Volume 7, Special Issue 4 (2026)
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Abstract
The increasing proliferation of artificial intelligence tools in the university environment has led to noticeable changes in learning approaches and the completion of academic tasks, raising debate about their impact on the development of students’ critical and creative thinking skills. While some argue that these tools enhance knowledge production, others contend that they may reduce cognitive effort and independent analytical thinking. This study adopts a descriptive-analytical approach through a questionnaire administered to a random sample of university students from various academic disciplines. The aim is to measure the level of use of artificial intelligence tools and examine the nature of their impact on critical and creative thinking skills, including analysis, inference, problem-solving, and brainstorming. The study also seeks to answer a set of research questions related to the extent of students’ use of AI tools, their contribution to improving higher-order thinking skills, and the presence of statistically significant differences based on selected demographic and academic variables. The findings are expected to contribute to developing a scientific perspective on how artificial intelligence tools can be effectively and responsibly integrated into higher education in a balanced manner that enhances students’ thinking skills without negatively affecting their cognitive independence. Moreover, the results may assist policymakers and universities in designing educational policies that promote the conscious and responsible use of artificial intelligence technologies in the learning process.
Abstract
The rapid advancement of digital technologies has transformed the global higher education landscape, making the transition toward smart universities a strategic necessity rather than a developmental option. Despite ongoing reform efforts in Iraq, higher education institutions continue to face significant challenges related to governance, digital infrastructure, data management, research capacity, and institutional readiness. The research problem stems from the existence of a substantial gap between the current state of Iraqi universities and the requirements of internationally recognized smart university models, which limits their ability to contribute effectively to sustainable development and the knowledge economy. This study aims to analyze the current status of smart university transformation in Iraq through a gap analysis approach and to develop a strategic roadmap that supports the transition process. Using a qualitative analytical methodology, the study examines the Iraqi higher education environment, identifies major transformation gaps, and evaluates key dimensions including governance, digital infrastructure, policy frameworks, pedagogy, research and innovation, stakeholder engagement, financing, and risk management. The findings reveal significant deficiencies in digital readiness, institutional integration, data governance, technological infrastructure, and university–industry collaboration. The study highlights the importance of establishing a coherent national framework that aligns digital transformation initiatives with higher education policies and development priorities. Based on the identified gaps, a comprehensive strategic roadmap is proposed to guide universities and policymakers through a phased transformation process toward smart university implementation. The study contributes to the growing body of knowledge on higher education digital transformation by providing a context-specific framework for Iraq and offering practical policy recommendations to enhance institutional performance, innovation capacity, educational quality, and long-term socio-economic development.
Abstract
This study presents a machine learning-based framework for predicting and analyzing student academic performance using behavioral, psychological, demographic, and digital learning features. The dataset consists of 14,003 student records collected from higher education institutions in 2024 and obtained from Kaggle. It includes 16 variables covering study behaviors, engagement patterns, learning resources, psychological factors, and demographic characteristics. The target variable (response) was Final Grade, which was categorized into four performance levels: Low / Fail / Poor performance, below average performance, Good / Average performance, and Excellent / High performance, representing overall academic performance. Three machine learning algorithms XGBoost (Extreme Gradient Boosting), CatBoost (Categorical Boosting), and Support Vector Machine (SVM) were applied to classify student performance levels. The models were evaluated using confusion matrices, accuracy, F1-score, MCC, R², RMSE, MAE, and feature importance analysis. Results show that XGBoost achieved the highest performance (99.96% accuracy), followed by CatBoost (99.82%) and SVM (98.96%). Analysis of the importance analysis revealed that Exam Score is the most influential predictor across all models. The study highlights the effectiveness of advanced machine learning techniques in predicting academic success and supporting data-driven educational decision-making.
Abstract
The interaction between the nervous and muscular systems, and the enhancement of complex movements that reflect the performance needs in various sports. This research highlights the theoretical frameworks and practical applications in functional training, based on recent scientific evidence published in the last three years. The research focuses on the impact of various functional training patterns, such as exercises based on a specific timing "Every Minute on the Minute" (EMOM), time-based exercises (RFT/FT), exercises aimed at achieving the highest number of rounds (AMRAP), in addition to high-intensity functional training (HIFT), and their effect on specific physiological indicators including: maximum oxygen consumption (VO₂max), blood lactate concentration, respiratory rate response, and heart rate variability (HRV). The research also discusses the implications of applying these training patterns in enhancing fundamental motor skills, such as power output, speed, agility, and balance. The research concludes that functional training achieves measurable improvements in both physiological and skill performance, providing scientific recommendations for its efficient application according to the athlete's experience levels and the needs of their sport.
