Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well a

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

    In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

IH Abdul-Abbas, QJ Rashid, M RasimYounus, PalArch's Journal of Archaeology of Egypt/Egyptology, 2021 - Cited by 9

Objectives: To Assess the Effect of Physical Status of Polycystic Ovarian Syndrome on Women in Reproductive Age,
To Find out the Relationship Between Polycystic Ovarian Syndrome and Women's Physical Health (Acne , Hirsutism ,
Weight Gain , Irregular Menstrual Period),&To Identify the Association of Physical Status to polycystic ovarian
syndrome and Some Socio Demographic Characteristic (Age ,Occupation & Obesity ), and Reproductive
Characteristic(Gravida ,Para ,Abortion &Menstrual Regularity).
Methodology :a descriptive analytical study was conduct on Non-probability (purposive sample) of (100)women who
suffering from polycystic ovarian syndrome in reproductive age in infertility counseling from three hospit

The effect of the concentration of the colloidal nanomaterial on their optical limiting behavior is reported in this paper. The colloids of sliver nanoparticles in deionized water were chemically prepared for the two concentrations (31 ppm and 11ppm). Two cw lasers (473 nm Blue DPSS laser and 532 nm Nd:YAG laser) are used to compare the optical limiting performance for the samples. UV–visible spectrophotometer, transmission electron microscope (TEM) and Fourier Transformation Infrared Spectrometer (FTIR) were used to obtain the characteristics of the sample. The nonlinear refractive index was calculated to be in the order of 10-9 cm2/W. The results demonstrate that the observed limiting response is significant for 532nm. In addition, t

This study was conducted to determine the effects of concentration of hydrochloric acids, temperature, and time on the hydrolysis of soya proteins (defatted soya flour) by determining the value of total protein nitrogen  concentration, and amino nitrogen concentration of protein, peptides, and amino acids, and then calculated the hydrolysis rate of proteins.

        The variables of the conditions of hydrolysis process was achieved in this study with the following range value of tests parameter:

• Concentration of HCl solution ranged between 1-7 N,
• Hydrolysis temperature ranged between 35-95 °C, and
• The time of hydroly

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea