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ijcpe-1048
Synthesis, Characterizations, and Recent Applications of the Silica-based Mobil Composition of Mesoporous Material: A Review
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Silica-based mesoporous materials are a class of porous materials with unique characteristics such as ordered pore structure, large surface area, and large pore volume. This review covers the different types of porous material (zeolite and mesoporous) and the physical properties of mesoporous materials that make them valuable in industry. Mesoporous materials can be divided into two groups: silica-based mesoporous materials and non-silica-based mesoporous materials. The most well-known family of silica-based mesoporous materials is the Mesoporous Molecular Sieves family, which attracts attention because of its beneficial properties. The family includes three members that are differentiated based on their pore arrangement. In this review, the major applications of the Mobil Mesoporous Molecular Sieves family, such as catalysts, adsorbents, and drug delivery agents, have been surveyed. Furthermore, the synthesis of the Mesoporous Molecular Sieves materials, the silica sources, the importance of templates, and the mechanisms of the synthesis are discussed herein. Members of this material family are characterized by many physicochemical properties that are closely related to their high silica content, crystalline structure, and pore arrangement. Commonly, the members of this family have large surface areas, high pore volumes, small pore sizes, and narrow and uniform particle size distributions. These properties enable numerous industrial applications and opportunities for scientific studies to further develop existing materials or manufacture new ones.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sun Feb 13 2022
Journal Name
Petroleum & Coal
Laboratory-Based Correlations to Estimate Geomechanical Properties for Carbonate Tight Reservoir.
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Rock mechanical properties are critical parameters for many development techniques related to tight reservoirs, such as hydraulic fracturing design and detecting failure criteria in wellbore instability assessment. When direct measurements of mechanical properties are not available, it is helpful to find sufficient correlations to estimate these parameters. This study summarized experimentally derived correlations for estimating the shear velocity, Young's modulus, Poisson's ratio, and compressive strength. Also, a useful correlation is introduced to convert dynamic elastic properties from log data to static elastic properties. Most of the derived equations in this paper show good fitting to measured data, while some equations show scatters

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Publication Date
Mon Nov 09 2020
Journal Name
Construction Research Congress 2020
Alternative Risk Models for Optimal Investment in Portfolio-Based Community Solar
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
CTJ: Input-Output Based Relation Combinatorial Testing Strategy Using Jaya Algorithm
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Software testing is a vital part of the software development life cycle. In many cases, the system under test has more than one input making the testing efforts for every exhaustive combination impossible (i.e. the time of execution of the test case can be outrageously long). Combinatorial testing offers an alternative to exhaustive testing via considering the interaction of input values for every t-way combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). IOR combinatorial testing only tests for the important combinations selected by the tester. Most of the researches in combinatorial testing

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Publication Date
Wed Aug 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Evaluation Based on Multi-UAV in Airborne Computer Network System
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Blue Organic-Inorganic Light Emitting Diode Based on Electroluminescence CdS Nanoparticle
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     A hybrid cadmium sulfide nanoparticles (CdSNPs) electroluminescence (EL) device was fabricated by Phase – Segregated Method and characterized. It was fabricated as layers of (ITO/poly-TPD:CdS ) and (ITO/poly-TPD:CdS /Alq3). Poly-TPD is an excellent Hole Transport Layer (HTL), CdSNPs is an emitting layer and Alq3 as electron transport layer (ETL). The EL of Organic-Inorganic Light Emitting Diode (OILED) was studied at room temperature at 26V. This was achieved according to band-to-band transition in CdSNPs. From the I-V curve behavior, the addition of Alq3 layer decreased the transfer of electrons by about 250 times. The I-V behavior for (poly-TPD/CdS) is exponential with a maximum current of 4500 µA. While, the current i

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Information Hiding And Multimedia Signal Processing
Upscale Gray Image using Mixing Transform Generation based on Tensor Product
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The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021

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Publication Date
Thu Mar 19 2026
Journal Name
International Journal Of Mechatronics And Applied Mechanics
EXTENDED STATE OBSERVER-BASED OPTIMIZED SYNERGETIC CONTROL FOR PRODUCTION-INVENTORY SYSTEMS
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The efficient exploitation of production inventory systems is of significant importance in the modern industrial reality. This paper explores the effect of such a system on dynamic behaviour of a system when the control is provided synergistically by a method called synergetic control (SC). The mathematical model of the system is first constructed and SC introduced to improve the responsiveness of the system when the time-varying demand condition is taken into account. To cope with the problem of unavailability of the systems' state signals and to estimate the demand, the extended state observer (ESO) is introduced. Moreover, mountain gazelle optimizer (MGO) is employed to tune the adjustable design parameters of the SC and the ESO based on

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Publication Date
Tue Apr 11 2023
Journal Name
Sensors
EEG Signal Complexity Measurements to Enhance BCI-Based Stroke Patients’ Rehabilitation
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The second leading cause of death and one of the most common causes of disability in the world is stroke. Researchers have found that brain–computer interface (BCI) techniques can result in better stroke patient rehabilitation. This study used the proposed motor imagery (MI) framework to analyze the electroencephalogram (EEG) dataset from eight subjects in order to enhance the MI-based BCI systems for stroke patients. The preprocessing portion of the framework comprises the use of conventional filters and the independent component analysis (ICA) denoising approach. Fractal dimension (FD) and Hurst exponent (Hur) were then calculated as complexity features, and Tsallis entropy (TsEn) and dispersion entropy (DispEn) were assessed as

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Publication Date
Mon Dec 01 2025
Journal Name
Results In Engineering
Kernel-based machine learning intrusion detection systems for ICMPv6 DDoS detection
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