Abstract
Eggs are a vital food source, rich in protein, vitamins, and minerals. However, egg safety has become a subject of debate. This study aimed to determine the quality standards of eggs collected in the morning and evening from local and commercial chicken breeds in Kurdistan. A total of 240 eggs were collected for quality measurements. 120 eggs were collected from local hens and 120 from commercial hens, with 60 eggs collected in the morning and 60 in the evening for each breed. The weight of the morning eggs was significantly higher from local hens. In commercial hens, significant differences (p<0.05) were observed in egg weight and shell weight. Significant differences (p<0.05) were also observed between local and commercial hens in egg weight, length, shell weight, and thickness. Eggs collected in the morning from local hens showed a significant advantage (p<0.05) in albumin weight, albumin index, and yolk percentage. For commercial chickens, significant differences (p<0.05) were observed in a greater proportion of egg quality characteristics based on whether the eggs were collected in the morning or evening. Specifically, significant differences (p<0.05) were found in albumin height, albumin weight, albumin percentage, albumin index, Howe unit, yolk width, and yolk weight. A statistically significant increase in the number of blood spots was also observed in evening eggs compared to morning eggs in both local and commercial breeds. However, no significant difference was observed between the two breeds. Therefore, it can be concluded that morning eggs have a higher nutritional value than evening eggs.
Abstract
The present study was conducted to explore the usage of differ-ent levels of cumin (Cuminum cyminum) in broiler nutrition. Sixty, (one-day-old) unsexed broiler chicks were randomly divided into four groups of similar mean weight, each with three replicates of five chicks. The control group T1 received a basal diet (fed ration without any supplements). For the other groups T2, T3 and T4, the basal diet was supplemented with 3, 6 and 9 g/kg cumin. The observed variables included growth performance, carcass parts and internal organ weights. Also, Growth performance parameters were measured 4 birds per treatment was slaughtered at the end of the trial to evaluate mus-cle characteristics. Results showed that Cumin did not affect the ob-served variables statistically. However, the best weight gain was ob-served in a 3g/kg Cumin group as compared to other treatments in 42 days of age. Similarly, the best feed conversion ratio was observed in a 3 g/kg Cumin group compared to 6 and 9 g/kg cumin while no sta-tistical difference between was observed in T1 and T2 in 42 days of age. In addition to, numerically higher body weight, feed intake car-cass, breast, thigh and wing weight observed in T2 compared to other treatments in in 42 days of age. Dietary cumin supplementation had not any adverse effects on growth performance, carcass weight, car-cass parts weight and organ weights
Abstract
This research aims to analyze the asymmetric impact of the Global Innovation Index (GII) on Gross Domestic Product (GDP) growth in South Korea over the period (2004–2024). It further explores the potential for adapting this experience within the economies of Iraq, Egypt, and Jordan. Utilizing a Nonlinear Autoregressive Distributed Lag (NARDL) model, the study examines the dynamics of this relationship in both the short and long runs. The empirical findings reveal a nonlinear cointegration relationship, indicating that the South Korean economy exhibits hyper-sensitivity toward negative innovation shocks. Specifically, a 1% negative shock in innovation leads to a growth contraction of approximately 1.65%, whereas the growth response to positive shocks does not exceed 0.33%. Furthermore, CUSUM and CUSUMQ tests confirmed the structural stability of the model over two decades. The research concludes that the innovation gap in the studied Arab countries necessitates policies that support innovation budgets to ensure the stability of structural growth parameters, independent of fluctuations in traditional sectors.
Abstract
The rapid shift towards artificial intelligence and its adoption in educational institutions to manage their educational and administrative affairs has produced large amounts of digital data. The research aims to design an integrated governance framework to protect the privacy of student data, making the commitment to protection a competitive advantage not a functional burden. The research used a comparative analytical approach to analyze institutional reports and documents. Among its findings was that the absence of governance in a smart university transforms data from a strategic asset into a source of risk that threatens the university's reputation. This research presents a model based on three main dimensions P3: political, people, and Platform. This model is applicable to universities that rely on artificial intelligence, unlike previous studies that focused on these dimensions separately to address the problem of student data protection. The shortcoming of those studies lies in the absence of a clear model for the interaction of these three dimensions.
