The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

Many countries, including the Arab countries, have sought to establish the free zones because of their important economic importance to diversify financial income, especially in rentier countries, in light of the trend towards the capitalist economy in light of what has been produced by economic globalization, in addition to that many Arab countries have turned towards establishing the free zones that many countries of the world have turned to, to support their economy, especially in the field of attracting foreign investments for these regions, and using them in transferring modern technology, and operating the national workers of the countries that have established those areas, and adopting their products in meeting the needs of t

In this reserch Some new substituted and unsubstituted poly imides compounds. were synthesized by reaction of acrylol chloride with different amides (aliphatic and aromatic) in a suitable solvent in the presence amount triethyl amine (Et3N) with heating. The Structure confirmation of all polymers were confirmed using FT-IR,1H-NMR,13C-NMR and UV spectroscopy. Thermal analysis (TG) for some polymers showed their thermal stabilities. Other physical properties including softening points, melting point and solubility of the polymers were also measured

Ciprofloxacin, which is a second generation of fluoroquinolone and one of the most effective and widely used drugs within fluoroquinolone. Unfamiliar adverse effects of ciprofloxacin such as bone marrow (BM) suppression, thrombocytopenia, anemia, agranulocytosis, renal failure, and others observed. Lutein, is a xanthophyll (an oxygenated carotenoid), was focused by most studies as it has a strong antioxidant activity in vitro; and also, it has been associated with reducing the risk of the age-related disorders. The current study was designed to describe the role of apoptosis through the measurement of Bcl-2 associated X protein (Bax) marker, as mechanisms of bone marrow toxicity induced by ciprofloxacin and to find whether lutei

Ciprofloxacin is widely used in treating adults infected with Gram-negative bacteria. It is contraindicated in children, growing adolescents and during pregnancy due to joint toxicity. Its toxicity concerning other organs needs to be clarified. Thus, this study was designed to study the possible cardiac damage induced by two selected doses of ciprofloxacin in juvenile rats.Eighteenth healthy juvenile rats (4 weeks old and their weight 30 ± 2 gm) were utilized in this study and divided into three groups. Group-I control; group II and group III, respectively injected IP with 25 mg/kg and 50 mg/kg ciprofloxacin every 12 hours for one week. Serum enzymes activities alanine aminotransferase (ALT), aspartate aminotransferase  (AST), cr