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Theoretical Investigations of Vibrational – Rotational Energy of some Hydrogen Halide Molecules
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A theoretical study by using computer model is presented to study the energy characteristics of the vibrational – rotational levels as a function of the vibrational and rotational quantum number, respectively. The calculations were based on the basis of a multilevel model taking into account the non-equilibrium population of the rotational levels. The computational investigation has been performed to examine the vibrational-rotational characteristics of some hydrogen halides chemical laser molecules. This program takes into account the various molecules of chemical lasers such as, Hydrogen Fluoride (HF), Deuterium Fluoride (DF), Hydrogen Chloride (HCl), and Deuterium Chloride (DCl). The practical difficulties associated with this type of lasers suggested that alternative route might be quite useful. Thus particular attention was paid to the development of computer program to investigate various energy characteristics. Comparison of the calculated results for different molecules shows that the highest values for the HF molecule probably due to their higher constants in comparison with the other molecules.

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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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Publication Date
Mon Jan 01 2024
Journal Name
Recent Research On Geotechnical Engineering, Remote Sensing, Geophysics And Earthquake Seismology
Evaluating the Accuracy of iPhone Lidar Sensor for Building Façades Conservation
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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Evaluation of Chloramphenicol as Thermosensitive Ocular in- situ Gel
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The purpose of this study was to develop poloxamer-based in-situ gel of chloramphenicol aiming to increase bioavailability and prolong corneal contact time, controlling drug release, and enhancing ocular bioavailability. The in-situ gel was prepared using different concentrations of poloxamer 407 combined with hydroxypropyl methyl cellulose (HPMC) or carbapol 940 to achieve gelation temperature about physiological temperature and improve rheological behavior and gelling properties of poloxamer gel. The prepared formulations were evaluated for their appearance, pH, and sol-gel transition temperature. The formulations F2, F3, and F5 have a gelation temperature within the accepted range 35-370C an

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Publication Date
Wed Jun 26 2024
Journal Name
Iraqi Journal Of Agricultural Sciences
ANTIBACTERIAL AND ANTIOXIDANT ACTIVITIES OF PHENOLIC COMPOUNDS FROM MYRTUS COMMUNIS CALLUS
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This study was aimed to evaluate atotal phenolic content, antibacterial activity, and antioxidant activity of M. communis callus extracts were evaluated. Callus induction in general Murashige and Skoog (MS) media is completed by the Benzil adenine's unique knowledge of callus formation. A well diffusion experiment was used to examine antibacterial interest in Staphylococcus aureus, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa. The DPPH radical scavenging activity test was used to measure antioxidant activity. FTIR and HPLC have been used to pinpoint the presence of polyphenol compounds in calluses. The total phenol content of plant leaves extract (0.1, 0.5, and 1) mg/ml was 42.12, 94.08, and 189 mg of Gallic ac

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of Engineering Science And Technology
THERMAL PERFORMANCE OF MULTIPLE- PASS SOLAR AIR HEATER WITH PIN FINS
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Publication Date
Sun Jun 01 2025
Journal Name
Results In Engineering
Structural Performance of Rail Connections: Experimental Testing and Finite Element Modeling
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Publication Date
Wed Aug 01 2018
Journal Name
Materials Research Bulletin
Chemical bath deposition of single crystal SnS nanobelts on glass substrates
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SnS nanobelt thin films were deposited on glass substrates in acidic solution by chemical bath deposition (CBD) method. The belt-like morphologies of as-deposited SnS thin films were characterized by scanning electron microscope (SEM) and transmission electron microscopy (TEM). X-ray diffraction (XRD) and Raman measurements were carried out to confirm the crystal structures and phase purities of SnS nanobelt thin films. The morphologies and phase purities of SnS thin films were influenced greatly by the tin and sulfur precursors. The bandgaps of SnS nanobelts were determined to be 1.39–1.41 eV by UV–vis absorption and photoluminescence (PL) spectra. Current-voltage ((I-V)) and current-time ((I-T)) characteristics were studied to demon

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Publication Date
Mon Mar 02 2020
Journal Name
Iraqi Geological Journal
RESERVOIR MODELING OF MISHRIF FORMATION IN MAJNOON OIL FIELD, SOUTHERN IRAQ
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The Middle Cenomanian-Early Turonian Mishrif Formation includes important carbonate reservoirs in Iraq and some other surrounding countries due to their high reservoir quality and wide geological extension. The 2D models of this study for facies, effective porosity and water saturation indicate the vertical and lateral heterogeneity of the Mishrif Formation reservoir properties in the Majnoon oil field. Construction of 2D reservoir model of the Mishrif Formation to explain the distribution of facies and petrophysical properties (effective porosity and water saturation) by using RockWorks software. The increase of effective porosity is attributed to the presence of shoal facies.The high water saturation is attributed to the existence of rest

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Classification of Diseases in Oil Palm Leaves Using the GoogLeNet Model
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The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

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