Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

Polyaniline nanofibers (PAni-NFs) have been synthesized under various concentrations (0.12, 0.16, and 0.2 g/l) of aniline and different times (2h and 3 h) by hydrothermal method at 90°C. Was conducted with the use of X-ray diffraction (XRD), Fourier Transform Infrared spectra (FTIR), Ultraviolet-Visible (UV-VIS) absorption spectra, Thermogravimetric Analysis (TGA), and Field Emission-Scanning Electron Microscopy (FE-SEM). The X-ray diffraction patterns revealed the amorphous nature of all the produced samples. FE-SEM demonstrated that Polyaniline has a nanofiber-like structure. The observed typical peaks of PAni were (1580, 1300-1240, and 821 cm-1 ), analyzed by the chemical bonding of the formed PAni through FTIR spectroscopy. Also, tests

The present study was designed to synthesize a number of new Ceftriaxone derivatives by its involvement with a series of different amines, through the chemical derivatization of its 2-aminothiazolyl- group into an amide with chloroacetyl chloride, which on further conjugation with these selected amines will produce compounds with pharmacological effects that may extend the antimicrobial activity of the parent compound depending on the nature of these moieties.

Ceftriaxone was first equipped with a spacer arm (linker) by the action of chloroacetyl chloride in aqueous medium and then further reacted with seven different aliphatic and aromatic amines which resulted in the production of the aimed final target products. The syntheses

The amino thiadiazole [I] on treatment with aromatic aldehydes yielded Schiff bases [IIa-c], which cyclized to thiazolidinone [IIIa-c] derivatives by reaction with thioglycolic acid. Reaction of carbon disulfide and methyl iodide with [I] gavedithiomethyl [IV] which on treatment with o-phenylenediamine gave the condensed N-Imidazolythiadiazolylamine [V], However, reaction of [I] with phenylisocyanate and phenylisothiocyanate afforded the carbamideand carbothiamide derivatives [VI. VII] ac. The structure of these compounds was characterized from their melting point, FTIR spectroscopy and elementalanalysis

Coumarin derivatives have shown different biological activities, such as antifungal, antibacterial   antiinflammatory, and antioxidant activities, besides antibiotic resistance modulating effects, and anti-HIV, hepatoprotective, and antitumor effect. So, new coumarin derivatives (hydrazones and an amide) were synthesized through multisteps reactions. All the synthesized target compounds were characterized by FT-IR spectroscopy, 1HNMR analysis. The compounds then evaluated for their anti-bacterial activity by means of well-diffusion method against two gram-positive bacteria (Staphylococcus aureus, Streptococcus pneumoniae) and two gram-negative bacteria  (E.coli and Pseudomonas aeruginosa). The highest activity was demonstr

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

The deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m