Search Results for ai-applications

Abstract

This research aims to explore the modern marketing of drugs through smartphone applications, focusing on the mechanisms of reaching and influencing consumers. With the rapid technological advancement and the widespread use of smartphones, these devices have become a powerful tool exploited for illegal purposes, such as drug promotion. The research examines how drug dealers utilize modern technologies, including encryption and targeted advertising, to reach a wide audience while maintaining the confidentiality of their operations. The study reviews the digital methods employed in this field and analyzes their impact on consumer behavior from psychological and social perspectives. Additionally, the research addresses the role of applications and digital platforms in facilitating this type of illegal marketing and how personal data and artificial intelligence algorithms are exploited to attract customers. Through data analysis and a review of previous literature, the research provides a comprehensive view of the ways drug dealers adapt to the rapidly changing digital environment and how they target specific consumer groups. Ultimately, the research aims to offer practical recommendations that help develop effective strategies to reduce the impact of this type of marketing on society, emphasizing the need to strengthen digital oversight and raise public awareness of the risks of exploiting technology for illegal activities.

Abstract

This study highlights the statement that contributes to the use of information technology applications on Narner in achieving the marketing strategy and did not participate in the search for the descriptive analytical approach in completing the study and answering the main question (Since Narner contributed to the research of information technology when building its marketing? The data was collected by a questionnaire prepared for this agricultural field, as I had conducted an innovative study of ((96) employees (46) employees in Abu Dhabi Bank and (50) employees in a Turkish agricultural bank) working within the researched nick and conducted research in analyzing the questionnaire directors statistically and processing it through the program (SPSS) version 26).

The study reached a set of conclusions, the most prominent of which are: Information technology applications are one of the most important systems that contribute to helping bank management make appropriate decisions for the purpose of achieving a sustainable marketing strategy and choosing the appropriate strategy for it, as information technology keeps pace with the changes that occur in the markets and tracks its movements and sustainable strategies and the availability of important information about customer trends and desires. Thus, it contributes to developing appropriate solutions that help achieve the bank's goals.

Based on the above, we recommend: paying equal attention to all dimensions of information technology (technical, administrative, behavioral, economic, strategic), as it is a complementary activity to each other, and it is not possible to ignore any of them and focus on one of them, as the key to success is the necessity of paying full attention to all its dimensions.

Abstract

Given the importance of human capital in keeping pace with the rapid changes in the business environment, particularly those related to technological developments and their applications across various fields, including auditing and the need for professional performance to analyze data from audited institutions, there is a pressing need to identify and develop human capital based on the efficiency of artificial intelligence and its data analytics technologies. Accordingly, the current study aims to demonstrate the importance of human capital development and its significance in educational institutions. The study adopted a descriptive-analytical approach. The research population consisted of accounting employees at Al-Nahrain University in Baghdad Governorate, with a sample size of 55 respondents. The study reached the following conclusions: 1. Al-Nahrain University places considerable emphasis on developing human capital and demonstrates efficiency in using artificial intelligence applications for big data analysis. 2. Al-Nahrain University is efficient in utilizing artificial intelligence applications to analyze big data. The researcher recommends the following: 1. Increasing attention to human capital development, given its significant impact on the efficiency of using artificial intelligence applications in big data analysis. 2. Conducting further research on the impact of human capital development on the efficiency of big data analysis in auditing and electronic accounting practices.

Abstract

Artificial intelligence (AI) applications are essential for enhancing payment security and improving customer experience in financial institutions. This research aims to examine the challenges faced by Mastercard in Australia and Visa in Singapore in implementing these technologies. The study focuses on three main areas: challenges related to fraud and privacy, the strategies employed by both companies to address these challenges, and the impact of AI applications on customer satisfaction and trust. The research adopts an analytical methodology that combines both qualitative and quantitative data, relying on diverse sources including academic studies and annual reports. The findings reveal that the effectiveness of AI applications varies across the two markets, reflecting different responses to local challenges. For instance, Mastercard demonstrates a greater reliance on machine learning technologies in Australia to combat fraud, while Visa in Singapore focuses more on enhancing privacy and data protection. The study offers strategic recommendations aimed at improving payment security and customer experience, such as increasing transparency in data usage and strengthening communication with customers. This research contributes to a deeper understanding of the role of AI in financial services, providing valuable insights for companies and practitioners in the sector. By addressing the unique challenges of each market, customer satisfaction can be enhanced and greater trust in digital payment services can be fostered.

