In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compared to traditional image filtering techniques. This paper aimed to utilize a specific CNN architecture known as AlexNet for the fingerprint-matching task. Using such an architecture, this study has extracted the significant features of the fingerprint image, generated a key based on such a biometric feature of the image, and stored it in a reference database. Then, using Cosine similarity and Hamming Distance measures, the testing fingerprints have been matched with a reference. Using the FVC2002 database, the proposed method showed a False Acceptance Rate (FAR) of 2.09% and a False Rejection Rate (FRR) of 2.81%. Comparing these results against other studies that utilized traditional approaches such as the Fuzzy Vault has demonstrated the efficacy of CNN in terms of fingerprint matching. It is also emphasizing the usefulness of using Cosine similarity and Hamming Distance in terms of matching.
Value Engineering is an analytical study on projects or services using a specific procedure and a multidisciplinary working group, works for the identification and classification of the project functions; either for a better perfuming of these functions or to lessen the total project cost or the two together. Value Engineering main aim is on finding innovative alternatives, without effecting the basic requirements of the project, its methodology based on the functional balancing between the three elements of production "performance, quality and cost". This methodology based on the "functional analysis", had shown high possibilities in solving any problem facing the production procedure , achieve better investment for available re
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
The minimum approaches distance of probing electrons in scanning electron microscope has investigated in accordance to mirror effect phenomenon. The analytical expression for such distance is decomposed using the binomial expansion. With aid of resulted expansion, the distribution of trapped electrons within the sample surface has explored. Results have shown that trapped electron distributes with various forms rather an individual one. The domination of any shape is mainly depend on the minimum approaches distance of probing electrons
Objective: Assess type 2 diabetic patients’ knowledge regarding preventive measures of diabetic foot. Find out the relationship between of type 2 diabetic patients’ knowledge regarding preventive measures of diabetic foot with certain sociodemographic characteristics
Methodology: A descriptive study was carried out from (2nd January 2022 to 26th March 2022). A non –probability (purposive) sample of (60) adult patients who are diagnosed with type2 diabetes mellitus these patients have met the study criteria which was selected from Imam AL-Hussein Medical-City. The study instrument consist of two section: (Demographic Information Sheet, and Foot Care Outcome Expectation
... Show MoreIncreased attention to corporate governance with the increasing need for investors and other parties in the Iraqi market for securities of the information credible and confidence and greater transparency in the disclosure as well as the systems of governance lead to raise the value of the company and that by reducing the cost of capital and reduce the cost of financing, as well as that there are indications modern measurement can be adopted by the Iraqi market for securities for the purpose of evaluating the performance of listed companies and then raise their value.
The research problem is that there is no framework or structure of the legal and local rules for the application of corporate governance in Iraq obliges
... Show MoreBackground: Analysis of human reports and comparison with results of experimental animals indicate that the effects of progesterone on human not analogous to experimental animals fetus, many studies showed that exposure to progesterone during developing of genital tract of human fetus was not teratogenic. Other studies which performed on laboratory animals found association between progesterone administration during gestation and genital malformation. Objectives: to explore the effect of progesterone in 10.2 mg/kg intraperitoneal injection in mice on testis development and anogenital distance. Materials and Methods: ten pregnant mice divided into five mouse control group that injected10. 2mg/kg sesame oil and treated group that injected pro
... Show MoreAmong the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the
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