The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

Today many people suffering from health problems like dysfunction in lungs and cardiac. These problems often require surveillance and follow up to save a patient's health, besides control diseases before progression. For that, this work has been proposed to design and developed a remote patient surveillance system, which deals with 4 medical signs (temperature, SPO2, heart rate, and Electrocardiogram ECG. An adaptive filter has been used to remove any noise from the signal, also, a simple and fast search algorithm has been designed to find the features of  ECG signal such as Q,R,S, and T waves.  The system performs analysis for medical signs that are used to detected abnormal values. Besides, it sends data to the Base-Stati

Cryptography is a major concern in communication systems. IoE technology is a new trend of smart systems based on various constrained devices. Lightweight cryptographic algorithms are mainly solved the most security concern of constrained devices and IoE systems. On the other hand, most lightweight algorithms are suffering from the trade-off between complexity and performance. Moreover, the strength of the cryptosystems, including the speed of the algorithm and the complexity of the system against the cryptanalysis. A chaotic system is based on nonlinear dynamic equations that are sensitive to initial conditions and produce high randomness which is a good choice for cryptosystems. In this work, we proposed a new five-dimensional of a chaoti

This study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subj

         The essence of the new work in the satellite TV channels is to provide news coverage of news that will inform the people of what is going on around them in order to increase their political, social, economic and cultural awareness and this drives them to take positions or certain behaviors on according to what the communicator in these channels wants. News and news reports are generally used as a psychological variable to influence public opinion and does not offer interestingness and information. Therefore, satellite TV channels have assumed special attention towards their correspondents desiring to achieve scoop in news coverage and to have the final word in reading events and install it

Background Many antidiabetic medications with distinct modes of action are available, The sodium glucose cotransporter-2 (SGLT-2) inhibitors are among the most recent oral antihyperglycemic medications. The American Diabetes Association recommends metformin, a biguanide medication, as the first option for oral control of type 2 diabetes because it has demonstrated promise in this regard. Aim of the study To evaluate and compare the effects of metformin and SGLT-2 inhibitors on general urine parameters in T2DM patients from Iraq. Method a prospective cohort study where 101 adult patients of both sexes aged under 70 years and newly diagnosed with T2DM, patients were divided into two groups, Metformin group (n=52), where metformin was p

The research aims to get acquainted with the evaluation of the reality of the application of the curriculum axis from among the eight Iraqi academic accreditation standards in a sample of governmental and private universities and colleges in Iraq and to identify the main and secondary reasons for it as well as to provide proposed mechanisms and procedures to help reduce gaps, If the research problem is represented in the weak availability of the requirements of the curriculum axis in universities and colleges (the study sample) due to the weak documentation and successful implementation of them and interest in them is still below the level of ambition, In order to arrive at scientific facts, the researchers adopted the comparativ

Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor