Early Diagnosis of Alzheimer Disease from Mri Using Deep Learning Models by Apparna Allada, R. Bhavani, Kavitha Chaduvula, R. Priya

“…The Alzheimer's disease Neuroimaging Initiative (ADNI) database of AD patients was used to develop a deep learning approach for AD identification. In addition, this study will present ideas for Haralick features, feature extraction from Local Binary Pattern (LBP), Artificial Neural Network (ANN), and Visual Geometry Group (VGG)-19 network techniques. …”
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Civic and social science learning in the Czech Republic: Current state, challenges and prospects by Denisa Labischová, Tomáš Hubálek

“…Purpose: Taking the form of a report, the presented text aims to map the curricular changes in civic education and social science learning in basic and upper secondary schools after 1989. …”
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A Sentinel-2 machine learning dataset for tree species classification in Germany by M. Freudenberg, M. Freudenberg, S. Schnell, P. Magdon

“…<p>We present a machine learning dataset for tree species classification in Sentinel-2 satellite image time series of bottom-of-atmosphere reflectance. …”
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Cybersecurity of smart grids: Comparison of machine learning approaches training for anomaly detection by S. V. Kochergin, S. V. Artemova, A. A. Bakaev, E. S. Mityakov, Zh. G. Vegera, E. A. Maksimova

“…The transformation of modern electric grids into decentralized smart grids presents new challenges in the field of cybersecurity. …”
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On the influence of artificially distorted images in firearm detection performance using deep learning by Patricia Corral-Sanz, Alvaro Barreiro-Garrido, A. Belen Moreno, Angel Sanchez

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Biological Motion-Based Emotion Recognition Through a Deep Learning Approach by Amjaad T. Alotaibi, Suhare Solaiman

“…In this study, emotion recognitions from biological emotional motion was presented. A model integrating convolutional neural networks (CNN) and long short-term memory (LSTM) layers was proposed to predict six distinct emotions: happiness, sadness, anger, fear, disgust, and neutral. …”
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A trajectory planning and tracking method based on deep hierarchical reinforcement learning by Jiajie Zhang, Bao-Lin Ye, Xin Wang, Lingxi Li, Bo Song

“…First, we present a hierarchical control framework for vehicle trajectory tracking that is based on deep reinforcement learning (DRL) and model predictive control (MPC). …”
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Transfer Learning and Semisupervised Adversarial Detection and Classification of COVID-19 in CT Images by Ariyo Oluwasanmi, Muhammad Umar Aftab, Zhiguang Qin, Son Tung Ngo, Thang Van Doan, Son Ba Nguyen, Son Hoang Nguyen

“…With the advances in computer-aided diagnosis and artificial intelligence, this paper presents the application of deep learning and adversarial network for the automatic identification of COVID-19 pneumonia in computed tomography (CT) scans of the lungs. …”
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Optimizing Deep Learning Algorithms for Effective Chicken Tracking through Image Processing by Saman Abdanan Mehdizadeh, Allan Lincoln Rodrigues Siriani, Danilo Florentino Pereira

“…Identifying bird numbers in hostile environments, such as poultry facilities, presents significant challenges. The complexity of these environments demands robust and adaptive algorithmic approaches for the accurate detection and tracking of birds over time, ensuring reliable data analysis. …”
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A Novel Semantic Driven Meta-Learning Model for Rare Attack Detection by Y. Annie Jerusha, S. P. Syed Ibrahim, Vijay Varadharajan

“…Traditional models often struggle with uncertain traffic patterns, reducing their reliability. This work presents a Novel Semantic-Driven Meta-Learning Model - a hybrid framework that systematically refines categorization decisions. …”
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Anomaly detection using unsupervised machine learning algorithms: A simulation study by Edmund Fosu Agyemang

“…This study presents a comprehensive evaluation of five prominent unsupervised machine learning anomaly detection algorithms: One-Class Support Vector Machine (One-Class SVM), One-Class SVM with Stochastic Gradient Descent (SGD), Isolation Forest (iForest), Local Outlier Factor (LOF), and Robust Covariance (Elliptic Envelope). …”
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The AI-knowledge management nexus for sustainable learning: A PLS-SEM study by Sashi Ranjan, V. P. Joshith, K. Kavitha, Shana Chittakath

“…Integrating artificial intelligence (AI) with knowledge management (KM) practices presents a promising avenue for advancing sustainable learning in higher education. …”
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Machine Learning in Public Governance: A Systematic Review of Applications, Trends and Challenges by Y. Nuruly, G. N. Sansyzbayeva, L. Z. Ashirbekova, S. K. Tazhiyeva

“…Today, the active implementation of machine learning (hereinafter – ML) methods in public administration opens up new opportunities for forecasting, impact assessment and decision support, while simultaneously generating various challenges. …”
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A web-based machine learning framework for building energy efficiency prediction by B.S.S.V. Ramana, S. Chanikya Kumar, N. Bharath Kumar, Attuluri R. Vijay Babu

“…Energy efficiency in buildings is crucial for advancing sustainability and minimizing operational costs. This paper presents a web-based machine learning framework for estimating heating and cooling loads using static design parameters. …”
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Sitting Posture Detection and Classification Using Machine Learning Algorithms on RapidMiner by Chawakorn Sri-ngernyuang, Prakrankiat Youngkong, Jinpitcha Mamom, Duangruedee Lasuka

“… Integrating pressure sensors into cushion pads presents a viable posture monitoring and classification solution in innovative health care and ergonomic design. …”
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A systematic mapping review at the intersection of artificial intelligence and self-regulated learning by Seyyed Kazem Banihashem, Melissa Bond, Nina Bergdahl, Hassan Khosravi, Omid Noroozi

“…Abstract Recently, artificial intelligence (AI) has increasingly been integrated into self-regulated learning (SRL), presenting novel pathways to support SRL. …”
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Effects of implicit, explicit and sequential learning in the acquisition of the basketball shooting skill in novices by Mariana Calábria Lopes, Maicon Rodrigues Albuquerque, Markus Raab

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Research and Application of Structural Plane Identification for Roadway Surrounding Based on Deep Learning by Qiang Xu, Ze Xia, Gang Huang, Xuehua Li, Xu Gao, Yukuan Fan

“…To address this need, a program was developed that uses deep learning to automatically recognize the structural plane in-borehole images. …”
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A novel explainable deep learning framework for reconstructing South Asian palaeomonsoons by K. M. R. Hunt, K. M. R. Hunt, S. P. Harrison

“…<p>We present novel explainable deep learning techniques for reconstructing South Asian palaeomonsoon rainfall over the last 500 years, leveraging long instrumental precipitation records and palaeoenvironmental datasets from South and East Asia to build two types of models: dense neural networks (“regional models”) and convolutional neural networks (CNNs). …”
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Advancements in Machine Learning-Based Intrusion Detection in IoT: Research Trends and Challenges by Márton Bendegúz Bankó, Szymon Dyszewski, Michaela Králová, Márton Bertalan Limpek, Maria Papaioannou, Gaurav Choudhary, Nicola Dragoni

“…This paper presents a systematic literature review based on the PRISMA model on machine learning-based Distributed Denial of Service (DDoS) attacks in Internet of Things (IoT) networks. …”
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