MIMO antenna optimization for millimeter-wave 5G applications using machine learning by Masuod Ghasemi

“…Abstract This paper presents the design and machine learning-based optimization of a compact single-port MIMO antenna operating at 37 GHz for millimeter-wave 5G applications. …”
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Learning the non-proportional multiaxial elastic–plastic response of an aluminium alloy with neural networks by Burcu Tasdemir, Antonio Pellegrino, Xinyu Su, Vito L. Tagarielli

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Predicting the <i>S. cerevisiae</i> Gene Expression Score by a Machine Learning Classifier by Piotr H. Pawłowski, Piotr Zielenkiewicz

“…The topic of this work is gene expression and its score according to various factors analyzed globally using machine learning techniques. The expression score (ES) of genes characterizes their activity and, thus, their importance for cellular processes. …”
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An investigation of learning strategies & personality traits among proficient & less proficient ESL learners by Christine Shobana Arthur, Lee Luan Ng

“…The outcome of the present study would be useful to assist language instructors in helping less proficIent ESL learners in undergoing a more effective and successful second language leaming experience and enlighten proficient ESL learners about their preference in language learning strategies. …”
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DIDACTIC POTENTIAL OF YOUTUBE CHANNELS FOR ENHANCED ENGLISH LANGUAGE LEARNING IN NON-LINGUISTIC PROGRAMS by Blynova Neliia, Medynska Svitlana, Voloboieva Anna

“…The emergence of Web 2.0, technological advancements, and the information age present a plethora of opportunities to facilitate engaging, efficient, and high-quality English language learning for both educators and students. …”
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Detection freezing of gait (FOG) in Parkinson's patients using wearable sensors and deep learning by Maryam Talebvand, Amir Lakizadeh, Faranak Fotouhi

“…The use of computational methods can provide non-pharmacological support and complementary information about the disease to neurologists by carefully examining patients’ FOG status and increasing the likelihood of a more effective treatment. This paper presents a method for FOG detection based on deep learning and signal processing techniques. …”
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Automated Quantification of Rebar Mesh Inspection in Hidden Engineering Structures via Deep Learning by Yalong Xie, Xianhui Nie, Hongliang Liu, Yifan Shen, Yuming Liu

“…This paper presents an in-depth study of the automated recognition and geometric information quantification of rebar meshes, proposing a deep learning-based method for rebar mesh detection and segmentation. …”
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Discussing the spectrum of physics-enhanced machine learning: a survey on structural mechanics applications by Marcus Haywood-Alexander, Wei Liu, Kiran Bacsa, Zhilu Lai, Eleni Chatzi

“…The intersection of physics and machine learning has given rise to the physics-enhanced machine learning (PEML) paradigm, aiming to improve the capabilities and reduce the individual shortcomings of data- or physics-only methods. …”
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Contrastive learning for one-shot building shape recognition using vector polygon transformers by Longfei Cui, Haizhong Qian, Junkui Xu, Chao Li, Xinyu Niu

“…Accurate building shape recognition is essential for cartographic generalization, urban planning, and geographic analysis, but existing methods struggle with numerous categories and limited samples. This paper presents a novel contrastive learning-based method for building shape recognition that improves accuracy and broadens recognizable types in one-shot scenarios. …”
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Design of a Deep Learning-Based Metalens Color Router for RGB-NIR Sensing by Hua Mu, Yu Zhang, Zhenyu Liang, Haoqi Gao, Haoli Xu, Bingwen Wang, Yangyang Wang, Xing Yang

“…In this study, we propose a deep learning network capable of forward prediction across a broad wavelength range, combined with a particle swarm optimization algorithm to design metalens efficiently. …”
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Overcoming the Barriers That Obscure the Interlinking and Analysis of Clinical Data Through Harmonization and Incremental Learning by Vasileios C. Pezoulas, Konstantina D. Kourou, Fanis Kalatzis, Themis P. Exarchos, Evi Zampeli, Saviana Gandolfo, Andreas Goules, Chiara Baldini, Fotini Skopouli, Salvatore De Vita, Athanasios G. Tzioufas, Dimitrios I. Fotiadis

“…<italic>Goal:</italic> To present a framework for data sharing, curation, harmonization and federated data analytics to solve open issues in healthcare, such as, the development of robust disease prediction models. …”
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Hierarchical classification of scientific articles using deep learning (using the UDC hierarchy as an example) by Valentin Y. Mamedov, Danil A. Kovalevsky, Dmitry A. Morozov, Stepan S. Stolyarov, Sergey S. Ospichev

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SMS Spam Detection System Based on Deep Learning Architectures for Turkish and English Messages by Hakan Can Altunay, Zafer Albayrak

“…The aim of this study is to present a hybrid model proposal with the intention of detecting SMS spam messages. …”
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Language-mixing in Content and Language Integrated Learning: benefit or burden? An auditory recall perspective by Thomas Caira, Mathieu Declerck, Esli Struys

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Enhancing User Experiences in Digital Marketing Through Machine Learning: Cases, Trends, and Challenges by Alexios Kaponis, Manolis Maragoudakis, Konstantinos Chrysanthos Sofianos

“…This systematic examination of machine learning in the Digital Marketing (DM) industry is also closely examined, focusing on its effect on human–computer interaction (HCI). …”
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Physical Layer Spoof Detection and Authentication for IoT Devices Using Deep Learning Methods by Da Huang, Akram Al-Hourani

“…In this work, we propose an authentication method based on radio frequency fingerprinting (RFF) using deep learning. This method can be implemented on the base station side without increasing the complexity of the IoT devices. …”
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Digital Transformation in Education: ASEM Case Study and the Integration of Modern Technologies in the Learning Process by Aurelia TURCAN, Lucia GUJUMAN, Tatiana COLESNICOV

“…The research conducted in the article is an analysis of the current state of digitization in the Republic of Moldova, with a case study focused on the implementation of the digital teaching-learning-assessment process at ASEM. This approach is based on observing how digital platforms and tools can enhance student autonomy through online collaboration and support teachers in adapting teaching methods to current requirements. …”
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Brain Tumor Classification Using FCM, DenseNet, and SVM with Transfer Learning Techniques by Rai Vivek, Tiwari Nirupma

“…The preprocessed images are then fed into a DenseNet model, leveraging transfer learning to extract deep features from the tumor regions. …”
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Finding the original mass: A machine learning model and its deployment for lithic scrapers. by Guillermo Bustos-Pérez

“…This allows for the wide spread implementation of a highly precise machine learning model for predicting initial mass of flake blanks successively retouched into scrapers.…”
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Leveraging real-time data analysis and multiple kernel learning for manufacturing of innovative steels by Wolfgang Rannetbauer, Simon Hubmer, Carina Hambrock, Ronny Ramlau

“…Abstract The implementation of thermally sprayed components in steel manufacturing presents challenges for production and plant maintenance. …”
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