This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilingual (Arabic–English) decision-support application was developed to operationalize the model, enabling scenario analysis, risk prediction, and project monitoring under crisis conditions. The findings highlight the potential of Ethical AI to enhance transparency, accountability, and data-driven decision-making in fragile and post-conflict environments, supporting national strategies aligned with the United Nations Sustainable Development Goals (UN-SDGs). © 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/ Author keywords Artificial neural networks, Sustainability indicators; Ethical artificial intelligence; Iraq; Risk management; SMART-AI; SPSS analysis; Sustainable development
This research examines the future of television work in light of the challenges posed by artificial intelligence (AI). The study aims to explore the impact of AI on the form and content of television messages and identify areas where AI can be employed in television production. This study adopts a future-oriented exploratory approach, utilizing survey methodology. As the research focuses on foresight, the researcher gathers the opinions of AI experts and media specialists through in-depth interviews to obtain data and insights. The researcher selected 30 experts, with 15 experts in AI and 15 experts in media. The study reveals several findings, including the potential use of machine learning, deep learning, and na
... Show MoreImmunization is one of the most cost-effective and successful public health applications. The results of immunization are difficult to see as the incidence of disease occurrence is low while adverse effects following the immunization are noticeable, particularly if the vaccine was given to apparently healthy person. High safety expectations of population regarding the vaccines so they are more prone to hesitancy regarding presence of even small risk of adverse events which may lead to loss of pub
... Show MoreCosmetic products contain variable amounts of nutrients that support microbial growth. Most contaminants in cosmetic products include bacteria such as Staphylococcus, Pseudomonas, Klebsiella, Achromobacter and Alcaligenes. Contaminated water is a likely source of organisms found in cosmetic products. Products such as shampoo, hand and body lotion, facial cleanser, and liquid soaps were analyzed. In this study, out of 60 cosmetic products analyzed, 26.4% were found to be contaminated. Most of the contamination was from bacteria and no fungal contamination was detected. The highest level o
... Show MoreInformation security is a crucial factor when communicating sensitive information between two parties. Steganography is one of the most techniques used for this purpose. This paper aims to enhance the capacity and robustness of hiding information by compressing image data to a small size while maintaining high quality so that the secret information remains invisible and only the sender and recipient can recognize the transmission. Three techniques are employed to conceal color and gray images, the Wavelet Color Process Technique (WCPT), Wavelet Gray Process Technique (WGPT), and Hybrid Gray Process Technique (HGPT). A comparison between the first and second techniques according to quality metrics, Root-Mean-Square Error (RMSE), Compression-
... Show MoreIn today's cities, it is easy to see large numbers of vacant lands and unused abandoned sites in downtown areas that are not only ugly but also potentially becoming fertile ground for criminal activities that endanger residents and visitors and contribute to the further degradation of neighborhoods,
can provide reuse of spaces Neglected opportunities to reshape the appearance of the city and to improve the city center for its users that the presence of many neglected sites, whether they were abandoned buildings or sites for destroyed buildings in Mosul after the war on ISIS and with large areas amid the urban fabric led to the emergence of the research problem is (lack of urban planning to reactivate abandoned sites within the ci
... Show MoreModern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan
... Show MoreThis current research aims to identify the effectiveness of a training program in developing moral intelligence and mutual social confidence among middle school students. The researcher made a number of hypotheses for this purpose to achieve the goal of the research.
The researcher relied on the (Al Zawaida 2011) scale prepared according to Coles (1997), including (60) items, and the mutual social trust scale for (Nazmi 2001) based on Roter's theory including (38) items.  
... Show MoreStereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me
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