Nawroz University

The information sharing on behalf of the delivery of the packet in the network router and the original information that is share to the correct person is enabled for the analysis and then the analysis is done. The traffic related problem based on the sharing the information is occur when two or more sis sent in the same routing path. So the packet or the information has been sent using the single router or an execution time delivery for the analysis. The method of novel QoS Routing, fault tolerance is used in this study for the analysis of the system to produce the formation and the analysis of the packet routing. Fault tolerance is used in the deliver the packets without fail and to deliver it in the fast manner. The QoS is used for managing the information or the packets which makes and send the data which is the high priority of the data and the analysis of the dependency is analysed. The finding of the CRAFT related protocol and the efficient routing has been found. Routing system the effective method for the analysis and the protocol transfer has been enabled using the CRAFT method. The suggested system explains the algorithms for enhancing fault detection, fault isolation, data redundancy, robustness against coalescing innovative QoS routing, and fault tolerance improving QoS parameters in the ad-hoc wireless network utilising CRAFT protocol. Compared to the early existing system, fault detection is now three times better. The execution time is 96% faster, and the decreased latency is less than 2 ms. The data redundancy rate is likely about 90% when restricted to the current services, which have improved in terms of resilience by 93%, jitter by 7%, and packet arrival time by over 50 ms per transmission.

The advent of artificial intelligence to the field of education has triggered a change in the way an environment is conceived and built with the objective of allowing adaptive learning. A research focused on the power of AI on adaptive learning contexts are drawn in this study including empirical scenarios and case studies showing transformative concepts at the crossroads of technology and academia. Adaptive learning environments are dynamically personalised educational environments built upon the deployment of artificial intelligence by providing a personalised learning experience for learners. Consequently, these systems include the unique needs and preferences of each learner. Empowered by artificial intelligence, adaptive learning systems are making data-driven decisions based on student performance metrics and then adjust the instructional materials based on techniques such as machine learning, natural language processing, and data analytics. These systems function in real-time, dynamically adjusting not only the complexity of tasks, but also the modality of feedback, as well as additional resources depending on a learner’s progress in their learning and their learning style. This paradigm provides an easy, coherent and effective alternative to traditional one-size-fits-all educational models. Regulatory bodies have also mapped out the use of artificial intelligence in adaptive learning scenarios citing many case studies in this capacity. For example, Knewton and DreamBox offer AI-based personalised learning paths in learning areas such as reading and mathematics. Knewton use of analysis of student interaction to personalise classes and assessments which claim that this technological approach not only increases the engagement of students but also improves their academic performance.

Blockchain technology has revolutionised different industries with the introduction of secure, transparent solutions at the same time keeping them decentralised. In light of an academic record management, blockchain poses a promising answer that offers insurmountable solutions to numerous longstanding problems relating to data security and access. The fundamental advantages, uses, and present difficulties related to blockchain within the educational record management are outlined; stance is also given for potential future exploration. Data security and tampering are both an issue for educational institutions who still preserve student records in centralized repositories. Paper records are vulnerable to various problems such as data breaches and unauthorized forgeries or access which in turn can jeopardize the integrity of the educational credentials. The properties of immutability, transparency and decentralisation provide an effective solution to these problems. Blockchain is a decentralised ledger that keeps track of secure transactions in the form of computers in a network. Each transaction, or block of records, is linked to the previous one forming a near-immutable chain which is protected by cryptographic algorithms. Ensuring educational records such as transcripts, diplomas and certificates are tamper proof and the data stored within this feature is authentic. Key features of blockchain in recording educational data are: single source of truth Reliable and unmanipulable.

Monetary policy and its instruments constitute the fundamental pillar for achieving economic stability, particularly in emerging economies facing persistent structural fluctuations. The problem of this study lies in the volatile effectiveness of traditional monetary policy tools in Turkey amid high inflation and frequent structural breaks, raising a fundamental question about the most influential channel for productive activity. Accordingly, the study aims to measure and analyze the impact of structural changes in monetary policy instruments on economic growth in Turkey during the period (1981–2025). To achieve this, the research adopted the Indicator Saturation Method (ISM) for its ability to identify structural breaks and integrate them into the econometric model, while analyzing variables such as broad money supply, real interest rates, and exchange rates. The key results revealed a weak impact of the broad money supply on growth, in contrast to the pivotal role of the exchange rate channel as a primary driver of economic activity. Furthermore, the model identified significant structural breaks in (2003, 2011, and 2022), reflecting the impact of radical political and economic shifts. The study’s main conclusions and recommendations highlight the limited effectiveness of the "liquidity channel" in high-inflation environments. Therefore, the study recommends that monetary policymakers focus on exchange rate stability and real interest rate management as more efficient tools for stimulating sustainable growth and enhancing economic resilience to future shocks.

Purpose - This study explores how fiscal policy influences economic growth in Iraq during the period 2004–2024, with a particular focus on the challenges faced by oil-dependent economies. Method - To achieve this objective, the study applies the ARDL model to examine both short-term adjustments and long-term relationships using annual time-series data. The analysis includes key macroeconomic variables such as GDP, government expenditure, oil revenues, tax revenues, money supply, and exchange rate. The Phillips–Perron test is used to ensure data stationarity. Result - The results indicate that economic growth in Iraq is closely tied to fluctuations in oil revenues, which largely drive fiscal activity. Government spending follows oil income patterns but shows limited independent impact in the long run. In contrast, non-oil fiscal tools, particularly taxation, play a relatively weak role, reflecting the narrow fiscal base of the economy. Implication - These findings suggest that improving fiscal policy effectiveness requires reducing reliance on oil revenues, strengthening the tax system, and enhancing the efficiency of public spending. Originality - This study presents a comprehensive assessment by combining numerous financial variables within a unified economic model, giving a clearer understanding of how fiscal policy works in a resource-based economy like Iraq. Keywords: Fiscal policy, Economic growth, Oil-dependent economy, ARDL, Iraq