Investigating EFL Undergraduates’ Vocabulary Learning Strategies (VLSs) at a University in Syria by Maisaa Moustafa Daaboulis, Vahid Nimehchisalem, Mustafa Mahdi Jubier

“…Therefore, the present study aims to investigate the use of Vocabulary Learning Strategies (VLSs) among 100 randomly selected EFL Syrian first-year undergraduates in a university in Syria. …”
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Teaching and learning medical English for international medical graduates: A scoping review by Chiew Hong Ng, Yin Ling Cheung

“…Through keyword searches in Scopus and EBSCOhost research databases of English-medium peer-reviewed refereed journals from 2008 to 2022, 33 articles were selected to answer three research questions for the present study. The findings highlight the complexity, diversity and challenges of teaching and learning medical English for international communication for IMGs in terms of learners' needs and difficulties in learning medical English (e.g., low proficiency levels and issue of communicative competence), specific courses implemented for IMGs to enhance English (e.g., English for medical purposes,  English medium international project, and interdisciplinary collaboration using multimedia) and conceptual frameworks guiding teaching and learning in international multilingual environments (e.g., clinical communication skills and genre approach). …”
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Improving the criteria of electricity consumptionforecasting in petrochemical industrial units based ondeep learning by Ehsan Tavakoli Garmaserh, Mehran Emadi

“… Accurate forecasting of electricity consumption in petrochemical industrial units is essential for optimizing energy management and ensuring operational efficiency. This study presents a novel deep learning framework that integrates advanced feature engineering and Long Short-Term Memory (LSTM) networks to address the challenges posed by irregular seasonal trends and dynamic consumption patterns. …”
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Decentralized queue control with delay shifting in edge-IoT using reinforcement learning by Viacheslav Kovtun

“…Abstract The article presents an adaptive approach to modelling and managing the service process of requests at peripheral nodes of edge-IoT systems. …”
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Novel Deep Learning-Based Facial Forgery Detection for Effective Biometric Recognition by Hansoo Kim

“…However, these systems are increasingly vulnerable to sophisticated forgery techniques. This study presents a novel deep learning framework optimized for texture analysis to detect facial forgeries effectively. …”
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A hybrid machine learning approach for the personalized prognostication of aggressive skin cancers by Tom W. Andrew, Mogdad Alrawi, Ruth Plummer, Nick Reynolds, Vern Sondak, Isaac Brownell, Penny E. Lovat, Aidan Rose, Sophia Z. Shalhout

“…Merkel cell carcinoma (MCC) is the most aggressive form of skin cancer that often presents in advanced stages and is associated with poor survival rates. …”
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Deep Learning-Emerged Grid Cells-Based Bio-Inspired Navigation in Robotics by Arturs Simkuns, Rodions Saltanovs, Maksims Ivanovs, Roberts Kadikis

“…We then present experimental results where a grid cell network was trained using trajectories from a mobile unmanned ground vehicle (UGV) robot. …”
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Financial constraints and Islamic finance: Lesson learned from external financing perspective by Achmad Tohirin, Mohd Adib Ismail

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Integer linear programming for unsupervised training set selection in molecular machine learning by Matthieu Haeberle, Puck van Gerwen, Ruben Laplaza, Ksenia R Briling, Jan Weinreich, Friedrich Eisenbrand, Clémence Corminboeuf

“…Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relevance of an ILP formulation to select molecular training sets for predictions of size-extensive properties. …”
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Unraveling the power of NAP-CNB’s machine learning-enhanced tumor neoantigen prediction by Almudena Mendez-Perez, Andres M Acosta-Moreno, Carlos Wert-Carvajal, Pilar Ballesteros-Cuartero, Ruben Sánchez-García, Jose R Macias, Rebeca Sanz-Pamplona, Ramon Alemany, Carlos Oscar Sorzano, Arrate Munoz-Barrutia, Esteban Veiga

“…In this study, we present a proof-of-concept classical vaccination experiment that validates the in silico identification of tumor neoantigens (TNAs) using a machine learning-based platform called NAP-CNB. …”
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People counting using IR-UWB radar sensors and machine learning techniques by Ange Joel Nounga Njanda, Jocelyn Edinio Zacko Gbadoubissa, Emanuel Radoi, Ado Adamou Abba Ari, Roua Youssef, Aminou Halidou

“…This study aims to detect and count people using impulse radio ultra-wideband radar and machine learning algorithms. However, the data quality, difficulty distinguishing human signals from noise and clutter, and instances where human presence is not detected make it challenging to count multiple humans. …”
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Enhance College AI Course Learning Experience with Constructivism-Based Blog Assignments by Di Wang, Xingbo Dong, Jingxun Zhong

“…This study explores the specific impacts of blogs on students’ learning abilities, learning experiences, academic outcomes, and overall satisfaction within the AI course. …”
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Gait and Trajectory Optimization by Self-Learning for Quadrupedal Robots with an Active Back Joint by Ariel Masuri, Oded Medina, Shlomi Hacohen, Nir Shvalb

“…This paper presents an efficient technique for a self-learning dynamic walk for a quadrupedal robot. …”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. …”
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Deep Learning-Based Vision Systems for Robot Semantic Navigation: An Experimental Study by Albandari Alotaibi, Hanan Alatawi, Aseel Binnouh, Lamaa Duwayriat, Tareq Alhmiedat, Osama Moh’d Alia

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Machine Learning Model for Road Anomaly Detection Using Smartphone Accelerometer Data by Mahdi Zareei, Carlos Alonzo Lopez Castaneda, Faisal Alanazi, Fausto Granda, Jesus Arturo Perez-Diaz

“…This paper presents a vibration-based machine learning approach for road surface monitoring using smartphone sensors. …”
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On-farm welfare monitoring system for goats based on Internet of Things and machine learning by Yuan Rao, Min Jiang, Wen Wang, Wu Zhang, Ruchuan Wang

“…Second, the monitoring hardware and software systems were presented in detail, aiming at supporting remote operation and maintenance, and convenience for further development. …”
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Automatic identification of Dong Son antique glass artifacts using evolving learning by Anh-Khoi Ngo-Ho, Hoang-Bac Bui, Van-Trieu Pham

“…Our research is motivated by the unique conditions present in archaeology, where we seek to employ evolving learning algorithms to archaeological databases, comparing and selecting the most suitable model that aligns with the archeological dataset's performance. …”
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The Effectiveness of Using Canva Application as A Science Learning Media in Elementary Schools by Dyah Aris Susanti, Nina Sultonurohmah, Eva Dewi Purwitasari

“… This study aims to analyze the effectiveness of using the Canva application as a learning medium in science subjects at elementary schools through a literature review method. …”
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Development of Animation Learning Videos Based on Ethnomathematics Using Plotagon on Spldv Material by Raden Roro Shinta Luthfiana Yasri, Endah Wulantina

“…The learning media used at SMP Negeri 6 Metro are textbooks the school provides. …”
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