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

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the

Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parall

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho

Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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

This study was aimed to determine the impact of Conocarpus erectus L. compost fertilizer, and some micronutrients on growth and production of potato. This research was conducted at one of the fields of the College of Agricultural Engineering Sciences - University of Baghdad. The experiment was implemented using factorial arrangement (4X3X3) within randomized complete block design with three replicates. Conocarpus fertilizer was represented the first factor with three levels (7.5, 15, 30 ton.ha-1), which symbolized (C2, C3, C4). Chemical fertilizer as recommended dose as a control, which symbolized (C1). The second factor was foliar spraying with three levels of iron (0, 100, 200 mg.L-1), which symbolized (F0, F1, F2). The third fact

To investigate the effect of spraying some plant extraction and anti-oxidants on growth and yield of two cultivars of sunflower, a field experiment was conducted during fall season of 2009 and spring season of 2010 at the Experimental Farm, Department of Field Crop Science, College of Agriculture/ University of Baghdad. RCBD with three replications as factorial at two factors was used. First factor was cultivars Akmar and Shmoss, second was spraying with extraction of karkade at 25%, liquorices at 50%, vitamin C at concentration 1.5 mg.l-1 and nutrient which content 15 elements at concentration 15 % in addition to control treatment which sprayed with distilled water only. The result showed no significant differences between the two cultivar

The development taking place in various sports in performance, which was and still takes a large part by focusing on the specialized level of the players, whether in training or competition in all sports, including handball. In the competition (the match) by measuring the hormone beta-endorphin as well as. To identify the changes that occur in some biochemical variables as a result of the high effort in the competition (the match) by measuring lactic acid and the hormone aldosterone). The researcher used the descriptive method, the pre and post test of one group Due to the nature of the research, the research community was represented by Al-Shorta Sports players and Al-Jaish club players in handball, as they numbered (24) players from the t

              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat