Sex classification accuracy through machine learning algorithms - morphometric variables of human ear and nose by Tej Kaur, Kewal Krishan, Akanksha Sharma, Ankita Guleria, Vishal Sharma

“…The study aims at predicting sex accuracy from different parameters of ear and nose by using a novel approach of Machine Learning Library, ‘PyCaret’. Results The present research was carried out on 508 participants (264 males and 244 females) aged 18–35 years from north India. …”
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Developing a participatory research framework through serious games to promote learning for children with autism by Hussein Karam Hussein Abd El-Sattar, Manal Omar, Hoda Mohamady

“…Serious games (SGs) offer an intelligent learning environment that supports lifelong learning for individuals with ASC. …”
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MIC: A deep learning tool for assigning ions and waters in cryo-EM and crystal structures by Laura Shub, Wenjin Liu, Georgios Skiniotis, Michael J. Keiser, Michael J. Robertson

“…However, direct identification of these sites from experimental data can prove challenging, and existing empirical approaches leveraging the local environment can only characterize limited ion types. We present a representation of chemical environments using interaction fingerprints and develop a machine learning model to predict the identity of input water and ion sites. …”
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AromaCanvas: A wearable olfactory display for Chinese painting appreciation and learning in virtual reality by Tao Lin, Quanhao Gan, Fuxi Ouyang, Yiming Luo, Yushan Pan, Yushi Li, Shaoyu Cai

“…In this paper, we present AromaCanvas, a wearable olfactory display designed to enhance immersive appreciation and exploration of Chinese paintings in virtual reality (VR). …”
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Machine learning-enabled techno-economic uncertainty analysis of sustainable aviation fuel production pathways by Chao Wu, Yuxi Wang, Ling Tao

“…To address these challenges, we present an accessible framework that harnesses machine learning methods to estimate techno-economic uncertainty in biofuel production pathways. …”
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Language models learn to represent antigenic properties of human influenza A(H3) virus by Francesco Durazzi, Marion P. G. Koopmans, Ron A. M. Fouchier, Daniel Remondini

“…Given that the best performing model that produces protein embeddings is agnostic to the specific pathogen, the presented approach may be applicable to other pathogens.…”
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Influence maximization under imbalanced heterogeneous networks via lightweight reinforcement learning with prior knowledge by Kehong You, Sanyang Liu, Yiguang Bai

“…However, one certain network referred to as Imbalanced Heterogeneous Networks (IHN), which widely used in social situation, urban and rural areas, and merchandising, presents challenges in achieving high-quality solutions. …”
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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods by Zhehao Huang, Benhuan Nie, Yuqiao Lan, Changhong Zhang

“…Carbon price forecasting and pricing are critical for stabilizing carbon markets, mitigating investment risks, and fostering economic development. This paper presents an advanced decomposition-integration framework which seamlessly integrates econometric models with machine learning techniques to enhance carbon price forecasting. …”
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Determinantes sociales del voto en México, un análisis longitudinal y machine learning by Alejandro Zamudio-Sosa, Olivia Leyva-Muñoz, Marcela Cavazos-Guajardo Solís

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Q-Learning based VM Consolidation Approach for Enhancing Cloud Data Centres Power Efficiency by Baikani Sreenithya, Bharde Hitesh Dutt, Chennamaneni Jashwanth, R Karthikeyan, MA Jabbar, Majjari Sudhakar

“…There are various strategies present to minimize this problem. One among them is using cloud computing infrastructure and VM setup. …”
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A novel deep sequential learning architecture for drug drug interaction prediction using DDINet by Anindya Halder, Biswanath Saha, Moumita Roy, Sukanta Majumder

“…Abstract Drug drug Interactions (DDI) present considerable challenges in healthcare, often resulting in adverse effects or decreased therapeutic efficacy. …”
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Enhancing Security of Proof-of-Learning Against Spoofing Attacks Using Feature-Based Model Watermarking by Ozgur Ural, Kenji Yoshigoe

“…The rapid advancement of machine learning (ML) technologies necessitates robust security frameworks to protect the integrity of ML model training processes. …”
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Malaysian non-Arabic speaking learners' readiness in a virtual second language learning environment by Noorafini Kassim, Muhammad Sabri Sahrir, Tunku Badariah Tunku Ahmad

“…The purpose of this present study is to investigate the effects of online readiness on learners’ learning satisfaction and performance in a virtual second language learning environment on a sample of 203 Malaysian Non-Arabic Speaking Learners using a cross-sectional survey. …”
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Rectified Tangent Activation (RTA): A Novel Activation Function for Enhanced Deep Learning Performance by Gaurav Kumar Pandey, Sumit Srivastava

“…In deep learning, activation functions (AFs) influence a model’s performance, convergence rate, and generalization capability. …”
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A Survey on Machine Learning Enhanced Integrated Sensing and Communication Systems: Architectures, Algorithms, and Applications by Mikael Ade Krisna Respati, Byung Moo Lee

“…Following an overview of ML and deep learning (DL), we explore common types of ML and DL models and their potential to enhance ISAC systems. …”
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A Fast Two-Dimensional Direction-of-Arrival Estimator Using Array Manifold Matrix Learning by Jieyi Lu, Long Yang, Yixin Yang, Lu Wang

“…This paper proposes a fast 2D DOA estimator using array manifold matrix learning, where source-associated grid points are progressively selected from the set of predefined angular grids based on marginal likelihood maximization in the sparse Bayesian learning framework. …”
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Cross-Lingual Summarization for Low-Resource Languages Using Multilingual Retrieval-Based In-Context Learning by Gyutae Park, Jeonghyun Park, Hwanhee Lee

“…Cross-lingual summarization (XLS) involves generating a summary in one language from an article written in another language. XLS presents substantial hurdles due to the complex linguistic structures across languages and the challenges in transferring knowledge effectively between them. …”
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TrapMI: A Data Protection Method to Resist Model Inversion Attacks in Split Learning by Hyunsik Na, Daeseon Choi

“…Split learning is a neural network training approach that can overcome the limitations of traditional deep neural networks in edge artificial intelligence environments. …”
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Deep Learning Techniques for Fault Diagnosis in Interconnected Systems: A Comprehensive Review and Future Directions by Nawel Said, Majdi Mansouri, Rami Al Hmouz, Atef Khedher

“…Advanced learning methods like deep learning, transfer learning, and hybrid models are tailored to processing and aggregating such disparate streams of data, thereby leading to higher diagnostic accuracy. …”
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An experimental investigation of HAM, a novel mnemonic technique for learning L2 homonyms and homophones by Charles M. Mueller

“… Over the past 40 years, extensive research has examined the effectiveness of mnemonics for vocabulary learning. Much of this research has investigated the keyword method (Atkinson & Raugh, 1975), which involves linking an image related to a to-be-learned L2 word with animage related to a similar-sounding L1 word. …”
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