Abstract
The research aims to understand the change in capital structure and its impact on financial stability, clarifying its features for decision-makers, thus enabling them to make sound decisions, especially investors. One of the most important objectives of the research was to determine the financial stability of the research sample during the research period, relying on the Altman model adopted in the financial stability process. The sample included five banks: (Bank of Baghdad, Bank of Babylon, Gulf Bank, United Investment Bank, and Sumer Bank). The research period was from 2015 to 2019. The researchers relied on financial analysis to present the results and clarify the nature of the relationship between the two variables. They reached a number of results, the most important of which is that the change in capital structure leads to an impact on the financial stability of the banks in the research sample. One of the most important recommendations reached by the research is the necessity of maintaining the capital structure from changes affecting it by relying on attracting investors, especially from outside the country.
Abstract
This study aims to build an applied model that explains the impact of strategic planning in activating total quality management to improve academic performance in business schools. To achieve this, the study seeks to explain the basic concepts of strategic planning and total quality management, and to establish the correlational and complementary relationship between them in the educational environment. The study relied on the descriptive analytical approach of previous literature and international standards for academic accreditation. The study concluded that strategic planning represents the basic guiding input, while total quality management provides the executive environment to raise the efficiency of academic performance outcomes (education, scientific research, and accreditation). The study recommends that business schools adopt the proposed model as a comprehensive administrative tool to achieve institutional excellence and keep pace with labor market requirements.
Abstract
This study examines digital transformation in universities and its role in supporting sustainable development and enhancing international trade openness through an econometric analytical study of a sample of developing countries, namely Iraq, Jordan, Saudi Arabia, Morocco, and Tunisia. The study is based on the premise that digital transformation in universities represents one of the most significant contemporary global transformations, exerting a direct influence on human capital development and the international economy. The study aims to analyze the impact of digital transformation in universities on supporting sustainable development and promoting international trade openness in the selected sample countries. To achieve this objective, both descriptive-analytical and quantitative approaches were employed, utilizing appropriate econometric techniques. The findings indicate that university digital transformation has a positive and significant effect on sustainable development and contributes to enhancing international trade openness. Based on these findings, the study recommends strengthening digital infrastructure, establishing a digital framework that supports sustainable digital transformation, increasing investments in university digital transformation, and enhancing digital training and capacity-building programs for academic staff and students in higher education institutions.
Abstract
The current study aimed to experimentally verify the effectiveness of an adapted cognitive-behavioral counseling program in reducing anxiety levels and improving psychological adjustment among adolescents with high-functioning autism spectrum disorder (ASD). The significance of this research stems from the psychological and emotional challenges faced by this demographic. The researcher adopted a quasi-experimental approach using a pre-test/post-test/follow-up control group design. The sample consisted of 60 adolescents who were matched and then randomly assigned to either an experimental or a control group. The experimental group received a program comprising 10 sessions that incorporated techniques such as cognitive restructuring, relaxation training, problem-solving, and social skills development. Results from the Analysis of Covariance (ANCOVA) revealed statistically significant differences at the level of (α≤0.05) favoring the experimental group in both anxiety (F=24.18, p=0.001, d=1.12) and psychological adjustment (F=18.76, p=0.001, d=0.96). Furthermore, mixed analysis confirmed the sustainability of the therapeutic effect in the follow-up measurement. These findings support the recommendation to adopt such adapted programs in educational institutions and specialized centers to enhance the mental health and quality of life for this population.
Abstract
This research aimed to identify the relationship between digital transformation, with its dimensions of technological infrastructure, legislation, policies, digital skills, and availability of necessary funding, and intellectual capital, with its dimensions of human capital, organizational capital, and relational capital. The study employed a deductive correlational approach. It also aimed to reveal the importance of intellectual capital and its essential components that contribute to developing and enhancing financial performance. The study population consisted of employees of Imam Al-Kadhim College (peace be upon him). The researchers designed a questionnaire comprising 22 items for each of the research variables, with 11 items for each variable. Data was collected from a sample of 30 employees of Imam Al-Kadhim College (peace be upon him). Based on this data, the data was analyzed and the hypothesis tested using statistical tools. The researchers distributed 30 questionnaires to the research sample in the Accounting Department, as it is the main department in the college, encompassing multiple specializations in management and economics. The researchers used several statistical methods to achieve the research objectives, including Pearson correlation coefficient analysis and simple regression analysis, to prove the research hypotheses through data analysis. The researchers reached several conclusions, most notably that while intellectual capital is important for the research sample, its presence in the financial statements and reports of the college under study was limited, as it still uses traditional methods and focuses primarily on material and financial matters.
