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Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites in Baghdad city were used. 70% of these results were used to train the prediction ANN models and the rest were equally divided to test and validate the ANN models. The performance of the developed models was examined using the correlation coefficient R. The final models have demonstrated that the ANN has capability for acceptable prediction of compression index and compression ratio. Two equations were proposed to estimate compression index using the connecting weights algorithm, and good agreements with test results were achieved.

 

 

 

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Publication Date
Tue May 14 2024
Journal Name
Iranian Journal Of Catalysis
Feasible and simple preparation of Pd (II), Ni (II), and Pt (IV) complexes: Their biological and industrial applications and investigation of Pd (II) complex in Suzuki reaction
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A novel ligand, (E)-5-((2-hydroxy-4,6-dimethylphenyl)diazenyl)-2,3-dihydrophthalazine-1,4- dione, was synthesized through the reaction of 3,5-dimethylphenol with the diazonium salt of 5-amino-2,3-dihydrophthalazine-1,4-dione. The ligand underwent characterization through the utilization of diverse spectroscopic methods, including UV-Vis, FT-IR, 13C, and 1H-NMR, alongside Mass spectroscopy and micro elemental analysis (Carbon, Hydrogen, Nitrogen, and Oxygen). Metal chelates of transition metals were prepared and analyzed using elemental analysis, mass spectra, atomic absorption, UV-Vis, FT-IR spectral analysis, as well as conductivity and magnetic measurements. The investigation into the compounds’ nature was conducted by utilizing mole r

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Publication Date
Fri Jun 21 2024
Journal Name
Pharmacia
Synthesis and biological activity evaluation of new isatin-gallate hybrids as antioxidant and anticancer agents (in vitro) and in silico study as anticancer agents and coronavirus inhibitors
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Background: The hybrid compounds hold promise for developing novel pharmaceuticals, potentially exhibiting greater activity, mainly against viruses and cancer diseases, than their components.

Objective: In this study, researchers explored the potential synergistic effects of hybrid molecules by designing and synthesizing a series of isatin-gallate hybrids, denoted as N’-(5-substituted-2-oxoindolin-3-ylidene)-3,4,5-trihydroxybenzohydrazide (3a–d).

Methods: Isatin-gallate hybrids (3a–d) were synthesized by reacting gallic hydrazide with each of the isatin analogs (2a–d). The structures of all produced comp

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Synthesis, Characterization and the Corrosion Inhibition Study of Two Schiff Base Ligands Derived From Urea and Thiourea and Their Complexes with Cu(II) and Hg(II) Ions
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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Effects of Nitrogen and Sulfur Sprays on the Growth and Production of Broccoli Brassica Oleracea var. Italica L.: nitrogen and sulfur spray enhance broccoli growth and production
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In order to achieve optimal plant growth and production, essential nutrients must be readily available in adequate quantities and in a balanced proportion to give a good yield, especially broccoli which has health benefits that may not be found in many other plants. For this purpose, this experiment was carried out during the seasons 2019/2020 in the botanical garden of the Department of Biology, College of Science for Women, University of Baghdad, to study the effects of nitrogen and sulphur and their interaction on eight parameters reflecting the overall traits of vegetative growth, yield, and chlorophyll content of broccoli Brassica oleracea L. (var. italic JASSMINE F1 Hybrid). A factorial design with three replicates was use

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Effect of Plasma Shot Peening on Mechanical Properties and Fatigue life of AL-Alloys 2024-T3
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An Investigation of estimated Mechanical Properties of AL-Alloys 2024-T3, which is the most commonly used in industrial applications, been established experimentally. A new novel Plasma Peening techniques had applied for the whole surfaces of the material by CNC-Plasma machine for 48 specimen, and then a new investigation were toke over to figure the amount of change in mechanical properties and estimated fatigue life. It found that improvement was showing a nonlinear behavior according to peening duration time, speed, peening distance, peening number, and amount of effected power on the depth of the material thickness. The major improvement was at medium speed long duration time normal peening distance. Which shows up t

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Computer Science Trends And Technology
Secure Video Data Deduplication in the Cloud Storage Using Compressive Sensing
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Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Experimental Study of Hybrid Solar Air Conditioning System in Iraq
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In this paper, an experimental study of the thermal performance for hybrid solar air conditioning system was carried out, to investigate system suitability for the hot climate in Iraq. The system consists of vapor compression unit combined with evacuated tube solar collector and liquid storage tank. A three-way valve was installed after the compressor to control the direction flow of the refrigerant, either to the storage tank or directly to the condenser. The performance parameters were collected by data logger to display and record in the computer by using LabVIEW software. The results show that the average coefficient of performance of hybrid solar air conditioning system (R=1) was about 2.42 to 2.77 and the average p

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Study the Structural Properties of Porous Silicon and their Applications as Thermal Sensors
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The photo-electrochemical etching (PECE) method has been utilized to create pSi samples on n-type silicon wafers (Si). Using the etching time 12 and 22 min while maintaining the other parameters 10 mA/cm2 current density and HF acid at 75% concentration.. The capacitance and resistance variation were studied as the temperature increased and decreased for prepared samples at frequencies 10 and 20 kHz. Using scanning electron microscopy (SEM), the bore width, depth, and porosity % were validated. The formation of porous silicon was confirmed by x-ray diffraction (XRD) patterns, the crystal size was decreased, and photoluminescence (PL) spectra revealed that the emission peaks were centered at 2q of 28.5619° and 28.7644° for et

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Publication Date
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
A Face Mask Detection Method in the Era of the COVID-19 Pandemic Based on GLCM and YOLO
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In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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