Abstract

Given the swift digital changes occurring in the Banking industry, the purpose of this paper is to examine how well artificial intelligence systems can forecast and protect against future disasters.  By utilizing its skills in big data analytics, forecasting financial behavior, and more accurately and effectively managing risks, artificial intelligence (AI) is increasingly regarded as a crucial component in the development of banking systems and improving their operational efficiency.

 By enhancing client satisfaction, tailoring banking services to meet the demands of each individual, and cutting down on operational errors and administrative expenses, banks hope to gain a competitive edge by utilizing these technologies.  AI also helps to speed up credit decisions, make it possible to identify financial crime early, and create clever marketing plans based on forecasts of future market trends.

In order to ensure financial sustainability and achieve integration between digital transformation and the demands of banking innovation, studies show that the future of AI encompasses strategic, cultural, human, technological, and organizational dimensions in addition to technical ones.

 The paper also examined a number of anticipated long-term effects of AI applications, such as increased forecasting precision, lower operating expenses, better customer satisfaction, increased worker productivity, and assistance with investment choices.  The findings show that implementing AI applications in the banking sector is a strategic requirement to guarantee long-term growth and competitiveness in the digital era, not a technical luxury.

In order to enhance lending decisions and lower default risks, the paper also assesses how well a number of categorization algorithms work in assessing loan applicants' creditworthiness.  Using a dataset that represented the traits and financial activities of clients, seven machine learning techniques were used: Gradient Boosting, Random Forest, Extra Trees, Gaussian Naive Bayes, Logistic Regression, SVC-RBF, and KNN.

The paper used a database of 21 variables for loan applicants. Numerical variables included (age, income, credit score, debt-to-income ratio, and loan amount). Descriptive variables included (loan purpose, region, marital status, employer, educational level, and application channel). Binary variables included (whether or not the applicant had a history of default). These variables were used to predict the approval or rejection decision, with the dependent variable being represented by two values: 0 for rejection and 1 for approval.

The models were evaluated using the following six key performance indicators: Accuracy, Precision, Recall, F1 Score, Receiver Operating Characteristic Area Under the Curve (ROC AUC), and Brier Score.   The findings demonstrated that the Gradient Boosting algorithm performed best overall in both probability prediction quality and customer differentiation across different risk levels.  The Random Forest algorithm, which showed stability and balanced metrics, came next.  On the other hand, despite its moderate performance, Logistic Regression provided great interpretability, while the Gaussian Naive Bayes algorithm demonstrated high sensitivity in identifying high-risk customers.  In terms of overall accuracy and probability quality, some models—like SVC-RBF and KNN—performed worse.

Abstract

The study addresses the nature of the intertwined and integrated relationship between the organizational health of business organizations in the Iraqi tourism sector and strategic immunity, according to what these variables witness from the emergence of artificial intelligence with its capabilities and driving powers in supporting the organizational environment to predict potential risks and challenges during future periods, as well as increasing the level of transparency in the business environment and improving the integration of artificial intelligence in the organizational circle, starting from planning and passing through describing the nature of internal processes, reaching the achievement of targeted institutional goals. Thus, the three variables: artificial intelligence, strategic immunity, and organizational health are no longer just individual concepts, but have become institutionalized strategic tools prepared for the future.

One of the most important determinants of the current study lies in addressing an underexplored research area. To the best of our knowledge, there is a notable scarcity of prior studies that integrate strategic immunity, organizational health, artificial intelligence, and organizational culture within a unified framework. Existing Arab and international studies tend to examine these dimensions separately, rather than as interconnected drivers of digital organizational resilience.

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

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

This research addresses the extent of digital transformation in the Iraqi banking sector, with a focus on a selected sample of Iraqi private banks. The research addresses the extent to which these banks adopt digital technologies to enhance their operations and customer services through quantitative analysis. The results reveal that although there is a growing interest in digital transformation Among Iraqi banks, the digital transformation in Iraqi private banks is still in its early stages compared to global trends. Although there is a growing recognition of the importance of digital technologies by banks, many of them still rely heavily on traditional banking methods, and this is due to This disparity is largely due to different levels of investment in digital infrastructure and different degrees of openness to technological change among bank management, and adoption rates remain uneven across the banking sector. This disparity is largely due to different levels of investment in digital infrastructure and different degrees of openness to technological change among bank management.

