The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Ever

There are two ways that the contract might be formed with (contracting between persons who are attended and contracting between absence persons).the need for determining the precise moment of the contract , is so clear because there is a specify period separate between the declaration of acceptance and the knowledge with it .and it is clear from the four theories known for jurisprudence (theory of the declaration of the acceptance, theory of exporting the acceptance , theory of the arrival of the acceptance , theory of the knowledge with the acceptance ) . It is difficult to promote one theory on another one if we look at each one and the justification of its supporters and what the opponents of each theory expose. Legal background and diff

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Dry gas is considered one of the most environmentally friendly sources of energy. As a result, developing an efficient strategy for storing this gas has become essential. In this work, MOF-199 was synthesized and characterized in order to investigate the MOF-199 in dry gas adsorption using a built-in volumetric system (methane, ethane, and propane from Basrah gas company). The MOF-199 (metal organic framework) was synthesized using the solvothermal method at 373K for 24h, and then it was characterized. The dry gas adsorption on MOF-199 was studied under various conditions (adsorbent dosage, contact time, temperature, and pressure). The isothermal adsorption of the dry gas had been studied on MOF-199 using two types of mo

Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel