical distribution. This gives the subject special importance for the purpose of knowing the city's important sites. And come out with a number of results and a set of recommend

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm