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A Proposed Blockchain-Based Digital-Identity Management using ERC 725/735
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In modern technology, the ownership of electronic data is the key to securing their privacy and identity from any trace or interference. Therefore, a new identity management system called Digital Identity Management, implemented throughout recent years, acts as a holder of the identity data to maintain the holder’s privacy and prevent identity theft. Therefore, an overwhelming number of users have two major problems, users who own data and third-party applications will handle it, and users who have no ownership of their data. Maintaining these identities will be a challenge these days. This paper proposes a system that solves the problem using blockchain technology for Digital Identity Management systems. Blockchain is a powerful technique to build a digital identity in chain matters that enables a secure environment. The idea of Blockchain is to distribute the data across multiple devices in a cryptographic way, which will reduce the ability to an impossible level. Therefore, in this paper a proposed Digital Identity based on Blockchain (ERC 725, and ERC 735) with MD6 as a hashing algorithm will be implemented in a Secure smart contract can prevent function calls from being carried out until the sender has received confirmation from a reliable issuer; for example, we might include a feature that restricts smart contract interactions to legitimate users only. Many additional use cases are possible with ERC-725, including multi-sig execution approvals and contract call verification in place of key validation.

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Publication Date
Tue Feb 06 2024
Journal Name
Research Square
Bioremediation of Cellulosic Wastes by Using Orthodillo chiltoni (Vandel, 1973), Isopoda
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Terrestrial isopods play an important role in the biodegradation of many wastes which gives agreat importance in the nutrient cycles and ecosystem services , therefore this paper aims to use species Orthodillo chiltoni (Vandel, 1973) as a model organism in bioremediation of urban environment with municipal wastes, agricultural fields, parks and markets wastes. Samples of these wastes included potato peels, orange fruit leaves, thyme plant and sawdust,cardboard residues , the experiments were carried out in laboratory condition similar to the living environment of this species in terms of temperature, humidity and intensity lighting. The applied results have shown that

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Publication Date
Mon Sep 01 2014
Journal Name
Journal Of Baghdad College Of Dentistry
Apexification and Periapical Healing of Immature Teeth Using Mineral Trioxide Aggregate
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Publication Date
Sun Dec 01 2024
Journal Name
Nordic Concrete Research
Evaluating Concrete Strength Under Various Curing Conditions Using Artificial Neural Networks
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Abstract<p>This study examines the impact of different curing methods on the compressive strength of concrete. It investigates techniques such as air curing, periodic water spraying, full water submersion, and polyethylene encasement. Artificial neural network models were employed to evaluate the compressive strength under each curing condition. A model for calculating compressive strength that considers surrounding conditions was created using an artificial neural network. The current study’s figures were generated using this model. The research thoroughly examined the impact of curing environments and concrete mix components on strength properties, taking into account factors such as tempera</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Tropical Medicine & Public Health
Assessment of Left Ventricular Function in Body builders using conventional echocardiography
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Background: Powerlifters and bodybuilders use anabolic androgenic steroids (AAS) especially – as many as 55 percent of elite powerlifters admitted using these agents. In contrast to numerous documented toxic and hormonal effects of AAS their impact on the structure and function of the left ventricular (LV) was not yet fully understood.

Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Mobile position estimation using artificial neural network in CDMA cellular systems
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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

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Publication Date
Wed Dec 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
Online medical consultation: covid-19 system using software object-oriented approach
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The internet has been a source of medical information, it has been used for online medical consultation (OMC). OMC is now offered by many providers internationally with diverse models and features. In OMC, consultations and treatments are available 24/7. The covid-19 pandemic across-the-board, many people unable to go to hospital or clinic because the spread of the virus. This paper tried to answer two research questions. The first one on how the OMC can help the patients during covid-19 pandemic. A literature review was conducted to answer the first research question. The second one on how to develop system in OMC related to covid-19 pandemic. The system was developed by Visual Studio 2019 using software object-oriented approach. O

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Characterization Performance of Monocrystalline Silicon Photovoltaic Module Using Experimentally Measured Data
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Solar photovoltaic (PV) system has emerged as one of the most promising technology to generate clean energy. In this work, the performance of monocrystalline silicon photovoltaic module is studied through observing the effect of necessary parameters: solar irradiation and ambient temperature. The single diode model with series resistors is selected to find the characterization of current-voltage (I-V) and power-voltage (P-V) curves by determining the values of five parameters ( ). This model shows a high accuracy in modeling the solar PV module under various weather conditions. The modeling is simulated via using MATLAB/Simulink software. The performance of the selected solar PV module is tested experimentally for differ

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Publication Date
Fri Aug 28 2015
Journal Name
Al-khwarizmi Engineering Journal
wavelength division multiplexing passive optical network modelling using optical system simulator
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Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The simulation shows the behavior of optical

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Publication Date
Sun Mar 01 2026
Journal Name
The Canadian Journal Of Chemical Engineering
Effective soap removal from biodiesel using NiO-doped ZnO nanoparticle adsorbent
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The production of biodiesel generates soap impurities that hinder biodiesel performance and complicate its purification. This study presents a novel approach for soap removal from biodiesel using NiO–doped ZnO nanoparticle (NP) adsorbent. The NPs are synthesized using a gliding arc discharge (GAD) method as a non-thermal plasma source (NTP). NiO doping reduced the bandgap energy by 74%, reduced the crystallite size, and increased the surface area by 78%, entailing lattice strain and structural modifications. Soap removal efficiency was 99.7% for NiO–doped ZnO within 16 min, compared with 95.5% for ZnO. Soap uptake as high as 2320 mg/g NiO–doped ZnO was reported, which could be equally fitted by Langmuir and Freundlich isotherms su

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Publication Date
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

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