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Multi-classification of autism spectrum disorder behavior for children using explainable artificial intelligence techniques
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Precise and interpretable classification of autism-related behaviors is important for initial diagnosis, personalized intervention, and support arrangements. This study proposes an interpretable machine learning (ML) model using Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost) to classify behavioral patterns into four categories (normal, mild, moderate, and severe) associated with Autism Spectrum Disorder (ASD) based on a custom 377-instance survey dataset from Iraqi parents and teachers of children aged 6-12. The model observes 16 key features across communication and social interaction, repetitive behaviors, language, and adaptive skills, preprocessed via interquartile range (IQR) outlier removal, mean imputation, and K-nearest neighbors (KNN) balancing. Shapley Additive Explanations (SHAP) provide instance-level explanations, and Permutation Feature Importance (PFI) quantifies global feature importance. CatBoost had better accuracy (99. 53%) precision recall, and F1-scores (even reaching 1. 00 for some classes), completely outshining LightGBM (97. 65%). This combination of two XAI tools improves clinicians' trust and the practicality of insights, taking ASD assessment that is both accessible and transparent a step further beyond the use of black-box sensor-based models.

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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Research on Emotion Classification Based on Multi-modal Fusion
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Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Hydrology
Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: Comparative study and insight for federated learning technology
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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Solution for Multi-Objective Optimisation Master Production Scheduling Problems Based on Swarm Intelligence Algorithms
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The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T

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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Publication Date
Sun Jan 04 2026
Journal Name
Steam-h: Science, Technology, Engineering, Agriculture, Mathematics; Health
Artificial Intelligence Applications for Achieving Economic Stability and Sustainable Growth in the Modern Era
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In recent years, the steady stream of artificial intelligence into economic systems has become a torrent. It is changing how we generate wealth and grow anew. Manufacturing, finance, health care energy, agriculture and education are just a few of the areas where AI may result in dramatic increases in productivity as well as innovation and sustainability. Predictive analytics, AI, robotics and natural language processing have significantly contributed in the improvement of resource allocation mechanisms and decision making as well as reaching SDGs. The concept of Artificial Humanity is also introduced in the paper. It shows how AI could become a global cognitive network to foster knowledge. By comparison and references of the literature, thi

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Publication Date
Thu Jul 23 2026
Journal Name
Dirasat: Human And Social Sciences
The U.S.-China Competition in Artificial Intelligence and Its Implications for Shaping Military Strategies
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Objectives: This study investigates the U.S.-China competition in the field of artificial intelligence (AI), focusing on its implications for both countries’ military strategies. It also offers a forward-looking assessment of how this rivalry may influence international security and geopolitical stability. Methods: The research adopts an integrative theoretical framework combining realism—which emphasizes military power and strategic dominance—and technological innovation theory, which highlights the role of emerging technologies in global power shifts. A descriptive and analytical approach is employed, synthesizing academic literature, policy reports, and strategic documents from 2010 to 2030. Results: The U.S.-China AI compe

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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Ecology
Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
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Publication Date
Sun Nov 30 2025
Journal Name
بدبي اعمال وقائع المؤتمر الدولي الاول لعلوم المكتبات والمعلومات جامعة الوصل و مكتبة محمد بن راشد
Artificial Intelligence Skills of Information Institutions Workers: A Descriptive Study
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Objectives: This research aims to study the artificial intelligence (AI) skills re-quired by employees in information institutions, specifically university libraries in Iraq, to enhance their services and align with modern technological advancements. It highlights the gap between the current knowledge of employees in Al technologies and their practical applications to improve the services of information institutions. Methodology: The research adopted a descriptive survey method, targeting em- ployees in three prestigious university libraries in Baghdad: the Central Library of the University of Baghdad, the Central Library and House of Books of Al-Mustansiriyah University, and the Central Library of the Iraqi University. A sample of (160)

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Publication Date
Tue Aug 15 2023
Journal Name
Al-academy
The effectiveness of artificial intelligence in contemporary digital graphic design
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In our world, technological development has become inherent in all walks of life and is characterized by its speed in performance and uses. This development required the emergence of new technologies that represent a future revolution for a fourth industrial revolution in various fields, which contributed to finding many alternatives and innovative technical solutions that shortened time and space in terms of making Machines are smarter, more accurate, and faster in accomplishing the tasks intended for them, and we find the emergence of what is called artificial intelligence (artificial intelligence), which is the technology of the future, which is one of the most important outputs of the fourth industrial revolution, and artificial inte

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