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THE ROLE OF DIGITAL TRANSFORMATION IN FINANCIAL REPORTING QUALITY UNDER THE TRUST SERVICES FRAMEWORK
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This study examines the impact of Digital Transformation (DT) on the Financial Reporting Quality (FRQ), taking into account the moderating role of the Trust Services Framework (TSF), in the context of rapid developments in the digital business environment and the resulting challenges and opportunities for accounting and financial systems. To achieve the study objectives, a descriptive–analytical approach was adopted, and a questionnaire was used as the primary data collection instrument. The study sample comprised 87 professionals working in accounting and financial functions. DT was measured through four dimensions: cloud computing, automation, data analytics, and systems integration. FRQ was assessed using the dimensions of accuracy and reliability, timeliness, transparency, and verifiability. The TSF was operationalized through five dimensions: security, availability, processing integrity, confidentiality, and privacy. A five-point Likert scale was employed to measure respondents’ perceptions, and the data were analyzed using descriptive statistics and structural equation modelling to test the study hypotheses. The findings indicate that DT has a statistically significant positive effect on the dimensions of the TSF; however, it does not exert a direct significant effect on FRQ. The results further reveal that availability and processing integrity have a significant positive influence on enhancing FRQ, whereas security, confidentiality, and privacy do not demonstrate a direct significant effect. The study concludes that the impact of DT on FRQ is realized indirectly through selected dimensions of the TSF, underscoring the importance of prioritizing the operational effectiveness of digital systems alongside regulatory and governance considerations.

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Publication Date
Mon May 01 2017
Journal Name
Spectrochimica Acta Part A: Molecular And Biomolecular Spectroscopy
Extraction, preparation and application of pigments from Cordyline fruticosa and Hylocereus polyrhizus as sensitizers for dye-sensitized solar cells
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Publication Date
Tue Jan 21 2025
Journal Name
Applied Biochemistry And Biotechnology
Synthesis and characterization of new (Au, Ru, and Rh) ion complexes and evaluating their activity as anticancer and antioxidants
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Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Engineering
Production of Load Bearing Concrete Masonry Units (blocks) From Green Concrete Containing Plastic Waste and Nano Silica Sand Powder
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Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Thermophysical properties of [EMIM][BF<sub>4</sub>] and [HMIM][PF<sub>6</sub>] imidazolium ionic liquids with MWCNTs
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Abstract<p>In this study, several ionanofluids (INFs) were prepared in order to study their efficiency as a cooling medium at 25 °C. The two-step technique is used to prepare ionanofluid (INF) by dispersing multi-walled carbon nanotubes (MWCNTs) in two concentrations 0.5 and 1 wt% in ionic liquid (IL). Two types of ionic liquids (ILs) were used: hydrophilic represented by 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM][BF<sub>4</sub>] and hydrophobic represented by 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF<sub>6</sub>]. The thermophysical properties of the prepared INFs including thermal conductivity (TC), density and viscosity were measured experimental</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
Preparation, characterization and preliminary cytotoxic evaluation of 6-mercaptopurine-coated biotinylated carbon dots nanoparticles as a drug delivery system
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Publication Date
Fri Mar 10 2017
Journal Name
Superconductor Science And Technology
Conceptual designs of conduction cooled MgB<sub>2</sub> magnets for 1.5 and 3.0 T full body MRI systems
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Publication Date
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
Preparation, characterization and preliminary cytotoxic evaluation of 6-mercaptopurine-coated biotinylated carbon dots nanoparticles as a drug delivery system
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Preparation and characterization of biomass-alumina composite as adsorbent for safranine-o dye from aqueous solution at different temperatures
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Publication Date
Thu Feb 06 2020
Journal Name
Scientific Reports
Waste foundry sand/MgFe-layered double hydroxides composite material for efficient removal of Congo red dye from aqueous solution
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Abstract<p>We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure</p> ... Show More
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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