Al-Furat Journal of Innovations in Management Sciences

:This research aims to determine how Babylon and Gulf, two private banks in Najaf Governorate, might benefit from entrepreneurial leadership for long-term strategic success. Descriptive analysis was used to determine the study's variables' relationships. The questionnaire was the main data source. Study participants were financial institution employees. Each of 180 bank administrators, department heads, division leaders, and unit operators received a questionnaire. Study participants numbered 287. The response rate was 94.6%, and 170 of 172 valid questionnaires were submitted for statistical analysis. The researcher used simple regression, correlation coefficient, standard deviation, and mathematical mean to examine the practical part of the study. (2007) used Excel and SPSS version 28 for advanced statistical analysis. Theory indicated a gap in our knowledge of entrepreneurial leadership's role in long-term strategic success, both generally and at the financial institutions. The study found that entrepreneurial leadership affected performance in real life. The survey also revealed many things that showed bank workers' interest and commitment to sustainable strategic performance.

This research aims to explain the impact of artificial intelligence on developing flexible budget and improving its accuracy and flexibility in financial planning and control, through its application at Middle -Euphrates Oncology Centre. The research mainly relies on the descriptive analytical approach, studying a case based on the financial and administrative reports belonging to the above-mentioned centre, and comparing the results of the traditional flexible budget with the results of artificial intelligence -based budget. The outcomes demonstrated that, in comparison to the traditional budget, the artificial intelligence-based flexible budget is more effective at lowering deviations and raising prediction accuracy, demonstrating its ability to boost strategic productivity. The value of the research lies in highlighting the role of integrating artificial intelligence with traditional accounting practices in supporting financial planning and control. It also recommends expanding the scope of future research and studies to include additional service industries.

his paper presents a theoretical rationale for integrating the Model based on Material flow cost accounting and Cleaner Production, and its role in achieving sustainability. This study synthesizes theoretical and empirical evidence from several papers published in top-tier cost accounting and production management journals to develop a structured model of the integration process. The study concludes that MFCA is a significant predictor of performance efficiency and prerequisite ratios for production and corporate efficiency. It also highlights that Cleaner Production technology can enhance a company's environmental behavior and sustainable performance. The review identifies important shortcomings, such as the lack of longitudinal and cross-cultural research to utilise the merging approach between MFCA and CP technology to foster sustainability. It encourages research on both positive and negative dimensions to enhance sustainable organizational operations. Concrete suggestions are made on the industrial side to improve and accelerate the transition to more energy-efficient and sustainable production methods.

This study aims to analyze and measure the impact of sustainability (ESG) indicators on the financial performance of companies listed on the Iraq Stock Exchange. This is achieved through a set of financial indicators, including return on assets (ROA), profit margin, total asset turnover, and company market capitalization. The research employs a descriptive-analytical approach and an econometric method, utilizing a correlation model and simple linear regression to measure the direction and strength of the relationship between the two variables. Data were collected from financial reports published on the Iraq Stock Exchange and from company disclosures regarding sustainability practices. The analysis revealed a positive correlation between the ESG indicator and return on assets, although the statistical strength of this relationship was moderate. Furthermore, the study found that the governance dimension had the greatest impact on financial performance compared to the environmental and social dimension, reflecting improvements in transparency and financial disclosure policies during the study period.
The research concludes that adopting sustainability practices contributes to increased asset utilization efficiency and enhanced investor confidence in the long term, even though the costs of implementation may limit short-term profitability. The research recommends integrating ESG indicators into the financial performance reports of Iraqi industrial companies and adopting international disclosure standards (GRI) and (ISSB) to ensure transparency, attract sustainable investments, and enhance the companies' market value.

Face detection has garnered a lot of attention and has been studied quickly in a large number of possible computer and communication applications, including automatic access control. Also, face detection is one of the most important aspects of face recognition as a preliminary step. Face detection is challenging due to the large number of variations in the appearance of the image, i.e., contrasting mode, clogging, image orientation, lighting condition, etc.
In this paper, we present an effective algorithm using RGB and the color model's morphological processing to detect human faces on color images. Tested on 170 various images obtained from the internet, the proposed algorithm proved highly effective with reduced computation time. The face detector in this study test applied 71 images with 100% accuracy; it works best when the image contains group photos with a small face region.

This study addresses earning power and its role in achieving the fair value of shares for a sample of industrial sector companies listed on the Iraq Stock Exchange. During the study period, the Iraqi economy experienced unstable economic and financial conditions that directly affected corporate performance and the level of share pricing in the market. These conditions were accompanied by multiple challenges that influenced the efficiency of industrial activity, corporate profitability, and the stability of dividend distributions, which contributed to widening the gap between market value and fair value of shares.
These changes were reflected in companies’ ability to achieve sustainable profits, thereby affecting investors’ expectations, the volume of financing and investment, and consequently the fair value of shares. Accordingly, this study seeks to highlight earning power as an indicator that reflects operational and financial performance efficiency and to clarify its role in explaining changes in the fair value of shares.
The study relied on annual financial data for the sample companies covering the period (2015–2024). Earning power was measured using the earning power model, while the fair value of shares was estimated based on the Dividend Discount Model. The study reached a set of results demonstrating that earning power plays a role in achieving the fair value of shares and concluded with a number of conclusions and recommendations relevant to the study topic.

Securing distributed infrastructure is a highly complex challenge due to the sheer volume of data, the diversity of its sources, and the severe imbalances in its categories, which render traditional anomaly detection systems ineffective [1, 7]. This work presents a hybrid approach combining privacy preserving unified learning capabilities with local data balancing technology (SMOTE). This framework is designed to enable collaborative training across endpoints without requiring centralized raw data exchange, thus striking a balance between privacy and reliability [9]. By applying heterogeneous data distribution processing locally at each site before global aggregation, this approach aims to minimize false positives and increase the likelihood of detecting attacks or rare anomalies [5, 12]. This approach will help provide scalable, proactive protection for existing cloud computing and distributed networks

In this research, we are trying to present a new proposal related to the possibility of preserving digital intellectual property rights, especially what is specifically related to the social networking site Facebook, and the problem of videos, fake news, or stolen information, and how to control this phenomenon, which researchers in this topic have tried to present many projects, but they were unable to limit this problem, in addition to the fact that there are no laws and deterrent legislation that can implement penalties for perpetrators of these crimes, and because the ethereal world and the Internet are not subject to legal determinants and evidence that can prove the crime in flagrante delicto in terms of spatial and temporal determination, and even there is difficulty in reaching the criminal, or the real hacker, and in light of that, we will try to present a proposal and a new method that can control the temporal and spatial limits that are based on adding technology to the Facebook site through which access to the first source of information or video.