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

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

In the present study, an attempt has been to develop a new water quality index (WQI) method that depends on the Iraqi specifications for drinking water (IQS 417, 2009) to assess the validity of the Euphrates River for drinking by classifying the quality of the river water at different stations along its entire reach inside the Iraqi lands. The proposed classifications by this method are: Excellent, Good, Acceptable, Poor, and Very poor. Eight water quality parameters have been selected to represent the quality of the river water these are: Ion Hydrogen Concentration (pH), Calcium (Ca), Magnesium (Mg), Sodium (Na), Chloride (Cl), Sulphate (SO_4), Nitrate (NO_3), and Total Dissolved Solids (TDS). The variation of the water quality parameters

Field experiment was conducted by using two fertilization systems (i.e.) biofertilizers (inoculation with Pseudomonas putida and with Azotobacter chroococcum and non - inoculation) and chemical fertilization (100%, 50% and 25% of recommended by Ministry of Agriculture) to study the influence of these system and interaction on water and grain yield productivity, some growth phytohorones and number of bacterial cells in soil rizosphere of root of wheat crop under water scarcity. The result showed that the integrate fertilization (inoculation with Pseudomonas putida and Azotobacter chroococcum bacterial + 50% of the recommended chemical fertilizer) recorded 5.70 and 5.55 t ha^-1, respectively with reducing the chemical fertilizer app

Pots experiment was conducted at the greenhouse of botanical garden belong to Department of Biology, College of Education for Pure Science, Ibn-AL-Haithum, University of Baghdad, for growth season 2018-2019. The aim of the experiment was to study the effects of foliar application of a-tocopherol concentrations (0, 50, 100, 150, 200 mg.L-1) on growth parameters and the activity of some antioxidant enzymes of wheat plant irrigated with sodium chloride concentrations (0, 75, 150, 225) mM.L-1. Salinity reduced plant growth parameter, plant height, flag leaf area, flag leaf chlorophyll content and increased the activity of antioxidant enzymes, superoxide dismutase and peroxidase. Plant growth parameters were enhanced by foliar application of a-t

The agricultural lands that depend on supplementary irrigation methods for winter wheat cultivating in wide areas of the Nineveh province are most vulnerable to climate change concerns. Due to frequent rainfall shortages and the temperature increase recently noticed and predicted by the climate scenarios. Hence important to assess the climate effect on the crop response in terms of water consumption during the periods (2021-2040) and (2041-2060) by using high-resolution data extracted from 6 global climate data GCMs under SSP5-8.5 fossil fuel emission scenarios in changing and fixed CO₂ concentration. And validate the Aqua-Crop model to estimate the yield and water productivity. And gives the RRSME of 7.1- 4.1

Estimation of trip attraction and analyzing its main influencing factors are powerful for offering different classifications for business districts and presenting recommendations for improving attractiveness in long term. This is beneficial for designing transportation facilities and infrastructures. The paper presents the prediction of trip attraction using an artificial intelligence technology due to the profits that the technology can possess in shortening time, lowering expenses and saving effort. The new model has utilized six input parameters that have not been considered previously within the area of Nasiriyah city including; age and educational level of the passengers, mode of transport that the passengers use, purpose of the trip,