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Enhancing Privacy and Improving Security in Scalable Blockchain
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Bitcoin is a decentralized blockchain-based cryptocurrency that has taken the world by storm. Since its introduction in 2009, it has grown tremendously in terms of popularity and market cap. The idea of having a decentralized public ledger while maintaining anonymity and security attracted the attention of developers and customers alike. Special nodes in the bitcoin network, called miners, are responsible for making the network secure by using a concept called proof-of-work. A certain degree of anonymity is also maintained as no personally identifiable information of a person, like name, address, etc., is linked to the bitcoin wallet. In terms of bitcoin, a user is anonymous if different interactions of the user cannot be linked to each other or the user. Recent research shows that bitcoin is not as anonymous as it appears to be. The inherently public nature of blockchain technology makes it difficult to achieve privacy. The purpose of this paper is to review how varying degrees of user privacy is maintained in bitcoin cryptocurrency. This paper is divided into two main segments. The first segment explores privacy-enhancing techniques adopted in bitcoin. The second segment critically analyzes these techniques.

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Publication Date
Wed Nov 17 2021
Journal Name
Sustainability
The Role of Accounting Information System and Knowledge Management to Enhancing Organizational Performance in Iraqi SMEs
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Small and Medium Enterprises (SMEs) in Iraq have experienced low performance due to the limited usage of accounting information systems (AIS) and the inability to exploit knowledge of management capabilities (KMC). These deficiencies have led to competitive pressures in the marketplace that have adversely affected their sales and production. This study investigates the role of AIS in terms of operation support, knowledge support, regulatory support, and the role of KMC, including knowledge acquisition, knowledge transfer, and knowledge utilized to enhance organizational performance in Iraqi SMEs. The target population was managers and owners in SMEs using AIS in Iraq’s cities. A non-probability purposive sampling technique was use

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Publication Date
Tue Oct 01 2024
Journal Name
Infrastructures
Enhancing Moisture Damage Resistance in Asphalt Concrete: The Role of Mix Variables, Hydrated Lime and Nanomaterials
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Moisture-induced damage is a serious problem that severely impairs asphaltic pavement and affects road serviceability. This study examined numerous variables in asphalt concrete mixtures to assess their impact on moisture damage resistance. Mix design parameters such as the asphalt content (AC) and aggregate passing sieve No. 4 (PNo. 4) were considered as variables during this study. Additionally, hydrated lime (HL) was utilized as a partial substitute for limestone dust (LS) filler at 1.5% by weight of the aggregate in asphalt concrete mixtures for the surface layer. This study also investigated the potential enhancement of traditional asphalt binders and mixtures by adding nano-additives, specifically nano-silica oxide (NS) and na

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Publication Date
Wed Aug 31 2022
Journal Name
Ieee Access
SHE Networks: Security, Health, and Emergency Networks Traffic Priority Management Based on ML and SDN
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Recently, the increasing demand to transfer data through the Internet has pushed the Internet infrastructure to the nal edge of the ability of these networks. This high demand causes a deciency of rapid response to emergencies and disasters to control or reduce the devastating effects of these disasters. As one of the main cornerstones to address the data trafc forwarding issue, the Internet networks need to impose the highest priority on the special networks: Security, Health, and Emergency (SHE) data trafc. These networks work in closed and private domains to serve a group of users for specic tasks. Our novel proposed network ow priority management based on ML and SDN fullls high control to give the required ow priority to SHE dat

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Intelligent Systems And Internet Of Things
Enhancing Convolutional Neural Network for Image Retrieval
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With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Hydraulic behaviour and improving of water quality of the Chibayish Marshes
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Publication Date
Mon May 02 2022
Journal Name
Neuroquantology
Manufacturing and Improving Engineering Properties of Silica Bricks from Raw Materials
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Refractories are mineral and chemical-, based, materials with excellent heat resistance, making them ideal for use in the construction of ovens, furnace walls industries. According to this our research is concerned to study the effect of addition of (4% CaO) and (5% graphite) on the silica brick properties. Different amounts of CaO and Graphite were included in the white sand (raw ingredients) of silica bricks as a binder to prepare the composition then the composition were sintered using Different sintering temperatures ranging from (1000–1400)𝛐C under static air. Density, thermal conductivity, porosity, and water absorption Compression there was power tested after sintering. XRD analysis was used to identify raw materials’

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of Participatory Budgeting in Improving Performance in light of Covid 19
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The current research aims to analyze the role of participatory budgeting in improving performance, especially during crises such as the Covid-19 crisis. The research used the descriptive analytical method to reach the results by distributing 100 questionnaires to a number of employees in Iraqi joint stock companies and at multiple administrative levels. The research came to several important conclusions, the most important of which is that the bottom-up approach to budgeting produces more achievable budgets than the top-down approach, which is imposed on the company by senior management with much less employee participation. Additionally, there is a better information flow from the lower levels of the organization to the upper management

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Publication Date
Wed Jan 01 2025
Journal Name
Educational Process International Journal
The Role of Artificial Intelligence Applications in Improving Blended Learning in Iraqi Universities
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Publication Date
Fri Mar 31 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
A Cryptosystem for Database Security Based on RC4 Algorithm
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Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Scopus (12)
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