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bsj-5597
Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System
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              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breathing difficulty) used to diagnose the person being infected by COVID-19 virus or not. Secondly, this approach divides the infected peoples into four classes, based on their immune system risk level (very high degree, high degree, mild degree, and normal), and using two indices of age and current health status like diabetes, heart disorders, or hypertension. Where, these people are graded and expected to comply with their class regulations. There are six important COVID-19 virus infections of different classes that should receive immediate health care to save their lives. When the test is positive, the patient age is considered to choose one of the six classifications depending on the patient symptoms to provide him the suitable care as one of the four types of suggested treatment protocol of COVID-19 virus infection in COVID-19 DSS application. Finally, a report of all information about any classification case of COVID-19 infection is printed where this report includes the status of patient (infection level) and the prevention protocol. Later, the program sends the report to the control centre (medical expert) containing the information. In this paper, it was suggested the use of C4.5 Algorithm for decision tree.

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Publication Date
Thu Oct 03 2024
Journal Name
Applied Organometallic Chemistry
Synthesis, Characterization, Molecular Docking, Cytotoxicity, and Antimicrobial Activity of Schiff Base Ligand and Its Metal Complexes
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ABSTRACT<p>A Schiff base ligand (L) was synthesized via condensation of <italic>N</italic>‐(1‐naphthyl)ethylenediamine dihydrochloride with phthalaldehyde. The ligand was characterized by FT‐IR, UV–Vis, <sup>1</sup>H NMR, mass spectrometry, and elemental analysis (C, H, N). Five metal complexes (Co(II), Ni(II), Cu(II), Zn(II), and Cd(II)) were prepared with the ligand in a 1:1 (M:L) ratio using an aqueous ethanol solution. The complexes were characterized by FT‐IR, UV–Vis, mass spectrometry, and elemental analysis (C, H, N). Additionally, <sup>1</sup>H NMR spectroscopy was employed for Cd(II) complex. Antimicrobial activity of the ligand and its metal complexes against </p> ... Show More
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Publication Date
Fri Jun 01 2018
Journal Name
Oriental Journal Of Chemistry
Synthesis, Spectral and Biochemical Studies of New Complexes of Mixed Ligand Schiff Base and Anthranilic Acid
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In this rescrch,new mixed ligand Schiff base complexes of Mn(II),Co(II),Ni(II),Cu(II), Cd(II), and Hg(II) are formulated from the Schiff base( L)resulting from  o-phathalaldehyde(o-PA) with p-nitroaniline(p-NA)as a primary ligand and anthranilic acid as a subordinate ligand. Diagnosis of prepared Ligand and its complexes is done by spectral methods mass spectrometer;1H -NMR for ligand Schiff base FTIR, UV-Vis, molar conductance, elemental microanalyses, atomic absoption and magnetic susceptibility. The analytical studies for the all new complexes have shown octahedral geometries. The study of organicperformance  of ligand Schiff base and its complexes show various activity agansit four type of bactria two gram (+) and two gram (-) .

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Engineering
Practical comparation of the accuracy and speed of YOLO, SSD and Faster RCNN for drone detection
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

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Publication Date
Thu Jun 01 2023
Journal Name
Russian Journal Of Organic Chemistry
New Quinolin-2-one, Indazole, and Benzisoxazole Derivatives Derived from Chalcones: Synthesis, Characterization, and Biological Activity
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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
Synthesis and characterization of metastable phases of SnO and Sn3O4 thin films for solar cells applications
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Abstract<p>Meta stable phase of SnO as stoichiometric compound is deposited utilizing thermal evaporation technique under high vacuum onto glass and p-type silicon. These films are subjected to thermal treatment under oxygen for different temperatures (150,350 and 550 °C ). The Sn metal transformed to SnO at 350 oC, which was clearly seen via XRD measurements, SnO was transformed to a nonstoichiometric phase at 550 oC. AFM was used to obtain topography of the deposited films. The grains are combined compactly to form ridges and clusters along the surface of the SnO and Sn3O3 films. Films were transparent in the visible area and the values of the optical band gap for (150,350 and 550 °C ) 3.1, </p> ... Show More
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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Ecological Engineering
Calibration and evaluation of aquacrop for maize (Zea Mays L.) under different irrigation and cultivation methods
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rop simulation models play a pivotal role in evaluating irrigation management strategies to improve water use in agriculture. The aim of this study is to verify the validity of the Aquacrop model of maize under the surface and sprinkler irrigation systems, and a cultivation system, borders and furrows, and for two varieties of Maze (Fajr and Drakma) At two different sites in Iraq, Babylon and Al-Qadisiyah governorates. An experiment was conducted to evaluate the performance of the Aquacrop model in simulating canopy cover (CC), biomass (B), dry yield, harvest index (HI), and water productivity (WP). The results of RMSE, R2, MAE, d, NSE, CC, Pe indicated good results and high compatibility between measured and simulated values. The highest a

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Publication Date
Fri Apr 23 2021
Journal Name
International Journal Of Environmental Analytical Chemistry
Removal of levofloxacin and ciprofloxacin from aqueous solutions and an economic evaluation using the electrocoagulation process‏
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For this research, the utilisation of electrocoagulation (EC) toremove theciprofloxacin (CIP) and levofloxacin (LVX) from aqueous solutions was examined. The effective removal efficiencies are 93.47% for CIP and 88.00% for LVX, under optimum conditions. The adsorption isotherm models with suitable mechanisms were applied to determine the elimination of CIP and LVX utilizingtheEC method. Thefindingsshowed the adsorption of CIP and LVX on iron hydroxide flocs followed the Sips isotherm, with correlation coefficient values (R2) of 0.939 and 0.937. Threekinetic models were reviewed to determine the accurate CIP and LVX elimination methods using the EC method. The results showed that itfittedfor the second-order model, which indicated that the c

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Publication Date
Tue Dec 01 2020
Journal Name
Marine And Petroleum Geology
Chemical and isotope composition of the oilfield brines from Mishrif Formation (southern Iraq): Diagenesis and geothermometry
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Publication Date
Tue Jul 17 2018
Journal Name
Materials Research Express
Structural, electronic and thermodynamic properties of bulk and surfaces of terbium dioxide (TbO<sub>2</sub>)
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This contribution reports a comprehensive investigation into the structural, electronic and thermal properties of bulk and surface terbium dioxide (TbO2); a material that enjoys wide spectra of catalytic and optical applications. Our calculated lattice dimension of 5.36 Å agrees well with the corresponding experimental value at 5.22 Å. Density of states configuration of the bulk structure exhibits a semiconducting nature. Thermo-mechanical properties of bulk TbO2 were obtained based on the quasi-harmonic approximation formalism. Heat capacities, thermal expansions and bulk modulus of the bulk TbO2 were obtained under a wide range of temperatures and pressures. The dependency of these properties on operational pressure is very evident. Cle

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Theoretical and experimental studies for different compounds to calculate: electronic transfer, energy gap and NLO properties
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This work involves theoretical and experimental studies for seven compounds to calculate the electrons spectrum and NLO properties. The theoretical study is done by employing the Time Depending Density Functional Theory TD-DFT and B3LYP/high basis set 6-311++G (2d,2p), using Gaussian program 09. Experimental study by UV/VIS spectrophotometer device to prove the theoretical study. Theoretical and experimental results were applicable in spectrum and energy gap values, in addition to convergence theoretically the energy gap results from ΔEHOMO-LUMO and UV/VIS. spectrum. Consider the theoretical method very appropriate to compounds that absorb in vacuum UV.

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