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Utilizing Activated Carbon from the Date Fronds to Detect Latent Fingerprints
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Background: In this work, a fingerprint powder was used to reveal latent fingerprints from different surfaces. This powder was derived from the Date fronds as activated carbon. Methods: In preparing the activated carbon, three parameters were studied: activation time, activation temperature, and impregnation ratio. Fourier Transform Infrared Spectroscopy (FTIR) was used to characterize the prepared Date frond activated carbon (DFAC) as well as the raw material (Date frond plant). Brunauer-Emmett-Teller (BET) was used to measure the specific surface area of DFAC. The surface shape and the element composition of the prepared powder were investigated using (SEM-EDS) analysis. A Central Composite Design (CCD) was employed to determine the optimal preparation conditions and to elucidate the relationship between the studied parameters and the response (yield). Sodium acetate and mineral oil were added to the (DFAC) powder in five different concentrations to enhance the intensity of the expression, thereby revealing latent fingerprints. Results: The results show that the best powder recipe was one with 20% sodium acetate and mineral oil, respectively. The Date frond activated carbon (DFAC) powder was compared with the commonly used importer powder (Sirchie) and tested for several surfaces. Additionally, the time of the latent fingerprints' presence on the surfaces was determined. It took fifteen days to notice the perfectly distinct fingerprint. Conclusion: Activated carbon derived from Date fronds was successfully used to reveal latent fingerprints on various non-porous materials. The Date frond activated carbon (DFAC) powder showed good adherence to friction ridges and was more effective than the commercial Sirchie powder, DFAC demonstrated similar excellent results in displaying detailed fingerprint patterns. Enhancing the DFAC powder with sodium acetate and mineral oil improved the visualization intensity, with the optimal formula being 20% sodium acetate and 2% mineral oil.

Publication Date
Sat Apr 01 2017
Journal Name
Applied Energy
Melting enhancement in triplex-tube latent heat energy storage system using nanoparticles-metal foam combination
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Publication Date
Sat Sep 01 2018
Journal Name
Microporous And Mesoporous Materials
Understanding the seeding mechanism of hierarchically porous zeolite/carbon composites
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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Image And Graphics
Normalized-UNet Segmentation for COVID-19 Utilizing an Encoder-Decoder Connection Layer Block
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The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre

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Publication Date
Sat Oct 18 2025
Journal Name
Pattern Recognition And Artificial Intelligence
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Fri Jan 01 2010
Journal Name
2010 Fourth Asia International Conference On Mathematical/analytical Modelling And Computer Simulation
Interaction Testing: From Pairwise to Variable Strength Interaction
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Publication Date
Mon Sep 01 2025
Journal Name
International Communications In Heat And Mass Transfer
Optimizing the shell-and-multitube latent heat thermal storage: Influence of tube layout and fin design on consecutive/simultaneous operation modes
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Energy Storage
Effects of non-uniform fin arrangement and size on the thermal response of a vertical latent heat triple-tube heat exchanger
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Publication Date
Wed Jun 01 2022
Journal Name
Civil And Environmental Engineering
Effect of Alkali - Activated Natural Pozzolan on Mechanical Properties of Geopolymer Concrete
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As an alternative to Ordinary Portland Cement (OPC), the alkali-activated binders have been developed with better technical characteristics and more extended durability. The Alkali-Activated Iraqi Natural Pozzolans (AANP) could produce geopolymer cementation building materials and make them ecologically acceptable. The primary advantage of geopolymer cement is that it has a lower environmental effect that contributes to it. The engineering characteristics of geopolymer concrete produced using activated Iraqi natural Pozzolan are summarized in this research. The mechanical properties, modulus of elasticity, and ultrasonic pulse velocity of various concrete mixes were determined via experimental study. The impact of essential variables like w

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Publication Date
Wed Jun 01 2022
Journal Name
Civil And Environmental Engineering
Effect of Alkali - Activated Natural Pozzolan on Mechanical Properties of Geopolymer Concrete
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Abstract<p>As an alternative to Ordinary Portland Cement (OPC), the alkali-activated binders have been developed with better technical characteristics and more extended durability. The Alkali-Activated Iraqi Natural Pozzolans (AANP) could produce geopolymer cementation building materials and make them ecologically acceptable. The primary advantage of geopolymer cement is that it has a lower environmental effect that contributes to it. The engineering characteristics of geopolymer concrete produced using activated Iraqi natural Pozzolan are summarized in this research. The mechanical properties, modulus of elasticity, and ultrasonic pulse velocity of various concrete mixes were determined via exp</p> ... Show More
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