Abstract
This study aimed to measure the impact of digital transformation on the financial performance of the Iraqi banking sector during the period (2020–2025). To achieve the objectives of the study, the descriptive-analytical approach was adopted through the analysis of financial data obtained from a sample of Iraqi banks under investigation. In parallel, a quantitative approach was employed using a questionnaire administered to a sample of (777) respondents. The results revealed a statistically significant statistically significant association between digital transformation variables, represented by digital services, artificial intelligence, and technological platforms, and financial performance indicators, namely Return on Assets (ROA) and Return on Equity (ROE). The findings also indicated that digital transformation contributes effectively to reducing operating costs and enhancing the operational efficiency of the surveyed banks. Based on these findings, the study proposed a set of recommendations focusing on the necessity of strengthening digital infrastructure, intensifying specialized training programs for human resources, and developing cybersecurity frameworks to ensure the sustainability of financial performance within the rapidly evolving digital environment.
Abstract
This study aims to examine the impact of enlightened marketing on improving product quality through an exploratory study of the opinions of a sample of customers of Al-Rasheed Bank / Al-Kufa Branch. Enlightened marketing is based on fundamental principles, including focusing on customer needs, transparency, social responsibility, and providing genuine and sustainable value. The study sought to identify the extent to which the bank adopts enlightened marketing practices and the extent to which this is reflected in the quality of banking services provided. The study adopted a descriptive-analytical approach, using a questionnaire distributed to a number of customers to collect data concerning their perceptions of the level of product quality and its alignment with their expectations. The data were analyzed using appropriate statistical methods to test the research hypotheses. The results revealed a statistically significant positive relationship between the application of enlightened marketing principles and the improvement of banking service quality. This approach contributes to enhancing customer trust, increasing customer satisfaction, and improving their banking experience. The study also demonstrated that paying attention to customer feedback and responding to it effectively contributes to the continuous development of product quality. The study concluded that banks should adopt the concept of enlightened marketing as a strategic approach to improving the quality of their services and enhancing their competitiveness in the market. To achieve the objectives of the study, 33 questionnaires were distributed to a sample of employees of the bank.
Abstract
The current research aims to study the reality of the transition towards metaphysical education in Iraqi academic educational institutions, through analyzing the opportunities, challenges and strategic requirements associated with the application of metaphysical technologies in university education, based on the opinions of faculty members at the University of Kufa, and emphasizes the importance of research from the growing global interest in virtual reality and augmented reality technologies and immersive digital environments, and what they can provide great potential in developing the educational process and improving the quality of learning and academic interaction. The research was based on the descriptive-analytical approach for its suitability to the nature of the subject, and the questionnaire was used as the main tool for data collection, as it included three main axes, which were the opportunities for applying the Metaverse, the challenges of application, the strategic vision and readiness for transformation towards metaphysical education. The research community included faculty members and academic staff at the University of Kufa, and an intentional sample of teachers interested in digital transformation and modern educational technologies was selected. The research has reached a set of important results, most notably, there is a high positive trend towards the adoption of Metaverse technologies in university education, because of its ability to enhance interactive and immersive learning, develop students ' skills, improve the educational environment, as well as support academic innovation and expand learning opportunities without time or spatial restrictions .therefore, the results showed the existence of technical, financial, organizational and human challenges that may hinder the actual application of these technologies, including poor infrastructure, high hardware costs, lack of technical support, privacy concerns and legislation. The research stressed the importance of having a clear strategic vision for digital transformation, including the development of infrastructure, the provision of financial support, the qualification of academic cadres, the modernization of educational systems and legislation related to virtual environments, and the research ended with a set of recommendations, the most important of which is the need to adopt a comprehensive strategy for the transformation towards metaphysical education, strengthening partnerships with global technology companies, and the implementation of pilot projects before expanding the comprehensive application.
Abstract
This study aimed to examine the role of internal auditing in enhancing the dimensions of digital governance—namely digital transparency, digital accountability, digital risk management, and digital compliance—in Iraqi commercial banks amid the challenges associated with rapid digital transformation. To achieve the study objectives, the researchers adopted a descriptive-analytical approach by designing and distributing a questionnaire to a sample of employees working in the banking sector. The collected data were analysed using appropriate statistical methods. The findings revealed a statistically significant effect of internal auditing on enhancing all dimensions of digital governance. The results indicated that the role of internal auditing extends beyond its traditional supervisory function to become a strategic driver that contributes to improving the quality of digital information, clarifying responsibilities, enabling the early detection of operational and cybersecurity risks, and ensuring compliance with regulatory requirements and technological policies. Based on these findings, the study emphasized the necessity of developing the competencies of internal audit personnel in the fields of modern technologies and cybersecurity, as well as activating electronic auditing systems. The study also highlighted the importance of support from top management in establishing a robust digital infrastructure. Furthermore, it recommended updating banking regulations and establishing specialized digital audit units to ensure the integration of oversight mechanisms with digital transformation requirements. Such measures would enhance the stability of the Iraqi banking sector and strengthen the confidence of all stakeholders in the digital banking environment.