Despite these challenges, many banks have begun to implement digital solutions such as online banking, mobile applications and electronic payment systems to meet evolving customer expectations and increase competitiveness. This research highlights the need for strategic investment in digital infrastructure and regulatory reforms to enhance the environment. Conducive to digital innovation, it also emphasizes the importance of educating and raising awareness among customers to increase the adoption of digital banking services, which ultimately contributes to the modernization and growth of the sector.

Abstract

The aim of the research is to clarify the role that artificial intelligence can play in contributing to improving financial performance and achieving a sustainable competitive advantage for economic units. The research was adopted on the descriptive analytical method through the analysis of intellectual literature and relevant previous studies, as well as reviewing the most prominent applications of artificial intelligence in the field of accounting, such as the intelligent automation of receipt and disbursement processes. The most prominent conclusions reached were that the use of artificial intelligence tools contributes to achieving a sustainable competitive advantage by reducing operational costs, raising the efficiency of financial performance, which is reflected positively on the financial performance of economic units. The research recommends the necessity of adopting clear strategies for the application of artificial intelligence tools, developing the digital infrastructure, and qualifying accounting personnel in line with the requirements of digital transformation.

Abstract

This study aimed to analyze the level of digital readiness and managerial perception of artificial intelligence applications in Jordan's five-star classified hotels. The study employed a descriptive-analytical approach and was applied to a sample of 342 managers and employees from 28 five-star hotels in Amman, Aqaba, and Petra. The results revealed that the level of digital readiness was moderate (3.42), while managerial perception was high (4.18). The findings also demonstrated a strong positive correlation (r=0.742, p<0.001) between digital readiness and managerial perception of artificial intelligence.

The contribution of this study lies in providing a comprehensive scientific framework that links digital transformation capabilities with hotel innovation through exploring the role of managerial perception as a critical factor in accelerating the adoption of artificial intelligence technologies. Furthermore, the study contributes to bridging the research gap in Arabic literature by presenting empirical evidence on the reality of Jordanian hospitality, thereby providing decision-makers and managers with a foundation for developing more sustainable digital strategies capable of enhancing competitive advantage.

The study recommends the necessity of investing in human capital and developing supportive national digital policies to accelerate digital transformation in the sector. Additionally, the study recommended developing comprehensive strategies to enhance digital readiness and build managerial capabilities in the field of artificial intelligence, with emphasis on investing in human capital.

Abstract

The research aims to diagnose the contribution of production scheduling rules in activating cyber production requirements and to determine the implications of this relationship at the level of the General Company for Electrical and Electronic Industries in Baghdad as a field of research, as manufacturing companies today face a major challenge represented by increasing complexity and responding to dynamic changes in addition to achieving short delivery times. As planning, control and scheduling mechanisms cannot deal efficiently under complex, dynamic and unexpected circumstances, this requires a move towards creative activities and problem solving using collaborative decision-making mechanisms between human and artificial intelligence. Therefore, a move was made towards creating requirements for the cyber production system that would have a positive impact. On artificial and human intelligence through trustworthy interaction and integration into the cyber production system. The research problem is demonstrated by answering the following question: Do production scheduling rules affect the activation of cyber production requirements in the researched company? To answer the research questions, reliance was placed on the descriptive analytical approach and on tools and methods for collecting data and information, represented by personal interviews and a questionnaire form that was distributed to 60 individuals working in the company, the research sample. The importance of the research is evident through its treatment of two variables that have become of great importance in our world today, as they It dealt with production scheduling as a tool for allocating resources and loading according to its rules, in addition to its endeavor to activate the requirements of cyber production, which is one of the applications of the fourth generation of industry and is consistent with artificial intelligence methods. In order to analyze the results of the practical side, a set of hypotheses were developed and tested in the company in the field of research using the statistical program. (SPSS VE 26) In addition to a number of statistical methods, the research reached a set of conclusions, the most prominent of which is: The existence of a significant correlation was achieved between production scheduling in terms of its rules (in general and individually) and cyber production in terms of its requirements (in general) in the company, the field of research, and this explains that the company’s management It was able to employ its rules to process requests and arrange work in an effort to enhance cyber production requirements. He presented a set of proposals, the most prominent of which are: increasing the company’s management’s interest in the field of research in production scheduling rules, deepening their importance, and enhancing investment in other rules according to customer requests by making adjustments to scheduling from time to time to avoid delays. In delivering products to customers.

