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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
Mon Dec 16 2024
Journal Name
Light & Engineering
The Design and Experimental Realization of a Laser-Based Heating System Using Recycled Laser Module
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Laser is a powerful device that has a wide range of applications in fields ranging from materials science and manufacturing to medicine and fibre optic communications. One remarkable

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Publication Date
Thu Nov 02 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Appraising the Role of Pharmacists in Medication Reconciliation at Hospital Discharge: A Field-Based Study
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Objective: To measure the effect of the pharmacist-led medication reconciliation service before hospital discharge on preventing potential medication errors. Methods: This behavioral interventional study took place in a public teaching hospital in Iraq between December 2022 and January 2023. It included inpatients who were taking four or more medications upon discharge from the internal medicine ward and the cardiac care unit. The researcher provided the patients with a medication reconciliation form and reconciliation form (including medication regimen and pharmacist instructions) before discharging them home. Any discrepancies between the patients’ understanding and the actual medication recommendations prescribed by the physici

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Publication Date
Wed Jan 01 2014
Journal Name
The Scientific World Journal
An In Vitro Assessment of Gutta-Percha Coating of New Carrier-Based Root Canal Fillings
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The first aim of this paper was to evaluate the push-out bond strength of the gutta-percha coating of Thermafil and GuttaCore and compare it with that of gutta-percha used to coat an experimental hydroxyapatite/polyethylene (HA/PE) obturator. The second aim was to assess the thickness of gutta-percha around the carriers of GuttaCore and HA/PE obturators using microcomputed tomography (μCT). Ten (size 30) 1 mm thick samples of each group (Thermafil, GuttaCore, and HA/PE) were prepared. An orthodontic wire with a diameter of 0.5 mm was attached to the plunger of an Instron machine in order to allow the push-out testing of the gutta-percha coating. Five samples of (GuttaCore and HA/PE) were scanned using

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Wed Dec 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Finite Element Based Solution of Laplace's Equation Applied to Electrical Activity of the Human Body
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Computer models are used in the study of electrocardiography to provide insight into physiological phenomena that are difficult to measure in the lab or in a clinical environment.

The electrocardiogram is an important tool for the clinician in that it changes characteristically in a number of pathological conditions. Many illnesses can be detected by this measurement. By simulating the electrical activity of the heart one obtains a quantitative relationship between the electrocardiogram and different anomalies.

Because of the inhomogeneous fibrous structure of the heart and the irregular geometries of the body, finite element method is used for studying the electrical properties of the heart.

This work describes t

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Publication Date
Thu Apr 01 2010
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
The Invariant Moments Based With Wavelet Used To Decide the Authintication and Originality of Images
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Publication Date
Fri Dec 30 2022
Journal Name
Journal Of The College Of Education For Women
Constructing Imminent Carcinogenic Attack in English and Arabic Scientific Discourse: A Corpus-Based Contrastive Study
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Cancer is one of the critical health concerns. Health authorities around the world have devoted great attention to cancer and cancer causing factors to achieve control against the increasing rate of cancer. Carcinogens are the most salient factors that are accused of causing a considerable rate of cancer cases. Scientists, in different fields of knowledge, keep warning people of the imminent attack of carcinogens which are surrounding people in the environment and may launch their attack at any moment. The present paper aims to investigate the linguistic construction of the imminent carcinogen attack in English and Arabic scientific discourse. Such an investigation contributes to enhancing the scientists’ awareness of the linguistic co

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Evaluating Filtration and Thermal Stability of Water-Based Mud Using Green Synthesized Zinc Oxide Nanoparticles
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   Nanoparticles (NPs) have unique capabilities that make them an eye-opener opportunity for the upstream oil industry. Their nano-size allows them to flow within reservoir rocks without the fear of retention between micro-sized pores. Incorporating NPs with drilling and completion fluids has proved to be an effective additive that improves various properties such as mud rheology, filtration, thermal conductivity, and wellbore stability. However, the biodegradability of drilling fluid chemicals is becoming a global issue as the discharged wetted cuttings raise toxicity concerns and environmental hazards. Therefore, it is urged to utilize chemicals that tend to break down and susceptible to biodegradation. This research presents the pra

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Publication Date
Thu Dec 28 2023
Journal Name
Farmacia
LASMIDITAN NANOEMULSION BASED IN SITU GEL INTRANASAL DOSAGE FORM: FORMULATION, CHARACTERIZATION AND IN VIVO STUDY
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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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