Abstract
The current research aims to study the reality of digital transformation among middle school students. The researcher developed a digital transformation reality scale based on the technology acceptance model. The scale consists of (15) items, with the response options being (agree, sometimes, often). After applying the scale to a sample of (400) male and female middle school students and processing the data using appropriate statistical methods, the research concluded that the middle school students in general demonstrate a high level of digital transformation use. Statistically significant differences in digital transformation were found according to the gender variable (male, female) and the specialization variable (scientific, literary). In light of these results, a number of conclusions, recommendations, and suggestions were formulated.
Abstract
Breast cancer is one of the most prevalent and life-threatening diseases worldwide, making early and accurate diagnosis essential for improving patient outcomes. This study aims to evaluate the performance of two machine learning models, Extreme Gradient Boosting (XGBoost) and Gaussian Naive Bayes, for breast cancer classification using the Breast Cancer Wisconsin Diagnostic dataset. A comparative analysis was conducted based on several performance metrics, including Accuracy, Precision, Recall, F1-score, Specificity, Receiver Operating Characteristic (ROC) curve, Area Under the Curve (AUC), Balanced Accuracy, and Confusion Matrix. In addition, feature importance analysis was performed to identify the most influential variables contributing to the classification process. The experimental results demonstrated that both models achieved high classification performance. However, the Gaussian Naive Bayes model showed slightly superior performance, achieving an Accuracy of 96.5% and an AUC of 0.997, compared with 96.0% and 0.993, respectively, for the XGBoost model. Furthermore, the analysis revealed that features related to tumor morphology, particularly concave points mean, perimeter worst, and radius worst, were among the most influential predictors of breast cancer classification. The findings indicate that both machine learning models provide reliable and effective tools for supporting early breast cancer diagnosis, with Gaussian Naive Bayes demonstrating a slight advantage for the dataset used in this study. These results highlight the potential of machine learning techniques to enhance diagnostic accuracy and support clinical decision-making.
Abstract
This study aims to analyze the role of reengineering digital thinking among university leaders and their belief in digital transformation in creating and adopting the smart university, which keeps pace with developments in artificial intelligence and digital tools. These represent some of the most important dimensions of digital transformation in an era in which digitalization has become one of the most significant competitive priorities. University leaders should therefore incorporate digital readiness into their strategic plans to ensure that the university completes the requirements of digital transformation, reaches the stage of becoming a smart university, and moves beyond traditional practices. Given the importance of reengineering leadership mindsets to foster belief in digitalization within higher education institutions and the need for universities to keep pace with rapid technological changes, the study problem was formulated around the question of the extent to which reengineering digital thinking among university leaders contributes to enhancing universities' digital readiness in a manner that supports the adoption of smart university dimensions and the achievement of the requirements of modern university transformation. The study adopted a descriptive-analytical approach. Its population and sample consisted of university leaders, including college deans, assistant deans, and heads of departments. A total of 73 valid responses were obtained for analysis. The study was based on three main variables. The first variable was reengineering digital thinking, comprising the following dimensions: leadership's belief in digital transformation, strategic digital vision, data-driven thinking, rapid responsiveness to digital changes, digital knowledge sharing, and digital skills updating. The second variable was digital readiness, comprising the dimensions of digital foresight, agile organizational structure, digital governance, digital competencies, and digital proactivity. The third variable was the smart university, comprising the dimensions of smart infrastructure, smart education, smart digital administration, smart services, digital innovation, and smart core capabilities of faculty members. The study found a significant correlation and significant effect between reengineering digital thinking and digital readiness. It also revealed a significant effect of digital readiness on the adoption of the smart university. These findings indicate that developing and reengineering digital thinking among university leaders contributes effectively to enhancing the level of digital readiness of universities, which, in turn, positively affects their ability to adopt smart university systems and improve the efficiency of academic and educational performance. The results also demonstrated that strategic digital vision, data-driven thinking, and digital skills updating are among the most influential dimensions in supporting the transition toward the smart university. The study recommends that universities adopt specialized programs for reengineering the digital thinking of university leaders, strengthen digital governance, develop smart infrastructure, invest in developing digital competencies, and foster a culture of digital innovation. Such initiatives would contribute to the transition toward smart universities and enhance their competitiveness and sustainability in the contemporary higher education environment.
