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Role of immobilised Chlorophyta algae in form of calcium alginate beads for the removal of phenol: isotherm, kinetic and thermodynamic study
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Publication Date
Thu Mar 01 2018
Journal Name
2018 International Conference On Computing Sciences And Engineering (iccse)
Comparison between Epsilon Normalized Least Means Square (ϵ-NLMS) and Recursive Least Squares (RLS) Adaptive Algorithms
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There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

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Publication Date
Tue Jul 26 2022
Journal Name
Frontiers In Veterinary Science
Berbamine and thymoquinone exert protective effects against immune-mediated liver injury via NF-κB dependent pathway
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Background

Immune-mediated hepatitis is a severe impendence to human health, and no effective treatment is currently available. Therefore, new, safe, low-cost therapies are desperately required. Berbamine (BE), a natural substance obtained primarily from Berberis vulgaris L, is a traditional herbal medicine with several bioactivities, such as antimicrobial and anticancer activities. Thymoquinone (TQ), a phytochemical molecule derived from the Nigella sativa plant's black cumin seeds, has attracted interest owing to itsanti-inflammatory, antioxidant, and anticancer properties.

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This c

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Polluted Water Sensor Based on Carbon Quantum Dots/Alq3 Using Drop Casting and Spin Coating Techniques
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Water quality sensors have recently received a lot of attention due to their impact on human health. Due to their distinct features, environmental sensors are based on carbon quantum dots (CQDs). In this study, CQDs were prepared using the electro-chemical method, where the structural and optical properties were studied. These quantum dots were used in the environmental sensor application after mixing them with three different materials: CQDs, Alq3 polymer and CQDs and Alq3 solutions using two different methods: drop casting and spin coating, and depositing them on silicon. The sensitivity of the water pollutants was studied for each case of the prepared samples after measuring the change in resistance of the samples at a temperature of

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Publication Date
Mon Jun 30 2025
Journal Name
Modern Sport
Visual Tracking and its Relationship to Dynamic Visual Acuity Among National Youth Foil Fencing Team Athletes
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Publication Date
Sun Mar 30 2025
Journal Name
Mustansiriyah Journal Of Pure And Applied Sciences
Secure E-voting authentication system employing biometric technology, Crypto-Watermarking Approach and blockchain technology: A Review
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Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Physics: Conference Series
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and cubic SVM
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Abstract<p>Communication of the human brain with the surroundings became reality by using Brain- Computer Interface (BCI) based mechanism. Electroencephalography (EEG) being the non-invasive method has become popular for interaction with the brain. Traditionally, the devices were used for clinical applications to detect various brain diseases but with the advancement in technologies, companies like Emotiv, NeuoSky are coming up with low cost, easily portable EEG based consumer graded devices that can be used in various application domains like gaming, education etc as these devices are comfortable to wear also. This paper reviews the fields where the EEG has shown its impact and the way it has p</p> ... Show More
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Publication Date
Tue Oct 01 2019
Journal Name
Comparative Immunology, Microbiology And Infectious Diseases
Zataria Multiflora bois as an auspicious therapeutic approach against Echinococcus granulosus: Current status and future perspectives
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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
A Try to combine more than approaches and competitive strategies to achieve a sustainable competitive advantage.
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The objective of this research paper is two-fold. The first is a precise reading of the theoretical underpinnings of each of the strategic approaches: "Market approach" for (M. Porter), and the alternative resource-based approach (R B V), advocates for the idea that the two approaches are complementary. Secondly, we will discuss the possibility of combining the two competitive strategies: cost leadership and differentiation. Finally, we propose a consensual approach that we call "dual domination". 

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Publication Date
Tue Nov 01 2016
Journal Name
Renewable And Sustainable Energy Reviews
Dye-sensitised solar cells: Development, structure, operation principles, electron kinetics, characterisation, synthesis materials and natural photosensitisers
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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