Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

“…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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Flood Risk Mitigation by Spatial Planning—Lessons Learned From Municipal Consultation by Stefan Greiving, Stefanie Wolf, Daniela Michalski, Mark Fleischhauer

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Smart Green Classroom and Machine Learning to Promote Green Awareness for Sustainable Livings by Subhasree Pal, Souren Bhattacharya, Subhranil Mustafi, Shankar Mitra

“…If education is getting assembled with techno savvy approaches putting a bird’s eye on green conversion, the world again rejuvenates with all its blooms. Machine learning and deep learning can be utilised for mining acquainted knowledge from natural unpolished circumstances to provide necessary inputs in teaching learning process to bring out most desirable outcomes to transfer the society into green and habitable one. …”
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Comparative Study of Person Re-Identification Techniques Based on Deep Learning Models by Mossaab Idrissi Alami, Abderrahmane Ez-zahout, Fouzia Omary

“…This study explores deep metric learning models, specifically Siamese and Triplet networks, to improve Re-ID performance. …”
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Using a Machine Learning Approach to Predict the Thailand Underground Train’s Passenger by Wuttipong Kusonkhum, Korb Srinavin, Narong Leungbootnak, Tanayut Chaitongrat

“…However, crowding is a concern in the present since crowding creates a problem and reduces customer pleasure. …”
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Machine learning for human mobility during disasters: A systematic literature review by Jonas Gunkel, Max Mühlhäuser, Andrea Tundis

“…Various strategies have been developed to overcome this issue, which we present and discuss in this systematic literature review. …”
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Machine learning techniques for predictive modelling in geotechnical engineering: a succinct review by Shrikant M. Harle, Rajan L. Wankhade

“…The advent of machine learning (ML) techniques has significantly enhanced the prediction of soil-structure interactions during seismic events, improving the accuracy of models. …”
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Teacher Trainees’ Perspectives on the Use of Technology for Teaching and Learning in Forced Displacement Contexts by Loise Gichuhi

“…The study concluded that teacher trainees perceive learning online as a major enabler that allows them to be flexible and attend to other personal roles and responsibilities. …”
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Mathematics in the Concept of Circles: Creating Digital Learning Tools That Honor Cultural Heritage by Neneng Aminah, Siska Firmasari, Lidiya Junaedi, Cicih Nurfarikha

“…This media also succeeds in presenting interesting and meaningful learning by integrating cultural and technological aspects. …”
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Deep learning for early Parkinson's detection: A review of fundus imaging approaches by Zheen ALI, Najdavan KAKO

“…One of the newest advances in artificial intelligence, deep learning (DL), presents new opportunities for the early, non-invasive diagnosis of Parkinson's disease. …”
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Deep transfer learning mechanism for fine-grained cross-domain sentiment classification by Zixuan Cao, Yongmei Zhou, Aimin Yang, Sancheng Peng

“…To solve this problem, we present a deep transfer learning mechanism (DTLM) for fine-grained cross-domain sentiment classification. …”
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Comparative Study of Hybrid Deep Learning Models for Kannada Sign Language Recognition by Gurusiddappa Hugar, Ramesh M. Kagalkar, Abhijit Das

“…Abstract Sign language recognition (SLR) systems continue to face significant challenges in accurately interpreting dynamic gestures, particularly for underrepresented languages like Kannada sign language (KSL). This study presents a novel hybrid deep learning architecture that synergistically combines convolutional neural networks (CNNs), hand keypoints (HKPs), long short-term memory (LSTM) networks, and transformers to achieve robust spatial-temporal-contextual learning for KSL recognition. …”
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Machine Learning based Model Reveals the Metabolites Involved in Coronary Artery Disease by Fathima Lamya, Muhammad Arif, Mahbuba Rahman, Abdul Rehman Zar Gul, Tanvir Alam

“…Methods: This article presents machine learning (ML) based model that can recognize metabolomic compounds associated with CAD in the Qatari population for the early detection of CAD. …”
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A Machine Learning-Based Framework for Measuring Attack Surfaces of IoT Systems by Bandar M. Alshammari

“…However, continuous evolution in Artificial Intelligence (AI) methods, such as machine learning models, can provide an intelligent and effective approach to accommodate and mitigate such risks in the early stages. …”
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Assessment of retention and attenuation of motor-learning memory by repeated rotor-rod analyses by Sho Kakizawa

“…Abstract Retention of acquired learning memory is essential for reasonable behavior and crisis avoidance of individuals. …”
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Teachers’ Views: Using Body Music in Teaching and Learning Primary School Subjects by Muzaffer Özgü Bulut, Ayşe Akarsu, Ersoy Karabay

“…The paper presents research conducted among Turkish primary school classroom teachers regarding their personal and professional views about creating and using KeKeÇa body music games as educational tools. …”
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Intellectually Gifted Fifth Graders: Is Enriched Learning Practice Needed in Primary School? by Shumakova N.B.

“…The article presents the results of a study of the features of cognitive development and learning motivation of intellectually gifted and normotypical fifth-graders who studied in the primary grades according to programs of various types – enriched and traditional (typical). …”
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Brain Tumor Identification and Classification of MRI Images Using Deep Learning Techniques by Zheshu Jia, Deyun Chen

“…In this paper, a Fully Automatic Heterogeneous Segmentation using Support Vector Machine (FAHS-SVM) has been proposed for brain tumor segmentation based on deep learning techniques. The present work proposes the separation of the whole cerebral venous system into MRI imaging with the addition of a new, fully automatic algorithm based on structural, morphological, and relaxometry details. …”
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Education for Environmental Sustainability Component: Innovative Strategies for Experiential Learning in Natural Contexts by Ana Cano-Ortiz, José Carlos Piñar-Fuentes, Carmelo Maria Musarella, Juan Peña-Martínez

“…A case study conducted at the Complutense University of Madrid is presented, analyzing 36 of the 53 Spanish BRs to evaluate their conservation activities and educational uses. …”
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Using Contemplative Medicine to Harness Compassion in the Palliative Care Setting: Lessons Learned by Milagros D. Silva, Brigit C. Palathra

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