Overcoming language barriers in film production: the role of VR-based learning in English proficiency by Orathai Piayura, Thidarat Boonmas, Niyom Wongphongkham, Phongthanat Sae-joo, Wanichcha Narongchai, Hava Wongphongkham, Buapun Promphakping, Md Ahbabur Rahman

“…Virtual Reality (VR) has promptly transformed educational practices, presenting immersive environments that boost learning experiences. …”
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Machine learning analysis of ARVC informed by sodium channel protein-based interactome networks by Yanan Zhu, Hui Zhang, Xuan Zhao, Xin Wang, Lina Xing, Sijie Yao, Xiao Jin, Tingting Li, Ting Dai, Xinyue Ding, Zhen Qi, Zongjun Liu

“…In vitro experiments further confirmed that Kaempferol exerted therapeutic effects in ARVC.ConclusionThis study presents a novel approach for identifying potential compounds to treat ARVC. …”
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Machine Learning-Based Predictive Maintenance at Smart Ports Using IoT Sensor Data by Sheraz Aslam, Alejandro Navarro, Andreas Aristotelous, Eduardo Garro Crevillen, Alvaro Martınez-Romero, Álvaro Martínez-Ceballos, Alessandro Cassera, Kyriacos Orphanides, Herodotos Herodotou, Michalis P. Michaelides

“…Towards this end, this study presents a machine learning (ML)-based approach for predicting faults in CHE to improve equipment reliability and overall port performance. …”
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The Impact of COVID-19 Crisis upon the Effectiveness of E-learning in Higher Education Institution by Sharina Osman, Muna Norkhairunnisak Ustadi, Hanna Kamila Zahrol Kamar, Nur Hasliza Johari, Nur ‘Amirah Ismail

“…Even though it is only a temporary approach, less is known in terms of its effectiveness.  The present paper intends to examine the factors contributing to E-learning's effectiveness in a Higher Education Institution in Malaysia amid the COVID-19 crisis. …”
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Screening of oral potentially malignant disorders and oral cancer using deep learning models by Karishma Madhusudan Desai, Pragya Singh, Mahima Smriti, Vivek Talwar, Manav Chaudhary, George Paul, Subhas Chandra Kolli, Parisa Sai Raghava, Golla Vamshi Krishna, C. V. Jawahar, P. K. Vinod, Varma Konala, Ramanathan Sethuraman

“…We trained and tested two deep learning models namely DenseNet201 and FixCaps using 518 images of the oral cavity. …”
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Hyperspectral Anomaly Detection Using Dual-Branch Network Based on Frequency Domain Learning by Xiaoyi Wang, Jun Du, Qingxuan Lv, Peng Wang, Xianchao Zhang, Jian Cheng, Henry Leung

“…To resolve these challenges, this article presents a dual-branch network based on frequency domain learning. …”
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Developing national frameworks for climate services: Experiences, challenges and learnings from across Europe by Nicola Golding, Keith Lambkin, Louise Wilson, Rozemien De Troch, Andreas Marc Fischer, Hans Olav Hygen, Angela Michiko Hama, Anita Verpe Dyrrdal, Ella Jamsin, Piet Termonia, Christopher Hewitt

“…While this article focuses on the experiences and practical learning within Europe, the benefit of establishing an NFCS is global, and many of the challenges and learnings presented here will be relevant anywhere in the world.It is the experience of this group that peer support has accelerated and enhanced the NFCS implementation process, as well as provided a forum for exchange on how to maintain and evolve an operational NFCS. …”
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A Fortran–Python interface for integrating machine learning parameterization into earth system models by T. Zhang, C. Morcrette, C. Morcrette, M. Zhang, W. Lin, S. Xie, Y. Liu, K. Van Weverberg, K. Van Weverberg, J. Rodrigues

“…Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. …”
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A deep learning approach to real-time Markov modeling of ion channel gating by Efthymios Oikonomou, Yannick Juli, Rajkumar Reddy Kolan, Linda Kern, Thomas Gruber, Christian Alzheimer, Patrick Krauss, Andreas Maier, Tobias Huth