Abstract
The integration of smart technologies into higher education is rapidly reshaping traditional teaching and learning environments. This study investigates differences in academic performance between students utilizing AI technologies and those who do not, spanning three educational levels: undergraduate, graduate, and postgraduate. Using a simulated dataset of 200 participants, the analysis employed independent sample t-tests, chi-square tests, regression models, correlation analyses, and visualizations such as scatter plots. The findings consistently demonstrate that students who adopt AI significantly outperform their peers, with notable statistical improvements across all groups. Additionally, factors like educational level and age were found to influence outcomes, with younger students and AI users showing greater consistency and higher achievement. Beyond presenting numerical data, the research contextualizes these results within modern digital learning theories, addresses challenges in technological integration, and offers practical recommendations for effectively incorporating AI tools into higher education frameworks.
Abstract
Managing network infrastructure resilience under hostile conditions is a fundamental priority for modern smart university ecosystems. This paper introduces an advanced analytical framework to model and quantify the resilience of hybrid networks protected by Shamir Secret Sharing and Diffie-Hellman cryptographic protocols under intelligent targeted cyber-attacks. The network architecture incorporates a primary hybrid path operating under a 4-out-of-5 threshold logic alongside an independent fallback path managed by a backup componentB_6. A rigorous mathematical derivation using probability theory establishes the joint availability equations for both normal operation and targeted strategic strikes, where an attacker specifically aims to compromise vital edge components B_1andB_5. To validate the closed-form reliability expressions, a robust Monte Carlo simulation with 10^5 iterations was executed in MATLAB. The numerical findings demonstrate that while targeted attacks reduce the primary path's capacity to zero, the independent backup mechanism successfully preserves data-flow continuity and encryption integrity, maintaining a steady system availability floor of R_(sys.)≥ 0.90. These insights provide concrete engineering design criteria for implementing fault-tolerant secure data pathways in digital academic institutions.
Abstract
This study aimed to examine the impact of internal auditing on the transparency of financial reports in companies listed on the Baghdad Stock Exchange. The study sought to identify the nature of the relationship between the effectiveness of internal auditing and financial reporting transparency, measure the effect of internal audit independence on the credibility of financial information, and determine its role in reducing accounting errors and financial manipulation. The study adopted a descriptive-analytical approach and used a questionnaire as the primary tool for data collection. The sample consisted of employees working in auditing, accounting, administrative departments, and other stakeholders concerned with financial reporting. A total of 259 valid questionnaires were collected and analysed. Appropriate statistical methods, including the Chi-Square test, were employed to evaluate the study hypotheses. The findings revealed a statistically significant relationship between internal auditing and the transparency of financial reports. The results also indicated that the independence of internal auditors, their direct reporting relationship with the board of directors, and their unrestricted access to financial records and information significantly enhance the credibility and transparency of financial reporting. Furthermore, the study confirmed that internal auditing plays a significant role in reducing accounting errors and financial manipulation, improving the quality of financial disclosure, and supporting management in making sound financial decisions. The study concluded that internal auditing is an effective control and managerial tool that contributes to strengthening transparency, accountability, and the quality of financial reporting in companies listed on the Baghdad Stock Exchange. The study recommends enhancing the independence of internal audit units, providing adequate support and resources, adhering to international professional standards, and continuously developing the competencies of internal auditors to increase confidence in financial reports and improve the investment environment.
Abstract
Smart universities constitute a complex environment in which thousands of Internet of Things (IoT) devices are interconnected, rendering them an increasingly attractive target for sophisticated cyberattacks. This study aims to design an integrated framework combining Artificial Intelligence (AI) and IoT technologies for the early detection of cyberattacks within smart university environments, employing machine learning and deep learning algorithms — namely Random Forest and a hybrid CNN-LSTM model — to classify network traffic and detect anomalous patterns in real time. The study adopted a descriptive-analytical approach supported by a field questionnaire administered to a sample of 150 participants from IT and network security personnel across universities. Results revealed excellent questionnaire reliability (Cronbach's Alpha = 0.927) and a strong positive correlation (r = 0.674) between cybersecurity awareness and AI detection effectiveness, alongside the superiority of the proposed model over traditional systems by an accuracy margin of approximately 25 percentage points (96.3% vs. 71.2%). The study recommends adopting a five-layer architectural framework integrating IoT devices, data processing, AI inference, attack detection, and real-time response layers as a viable model for deployment in Arab smart universities.