Abstract

This study aims to analyze the role of artificial intelligence in achieving sustainable economic growth and addressing unemployment in Iraq. It examines the current state of artificial intelligence technology adoption, the level of institutional and human readiness, and the impact of these factors on economic growth and labor market indicators within the framework of the Sustainable Development Goals. The significance of the study stems from the growing global reliance on artificial intelligence as a key driver of economic transformation, in contrast to the limited adoption of these technologies in the Iraqi economy, despite the structural challenges it faces, most notably unemployment and a lack of economic diversification. The study adopts a descriptive-analytical approach, drawing on official data from the Ministry of Planning and the Central Statistical Organization, World Bank data, and the Scopus database. It also examines indicators of expenditure on education, research and development, and health during the period 2010–2024, with the aim of analyzing the relationship between artificial intelligence adoption, economic growth, and unemployment in Iraq. The study concludes that the contribution of artificial intelligence to achieving sustainable economic growth in Iraq remains limited due to weak digital infrastructure, low levels of investment in research and development, and the absence of a comprehensive national digital transformation strategy, despite the relative increase in the number of published scientific studies and growing official interest in modern technologies. The findings also indicate that artificial intelligence applications have the potential to improve productivity and enhance the efficiency of economic and service sectors. Nevertheless, their impact on addressing unemployment remains limited because educational outcomes are misaligned with the requirements of the digital labor market and because high-quality, knowledge-based employment opportunities remain scarce

Abstract

The study aims to evaluate the extent to which Iraqi banks have adopted digital transformation technologies and their willingness to shift from traditional methods to digital ones in order to achieve sustainable development goals. This is done through a quantitative analysis of a sample of banks using financial indicators. The results show that some banks have begun to pay attention to adopting digital technologies and considering sustainable development principles; however, these efforts are still in their early stages compared to foreign banks, while most banks continue to rely on traditional methods due to limited awareness and insufficient exposure to technological advancements. The study also indicates that there are limited attempts to adopt digital services such as mobile banking applications, account inquiries, and electronic payment systems. It emphasizes the need to invest in technological infrastructure, provide regulatory support, and enhance awareness among bank management and the community about the benefits of digital technologies, including cost reduction, increased efficiency, and improved service quality, thereby contributing to the achievement of sustainable development.

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

This research aims to measure the impact of using Internet of Things (IoT) and machine learning techniques on achieving the characteristics of accounting information and the extent to which this is reflected in the conceptual statement/8.This is based on the ability of artificial intelligence techniques to solve business problems and overcome obstacles facing companies by using highly advanced devices and applications, as it is a system capable on simulating human intelligence. According to the importance and problem of the research, and for the purpose of testing its hypotheses, a questionnaire was designed using Google Forms and distributed electronically to the research sample members, who were selected using a deliberate (intentional) sample consisting of employees from the departments of (financial affairs, auditing and internal control). (50) responses were obtained. Using the Statistical Package for the Social Sciences (SPSS), the results of the questionnaire were analyzed. According to the applied frame wall of the research, a set of conclusions were reached, the most important of which was that artificial intelligence techniques achieve the qualitative characteristics of accounting information, as stated in Conceptual statement/8. The researchers presented a set of The most prominent recommendations include the adoption by the Accounting Department of the Basrah Municipality Directorate of artificial intelligence techniques when performing various accounting tasks.

