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High Transaction Rates Performance Evaluation for Secure E-government Based on Private Blockchain Scheme
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send rate, blockchain size, batch timeout, organization number, and the number of clients, were modified in the two scenarios. The gradual addition of organizations was also observed to determine the impact of multi-organization on the throughput, latency, and scalability of the system. By increasing the block size to approximately 100 transactions per block, acceptable performance and latency results are attained. The throughput and latency findings are accepted for three or four organizations, but when many organizations are added, throughput and latency begin to suffer from poor performance. Also, many tests show that increased block timeout for high sending rates positively affects the throughput and latency.

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Publication Date
Fri Nov 01 2019
Journal Name
2019 1st International Informatics And Software Engineering Conference (ubmyk)
Radial Basis Function (RBF) Based on Multistage Autoencoders for Intrusion Detection system (IDS)
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In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Modeling and analysis of thermal contrast based on LST algorithm for Baghdad city
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Publication Date
Wed Apr 02 2025
Journal Name
Current Studies On Probability And Statistics
SAR-HDP: Non-parametric Topic Model for Aspect categorisation based on online reviews
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Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Potentiometric Transducers for the Selective Recognition of Risperidone Based on Molecularly Imprinted Polymer
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          Graphite Coated Electrodes (GCE) based on molecularly imprinted polymers were fabricated for the selective potentiometric determination of Risperidone (Ris). The molecularly imprinted (MIP) and nonimprinted (NIP) polymers were synthesized by bulk polymerization using (Ris.) as a template, acrylic acid (AA) and acrylamide (AAm) as monomers, ethylene glycol dimethacrylate (EGDMA) as a cross-linker and benzoyl peroxide (BPO) as an initiator. The imprinted membranes and the non-imprinted membranes were prepared using dioctyl phthalate (DOP) and Dibutylphthalate (DBP) as plasticizers in PVC matrix. The membranes were coated on graphite electrodes. The MIP electrodes using

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Generating a Strong Key for a Stream Cipher Systems Based on Permutation Networks
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The choice of binary Pseudonoise (PN) sequences with specific properties, having long period high complexity, randomness, minimum cross and auto- correlation which are essential for some communication systems. In this research a nonlinear PN generator is introduced . It consists of a combination of basic components like Linear Feedback Shift Register (LFSR), ?-element which is a type of RxR crossbar switches. The period and complexity of a sequence which are generated by the proposed generator are computed and the randomness properties of these sequences are measured by well-known randomness tests.

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Survival estimation for singly type one censored sample based on generalized Rayleigh distribution
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This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.

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Publication Date
Tue Dec 01 2020
Journal Name
Minar International Journal Of Applied Sciences And Technology
INNOVATE GESTATIONAL AGE ESTIMATION MODEL FOR IRAQI FETUSES BASED ON ULTRASOUND IMAGES MEASUREMENTS
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Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify fo

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Publication Date
Tue Oct 08 2019
Journal Name
Asa-cssa-sssa International Annual Meeting
Cover Crop Effects on Soil Health in Organic High Tunnels (2019).
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High tunnels, or unheated plastic greenhouses, are becoming increasingly popular among organic vegetable growers across the United States. However, the intensive production typical of these systems presents soil health challenges, including salinization due to high fertilizer or compost inputs coupled with lack of rainfall to leach salts. Legume cover crops may improve soil health in high tunnels by reducing the need for external inputs, while adding organic matter. We tested the soil health effects of a winter hairy vetch (Vicia villosa Roth) cover crop used to replace fertilizer N in an organic tomato cropping system in high tunnels. Studies were replicated across three sites differing in climate and soil type (Kansas, Kentucky, and Minne

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