Abstract
This paper reviews the growing role of AI in accelerating the discovery and design of inorganic nanomaterials for sustainable development through a six-stage pipeline: Data → AI → Prediction → Design → Fabrication → Application. Using a critical-analytical approach supported by quantitative metrics (99.99% correlation for TiO₂ band gap, screening of >10 million oxides, >2 compounds/day at A-Lab), it systematically compares ML, DL, and GNN techniques, alongside DFT-based high-throughput screening, inverse design, active learning, and self-driving laboratories. Based on 30 peer-reviewed references (2013–2026) selected using PRISMA guidelines from Scopus, Web of Science, and Google Scholar.
Abstract
Rapid evolution of the Internet of Things (IoT) has transformed the urban infrastructure because it is possible to interconnect systems that can improve transportation, healthcare, security, energy management, and public services. Implementation of IoT network in Iraqi cities faces numerous constraints including lack of infrastructural development, network saturation, unstable connections, poor cybersecurity and lack of resource management. These factors largely affect dependability and functionality of smart city applications. This paper examined how Artificial Intelligence (AI) methods applied to improve IoT network performance in Iraqi cities through effective data routing, predictive maintenance, anomaly detection, bandwidth optimization, and intelligent resource management. Machine learning, Deep Learning and reinforcement learning methods were commonly used methods to address the conditions of dynamic networks and maximize operational efficiency. The study aims at the application of AI techniques to strengthen current IoT systems to enhance scalability, minimize latency, enhance security, and energy efficiency. The research, based on analytical modeling and comparative performance analysis, shows that AI-based IoT systems significantly improve technological resilience of cities and assist Iraq in the development of smart cities. The results offer viable advice to policy makers, network engineers and urban planners who wish to develop modern cities in Iraq using intelligent technology.
Abstract
In this work, we do a comprehensive examination of the mechanisms of magneto-optical amplification in silicon nanostructured photodetectors, including laser-assisted fabrication and coupling with an external magnetic field. The performance of photodetectors is improved by the crystallinity of Au@Pb core-shell nanoparticles being greatly improved by pulsed laser ablation in liquid (PLAL) under magnetic field. The experimental results demonstrate that the responsivity is enhanced from 0.220 A/W to 0.445 A/W at 550 nm with an external quantum efficiency (EQE) of 95% and a specific detectivity of 2.1 × 1013 Jones with the applied magnetic field of 0.3 T. The primary physical processes are the change of hot electron trajectories by Lorentz force, giant magnetoresistance (GMR) in hybrid metal-semiconductor devices and the Purcell enhancement in magneto-dielectric nanostructures. This work offers the theoretical and practical framework for next-generation silicon-compatible magneto-optical detectors for quantum sensing, optical magnetometry and weak-signal detection
Abstract
Standard multilayer dielectric beam splitter is limited by spectrum interference ripples, high production complexity and strict tolerance of the thickness. Here we report a compositionally tuned TiO2-SiO2 mixed dielectric thin film as an effective single-layer broadband beam splitter. The composite films were produced on glass substrates with pulsed laser deposition (PLD) which allowed fine control over layer thickness and equilibrium stoichiometry by varying the number of laser pulses. The TiO₂:SiO₂ ratio was optimized using the effective medium model of Lorentz-Lorenz to attain a refractive index in between (~1.95-2.05) for controlled amplitude division with no multilayer interference stacking. X-ray diffraction (XRD) study revealed a nanostructured mixed-phase morphology using crystallite sizes in the range of 16-46 nm, ideal for low-scattering optical applications. The transmission-reflection ratios were steady and adjustable from 65/35 to 80/20 with small spectral ripples (ΔT_ripple < 4%) as demonstrated by UV–Vis–NIR spectroscopy in the range 400–1100 nm. The experimental results agree well with transfer matrix method (TMM) simulations, which validates the effective refractive index technique. The suggested single-layer design outperforms existing multilayer designs in terms of structural complexity, thickness sensitivity and number of manufacturing processes, while maintaining broadband and spectrally flat optical performance. Here, we show a simple and scalable way to achieve broadband beam splitting by changing the refractive index in a single dielectric layer.