Abstract

This research aims to study the role of Lean Quality in promoting the transition to Green Manufacturing in modern organizations, focusing on its practical applications at the Al-Hillah Sugar Factory, owned by Al-Ittihad Company. The research highlights how Lean Quality principles, such as continuous improvement, waste reduction, and process flow optimization, can be used as tools to enhance production efficiency and achieve environmental sustainability.The research employed a field survey methodology, utilizing an eight-item questionnaire to cover Lean Quality and Green Manufacturing elements. A five-point Likert scale was used to assess the extent to which these concepts were applied by factory employees. A representative sample of employees was selected using stratified random sampling to ensure comprehensive coverage of all departments and job levels.The results of the analysis showed that Lean Quality is applied to varying degrees within the factory, with a high level of application in continuous improvement and process flow. However, some gaps were observed in employee engagement and waste reduction. Green Manufacturing practices ranged from moderate to high, with superior performance in the areas of corporate sustainability and energy consumption reduction. Environmental innovation, however, presented some challenges that require further development.

Abstract

Purpose of the Study: This research addresses a relatively new field; its primary objective is to determine whether the use of strategic momentum in productive organizations leads to the enhancement of organizational brilliance. Furthermore, the study aims to focus on modern strategic management approaches—including strategic momentum—and clarify their pivotal role in creating a comprehensive and integrated environment that fosters growth and differentiation, thereby advancing the industrial sector through the introduction of the concept of organizational brilliance.

Methodology: A sample was selected from employees at the Men’s Garments Factory in Al-Najaf Al-Ashraf. A questionnaire consisting of 22 questions was distributed to employees, including unit and division managers, department heads, accountants, and production staff. A total of 93 completed forms were collected.

Key Findings: The study results revealed a significant and meaningful impact of strategic momentum on organizational brilliance. According to the findings, the path coefficient of the explanatory variable (strategic momentum) showed strong influence on the responsive variable (organizational brilliance), indicating that strategic momentum plays a powerful role in organizing and enhancing employee brilliance within the industrial sector (the factory under study).

Applications of the Study: Strategic momentum can play a critical role in enhancing industrial performance by creating a comprehensive and integrated environment that promotes leadership brilliance, service excellence, innovation, knowledge, efficiency, and financial inclusion. This contributes to elevating the status of the factory under study. Productive factories that adopt strategic momentum can remain at the forefront of the curve, deliver superior services to their customers, maintain market share, and contribute to the sustainable and inclusive development of the national economy.

Abstract

This research aims to analyze the role of integrating artificial intelligence (AI) technologies in promoting digital transformation in the banking sector. This is of great importance due to its significant impact on monetary policy. Through the application of digital technologies, banks and financial institutions can greatly improve their procedures, leading to changes in banking liquidity. Digital transformation can contribute to increased cash flows and improved liquidity management, thus affecting the central bank's ability to implement monetary policy effectively. Thanks to big data analytics and AI, banks can better identify economic needs, influencing interest rate decisions. Therefore, it can be said that digital transformation plays a significant role in shaping monetary policy and opens the door to significant improvements in the management of fiscal and monetary policies and creative thinking skills. Traditional reliance on auditing methods does not keep pace with rapid technological developments, and auditors' weak adoption of creative thinking methods in addressing audit problems negatively affects the quality of audits and the accuracy of their results. The importance of this research lies in its aim to provide a comprehensive framework that combines modern technological tools and creative approaches to digital work, thereby contributing to the development of critical practices and enhancing the quality of its results according to standards of efficiency and effectiveness. The advanced statistical software Smart Pals and appropriate statistical methods were used to test the hypotheses. The results showed a statistically significant effect of using artificial intelligence technologies (expert systems, machine learning, continuous auditing, natural language processing, and robotic process automation) across all dimensions. This indicates the importance of AI applications in improving the quality of external auditing. Furthermore, the use of AI technologies has a positive impact on investor decisions through the quality of external auditing. Based on these findings, the researcher recommends that all accountants and auditors keep pace with technological developments and respond to changes in the surrounding environment by developing their AI skills. Audit firms should also be encouraged to adopt AI technologies in their work by replacing manual systems with computerized systems. The study aimed to analyze the impact of digital transformation indicators (ATMs, electronic payment cards, electronic point-of-sale systems, and instant settlement transfers). Adopting digital technologies has contributed to reducing reliance on cash and increasing the efficiency of monetary policy. However, in Iraq, limited effects were observed due to structural challenges such as weak infrastructure and economic instability.