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Secure Smart Contract Based on Blockchain to Prevent the Non-Repudiation Phenomenon
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Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well as to cover the security aspects of digital management and to solve negotiation concerns. The smart contract was employed in creating a distributed ledger to eliminate the need for centralization. In this paper, a simple prototype has been implemented for the smart contract integrated with blockchain which is simulated in a local server with a set of nodes. Several security objectives, such as confidentiality, authorization, integrity, and non-repudiation, have been achieved in the proposed system. Besides, the paper discussed the importance of using the Blockchain technique, and how it contributed to the management of transactions in addition to how it was implemented in highly transparent real-estate scenarios. The smart contract was employed in creating a distributed ledger to eliminate the need for centralization. The elliptic-curve public key has been adopted as an alternative for the RSA in a signature generation/verification process and encryption protocol. For secure transactions, The Secure Socket Layer (SSL) also has been adopted as a secure layer in the web browser. The results have been investigated and evaluated from different aspects and the implementation was in a restricted environment. Experiments showed us the complexity of time and cost when using the (ECC) algorithm and using (RSA) algorithm depending on the size and length of the key. So if the size of the key in (ECC) equals (160) bits, and it corresponds to (1024) bits in (RSA), which is equivalent to 40% for (ECC) and 30% for (RSA). As a result, the (ECC) algorithm is complex, its key is smaller and the process of generating the key is faster, so it has achieved a high level of security.

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Publication Date
Tue Jan 01 2019
Journal Name
Aip Conference Proceedings
Temperature dependence energy distribution function for proton-tritium fusion reaction
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The physical behavior for the energy distribution function (EDF) of the reactant particles depending upon the gases (fuel) temperature are completely described by a physical model covering the global formulas controlling the EDF profile. Results about the energy distribution for the reactant system indicate a standard EDF, in which it’s arrive a steady state form shape and intern lead to fix the optimum selected temperature.

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between robust methods in canonical correlation by using empirical influence function
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       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimation for Two Parameters of Weibull Distribution under Generalized Weighted Loss Function
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In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
New White Method of Parameters and Reliability Estimation for Transmuted Power Function Distribution
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        In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E1 , E2 , E3)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
Spatial Quantile Autoregressive Model: A Review
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This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
An Efficient Algorithm for Fuzzy Linear Fractional Programming Problems via Ranking Function
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In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an

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Publication Date
Sun Jan 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimation for Two Parameters of Gamma Distribution Under Precautionary Loss Function
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In the current study, the researchers have been obtained Bayes estimators for the shape and scale parameters of Gamma distribution under the precautionary loss function, assuming the priors, represented by Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation.

Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of Bayes estimator under precautionary loss function with Gamma and Exponential priors is better than other estimates in all cases.

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Publication Date
Fri Jun 17 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Development of 5-FU Loaded poly lactic-co-glycolic acid Nanoparticles for Treatment of Lung Cancer
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Non-Small Cell Lung Cancer (NSCLC) accounts for about 84% of all lung cancer types diagnosed so far. Every year, regardless of gender, the NSCLC targets many communities worldwide. 5-Fluorouracil (5-FU) is a uracil-analog anticancer compound. This drug tends to annihilate multiple tumour cells. But 5-FU's most significant obstacle is that it gets very easily metabolized in the blood, which eventually leads to lower anticancer activity. Therfore a perfect drug delivery system is needed to overcome all the associated challenges.

In this experiment, an attempt was made to prepare 5-FU loaded poly lactic-co-glycolic acid  nanoparticles using solvent evaporation method and subsequently observed the effect of molecular weight of poly l

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