Novel intelligent model following controller and PQ droop controller operated nuclear-PV-biogas hybrid microgrid and EV charging station

Intelligent Recognition English Translation Model Based on Speech Recognition

Leveraging artificial intelligence and statistical models for predicting dam water storage: insights from a Moroccan case study

Intelligent Predictive Hiring Model and Personality Assessment

Advancement of machine learning algorithms in biosensors.

Interplay and integrated regulation of astaxanthin-lipid biosynthesis in microbial systems: A review from metabolic pathway cross-talk to biotechnological optimization.

Actigraphy-based step analysis for the detection of depressed mood: An explainable machine learning approach.

Artificial intelligence-based lesion characterization and outcome prediction of prostate cancer on [18F]DCFPyL PSMA imaging.

Evolution of chromatographic modeling: From mechanistic models to hybrid models with physics-based deep learning.

Development of intelligent learning-based surrogate models for predicting diesel ignition at different thermodynamic conditions

A data-driven and expert flood knowledge model based on the development of the Huber loss function for flood forecasting.

Water quality monitoring for coastal hypoxia: Integration of satellite imagery and machine learning models.

Accuracy of LLMs to retrieve numeric data for meta-analysis in dentistry.

Advancing glaucoma research with multiphysics continuum mechanics modelling: Opportunities and open challenges.

Predictive model of Ki67 expression level in osteosarcoma based on weakly supervised segmentation and multi-type feature fusion.

Artificial Intelligence Modeling, RSM regression, and correlation analysis to predict of dispersed phase hold-up in the new agitated extraction column with randomly packing

Advances in multimodal artificial intelligence models for epilepsy research.

This study aimed to design a localized model for documenting the knowledge of biology teachers in Baghdad secondary schools, based on the principles of micro educational management. Micro educational management conceptualizes the teacher as a leader at the classroom level who manages the teaching and learning process through moment-to-moment decision-making and continuous reflection. Within this framework, a teacher’s professional knowledge is categorized into three types: “substantive knowledge” (scientific concepts), “contextual knowledge” (lived experience), and “explicit knowledge” (observable documentation). This qualitative study was conducted within an interpretive paradigm, employing semi-structured interviews, participatory observation, and document analysis of 12 biology teachers in four schools in Baghdad. The data were analyzed using the Attride-Stirling thematic analysis method. Findings led to the extraction of five basic themes: documentable content as substantive knowledge, strategies for recording and organizing knowledge, implicit and non-recordable knowledge, criteria for selecting documentable content, and enablers and barriers to documentation. These themes were ultimately integrated into an overarching theme entitled “The Intelligent Model of Teacher Knowledge Documentation within the Framework of Micro Educational Management.” This model demonstrates that documentation becomes intelligent and effective when the teacher, guided by reflective and situational rationality, assumes the role of a knowledge manager and designer, establishing interconnections among the three types of knowledge. This process transforms documentation from a mere administrative task into a research-based and knowledge-creating practice that leads to sustainable individual and organizational learning. The results indicate that implementing this model can foster teachers’ professional growth, strengthen the school’s intellectual capital, and enhance the quality of biology instruction. The study underscores the necessity of institutionalizing documentation within the school culture and providing institutional support for teachers to realize micro educational management.

An explainable three dimensional framework to uncover learning patterns: A unified look in variable sulci recognition.

Multi-modal multi-task artificial intelligence model for active distribution network scheduling with multi-agent reinforcement learning