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bsj-6704
Synthesis, Spectral Identification, Antibacterial Evaluationand Theoretical Study of Co, Fe, Rh and Pd Complexes for 2-benzoylthiobenzimidazol
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A new novel series of metalcomplexes are prepared from reactions between 2-benzoylthio- benzimidazole (L) with metal salts of Co (II) , Fe(III) and Rh (III) , while Pd(II) complex was obtained by mixing ligandsof 2-benzoylthiobenzimidazole (L) as primary ligand and bipyridine (L/)as secondary ligand as well as palladium chloride as metal salt in an ethanoic medium. The geometry of these compounds were identified using C.H.N.microanalysis, Ultraviolet–visible, Fourier transforms infrared, magnetic susceptibility, molar conductivity and flame atomic absorption (A.A). From the dataobtained by these spectral analyses, the molecular structures for Rh and Fe complexes were proposed to be octahedral geometry. A square planar construction is proposed for Pd(II), while a Tetrahedral Geometry for Cobalt (II)complex. All of the complexes which were prepared displayedobviousconstancy and could be stored for months without showing any considerablealteration. Semi-empirical methods (ZINDO/1, ZINDO/S & PM3) were conducted to assess the heat of formation ∆H˚f, binding energy ∆Eb, and dipole moment for all compounds as theoretic study. The complexes expressnotable biological activities to pathogenic bacteria when inspected on certain bacteria. The synthesized compounds exhibited moderate toverygood antibacterial activity against bacterial strains, i.e., Escherichiacoli, Staphylococcus aureus & Pseudomonas aeruginosa.

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Publication Date
Sun Jan 01 2023
Journal Name
Organization, Technology And Management In Construction: An International Journal
Using the ordinal priority approach for selecting the contractor in construction projects
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Abstract<p>Effective decision-making process is the basis for successfully solving any engineering problem. Many decisions taken in the construction projects differ in their nature due to the complex nature of the construction projects. One of the most crucial decisions that might result in numerous issues over the course of a construction project is the selection of the contractor. This study aims to use the ordinal priority approach (OPA) for the contractor selection process in the construction industry. The proposed model involves two computer programs; the first of these will be used to evaluate the decision-makers/experts in the construction projects, while the second will be used to formul</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials &amp; Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Mon Aug 01 2022
Journal Name
Water, Air, & Soil Pollution
Cladophora Algae Modified with CuO Nanoparticles for Tetracycline Removal from Aqueous Solutions
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Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

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Publication Date
Sun Oct 01 2023
Journal Name
Ieee Transactions On Industrial Electronics
Singular Perturbation-Based Adaptive Integral Sliding Mode Control for Flexible Joint Robots
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The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
Determination the optimum orbit for low Earth satellites by changing the eccentricity
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Abstract<p>The main objective of this paper is to determine an acceptable value of eccentricity for the satellites in a Low Earth Orbit LEO that are affected by drag perturbation only. The method of converting the orbital elements into state vectors was presented. Perturbed equation of motion was numerically integrated using 4<sup>th</sup> order Runge-Kutta’s method and the perturbation in orbital elements for different altitudes and eccentricities were tested and analysed during 84.23 days. The results indicated to the value of semi major axis and eccentricity at altitude 200 km and eccentricity 0.001are more stable. As well, at altitude 600 km and eccentricity 0.01, but at 800 km a</p> ... Show More
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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Construction Engineering And Management
Developing a Decision-Making Framework to Select Safety Technologies for Highway Construction
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Publication Date
Sat Jun 01 2024
Journal Name
Alexandria Engineering Journal
U-Net for genomic sequencing: A novel approach to DNA sequence classification
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The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
An Evolutionary Algorithm for Task scheduling Problem in the Cloud-Fog environment
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Abstract<p>The rapid and enormous growth of the Internet of Things, as well as its widespread adoption, has resulted in the production of massive quantities of data that must be processed and sent to the cloud, but the delay in processing the data and the time it takes to send it to the cloud has resulted in the emergence of fog, a new generation of cloud in which the fog serves as an extension of cloud services at the edge of the network, reducing latency and traffic. The distribution of computational resources to minimize makespan and running costs is one of the disadvantages of fog computing. This paper provides a new approach for improving the task scheduling problem in a Cloud-Fog environme</p> ... Show More
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Publication Date
Wed Sep 01 2021
Journal Name
Expert Systems With Applications
A long short-term recurrent spatial-temporal fusion for myoelectric pattern recognition
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Publication Date
Tue Nov 01 2022
Journal Name
2022 International Conference On Data Science And Intelligent Computing (icdsic)
An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

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