We focus on studying the dynamics of bulk semiconductor optical amplifiers and their effects on the saturation region for short pulse that differ, however there is the same unsaturated gain for both dynamics. Parameters like current injection, fast dynamics present by carrier heating (CH), and spectra hole burning (SHB) are studied for regions that occur a response to certain dynamics. The behavior of the saturation region is found to be responsible for phenomena such as recovery time and chirp for the pulse under study.

Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

The recent development in communication technologies between individuals allows for the establishment of more informal collaborative map data projects which are called volunteered geographic information (VGI). These projects, such as OpenStreetMap (OSM) project, seek to create free alternative maps which let users add or input new materials to the data of others. The information of different VGI data sources is often not compliant to any standard and each organization is producing a dataset at various level of richness. In this research the assessment of semantic data quality provided by web sources, e.g. OSM will depend on a comparison with the information from standard sources. This will include the validity of semanti

      The transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than othe

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

     This study examined the effects of a few biochemical variables on obese Iraqi males and females with a 30.5 body mass index (BMI) when they were fed a ketogenic diet. The present study demonstrates how an individual who follows a ketogenic diet has an increase in low-density lipoprotein (LDL-cholesterol). This research's objective was to assess the levels of some biochemical variables in obese people who were eating a ketogenic diet. Following 35 days on a ketogenic diet, the results show a significantly higher P ≤ 0.05 level of low-density lipoprotein (LDL) and total cholesterol (TC). Additionally, insulin, fasting blood sugar (FBS), cortisol, HOMA-IR, urea, BMI, and creatinine all show a considerable reduction, P ≤

A theoretical and protection study was conducted of the corrosion behavior of carbon steel surface with different concentrations of the derivative (Quinolin-2-one), namly (1-Amino-4,7-dimethyl-6-nitro-1H-quinolin-2-one (ADNQ2O)). Theoretically, Density Functional Theory (DFT) of B3LYP/ 6-311++G (2d, 2p) level was used to calculate the optimized geometry, physical properties and chemical inhibition parameters, with the local reactivity to predict both the reactive centers and to locate the possible sites of nucleophilic and electrophilic attacks, in vacuum, and in two solvents (DMSO and H2O), all at the equilibrium geometry. Experimentally, the inhibition efficiencies (%IE) in the saline solution (of 3.5%) NaCl were studied using potentiomet

     PARP-1 is a protein enzyme with a major role in DNA repair that is overexpressed in many malignancies. It is correlated with susceptibility and metastasis to lymph nodes in gastric cancer (GC). The objective of the present investigation is to estimate PARP1 expression in patients with gastric cancer and detected if it could be used as a predictive marker. Furthermore, we aimed to find the correlation between PARP1 expression and clinicopathological parameters, such as gender, age, invasion depth, histopathological type, involvement of lymph nodes, grade, and stages of GC. This is a retrospective study from the period 2018-2020. Fifty randomly selected subjects (10 normal and 40 GC) were examined for formalin-fixe

For modeling a photovoltaic module, it is necessary to calculate the basic parameters which control the current-voltage characteristic curves, that is not provided by the manufacturer. Generally, for mono crystalline silicon module, the shunt resistance is generally high, and it is neglected in this model. In this study, three methods are presented for four parameters model. Explicit simplified method based on an analytical solution, slope method based on manufacturer data, and iterative method based on a numerical resolution. The results obtained for these methods were compared with experimental measured data. The iterative method was more accurate than the other two methods but more complexity. The average deviation of