Abstract
The social responsibility of emerging organizations refers to the obligation of management to consider and respond to issues that extend beyond the organization’s administrative, economic, and legal requirements, in a manner consistent with social values and cultural tolerance. Management is composed of individuals who are responsible for routine decision-making and for formulating and implementing organizational policies. Accordingly, it can be argued that the ethical ideals and beliefs of these individuals, particularly their personal values, play an important role in shaping their decisions. Therefore, this study focuses on how cultural tolerance within organizations can contribute to creating and maintaining organizational cultures and a sense of social responsibility. These organizational cultures emphasize ensuring environmental and social sustainability. The study highlights the need for managers to pay greater attention to organizational social responsibility, particularly with regard to the influence of their personal values on their work through cultural tolerance. The first part discusses the concept of cultural tolerance and the relationship between values and organizational cultures within the context of Iraqi society. The second part provides a brief review of organizational social responsibility and explores the perceptions of participating managers, identifying the main thematic patterns embodied and adopted to achieve organizational objectives
Abstract
This study investigates the impact of Internet of Things (IoT) technologies on enhancing academic interaction between students and faculty members in higher education institutions, with an in-depth comparative analysis of the Iraqi context in relation to the Arab and global contexts. The study adopts a descriptive-analytical approach based on a literature review and comparative analysis, supported by statistical charts and a field survey. The findings revealed that IoT-enabled smart classrooms improved interaction indicators by between 10% and 96%. The global market reached USD 14.24 billion in 2024 and is projected to reach USD 48.26 billion by 2033, representing a compound annual growth rate of 15.3%. In contrast, the adoption rate of IoT in Iraqi public universities does not exceed 18%, compared with 68% globally, revealing a structural gap that requires urgent strategic intervention.
Abstract
In light of the rapid digital transformation that has reshaped the educational landscape, smart learning technologies have emerged as one of the most significant contemporary trends that higher education institutions seek to adopt in order to enhance the quality of the educational process and improve both academic and administrative performance. The adoption of these technologies is no longer viewed as merely a developmental option; rather, it has become a strategic necessity driven by the demands of the contemporary educational environment and continuous technological advancements. Accordingly, this study aims to examine the adoption of smart learning technologies as the dependent variable through four dimensions: smart technological compatibility, performance expectancy, interaction, and institutional support, which collectively reflect the readiness and capability of educational institutions to effectively utilize modern technologies in supporting teaching and learning processes. Conversely, organizational mindfulness is examined as the independent variable through its five dimensions: preoccupation with failure, reluctance to simplify interpretations, sensitivity to operations, commitment to resilience, and deference to expertise. These dimensions enhance the institution's ability to anticipate organizational and technological changes and respond to them proactively and effectively. The significance of this study stems from the uniqueness of its empirical context within the Zakho Independent Administration, which is currently pursuing an ambitious vision for institutional development and educational modernization. The Technical College and Technical Institute in Zakho represent key pillars in supporting this transformation toward a more advanced and sustainable educational environment. The study adopted a descriptive-analytical research design and targeted a purposive sample of 82 faculty members and administrative leaders from the Technical College and Technical Institute in Zakho. To ensure the robustness and accuracy of the findings, Structural Equation Modeling (SEM) was employed using Smart PLS software to test the proposed hypotheses. The findings are expected to demonstrate that organizational mindfulness serves as a fundamental organizational capability that facilitates the successful adoption of smart learning technologies. Furthermore, the study provides a scientific framework that can support educational decision-makers in developing smart learning environments capable of meeting future educational challenges and promoting sustainable development within the region.
Abstract
The primary objective of this study is to verify the effect of smart strategies on achieving organizational excellence at Zain Telecommunications Company. The researcher adopts the descriptive analytical approach in conducting the survey to achieve the study objectives. The researcher relied on two main tools in collecting data, namely the questionnaire and interviews, and distributed (80) questionnaires to the employees of Zain Company, but the valid for statistical analysis (73) and determine the sample in addition to identify the demographics of the sample (age - gender - educational qualification - years of service - job title) and verbal statements of their opinions about the smart strategies (continuous learning, technological integration, understanding the environment, strategic adaptation) as well as the organizational excellence (organizational excellence is measured by a set of variables, namely performance results, customer focus, internal processes, continuous improvement. The most important conclusions of the study were that strategic skills have a positive impact on achieving organizational excellence in Zain Telecommunications Company. Two-tailed test results on the correlation between smart strategies and organizational excellence show a strong positive correlation. A smart strategy will significantly impact organizational excellence. A high level of smart strategies will have a high level of organizational excellence and vice versa. Smart strategies are the driving force of change in the organization. Its positive impact on organizational excellence must be sufficiently emphasized and enhanced in the organization. The most important recommendations of the study are that Zain Company should work to create a collaborative multi-dimensional work environment to improve the performance of its employees and earn their satisfaction, and Zain Company should take into consideration the idea of sharing some responsibilities with its employees and providing them with the opportunity to make decisions, in order to improve skills and increase the sense of belonging, as well as putting more effort to apply digitization in all departments and workstations.