“…Ion channel kinetics are typically described using hidden Markov models (HMM), which allow conclusions on the inner workings of the protein. In this study, we present a Deep Learning approach for extracting models from single-channel recordings. …”
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A secure and efficient deep learning-based intrusion detection framework for the internet of vehicles by Hasim Khan, Ghanshyam G. Tejani, Rayed AlGhamdi, Sultan Alasmari, Naveen Kumar Sharma, Sunil Kumar Sharma

“…AES-256 encryption for strong real-time security and access control, along with Secure Multi-Party Computation (SMPC) and Homomorphic Encryption (HE) for privacy-preserving collaborative data processing and encrypted computations, are some of the innovative contributions to IoV security that this work presents. Z-score normalization and median imputation are two excellent methods for prepping high-quality data for a deep learning-based intrusion detection system (IDS). …”
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Research on fine-grained classification of rare metal granite lithology based on deep learning by ZHAO Hengqian, WANG Pan, LIU Zhiguo, MIAO Qunfeng, LI Zhibin, TANG Guanglong, QI Yunfei, XIE Yu, WANG Mengmeng

“…Comparative experiments were carried out using typical deep learning models such as AlexNet, VGG16, ResNet50 and Vision Transformer. …”
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Machine learning based prediction of cognitive metrics using major biomarkers in SuperAgers by Hyo-Bin Lee, So-Yeon Kwon, Ji-Hae Park, Bori Kim, Geon-Ha Kim, Jang-Hwan Choi, Young Mi Park

“…While conventional statistical analyses identified significant differences in only four biomarkers, advanced feature selection and machine learning techniques revealed a broader set of 15 key biomarkers associated with SuperAger status. …”
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Intelligent Thermal Condition Monitoring for Predictive Maintenance of Gas Turbines Using Machine Learning by Sadiq T. Bunyan, Zeashan Hameed Khan, Luttfi A. Al-Haddad, Hayder Abed Dhahad, Mustafa I. Al-Karkhi, Ahmed Ali Farhan Ogaili, Zainab T. Al-Sharify

“…Traditional condition monitoring methods often rely on scheduled inspections, leading to potential downtime and increased maintenance costs. This study presents an AI-driven approach for thermal condition monitoring and the predictive maintenance of gas turbines using machine learning. …”
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Greater neural pattern similarity to the native language is associated with better novel word learning by Yuan Feng, Yuan Feng, Yuan Feng, Yuan Feng, Aqian Li, Aqian Li, Aqian Li, Aqian Li, Jing Qu, Jing Qu, Jing Qu, Jing Qu, Huiling Li, Huiling Li, Huiling Li, Huiling Li, Xiaoyu Liu, Xiaoyu Liu, Xiaoyu Liu, Xiaoyu Liu, Jingxian Zhang, Jingxian Zhang, Jingxian Zhang, Jingxian Zhang, Jiayi Yang, Jiayi Yang, Jiayi Yang, Jiayi Yang, Leilei Mei, Leilei Mei, Leilei Mei, Leilei Mei

“…IntroductionPrevious neuroimaging studies on bilingualism revealed that individuals tend to apply their native-language (L1) neural strategies to second language (L2) learning and processing. Nevertheless, it is still unclear how the utilization of the L1 neural strategies affects visual word learning in a new language.MethodsTo address this question, the present study scanned native Chinese speakers while performing implicit reading tasks before 9-day form-meaning learning in Experiment 1 and before 12-day comprehensive word learning in Experiment 2. …”
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Learning Spectral–Spatial-Former Deep Prior for Hyperspectral Image Superresolution by Zeinab Dehghan, Jingxiang Yang, Abdolraheem Khader, Jian Fang, Liang Xiao

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Identification of Typical Time-Series House Consumption Profiles Based on Unsupervised Learning Techniques by Marcelo Forte, Cindy P. Guzman, Lucas Pereira, Hugo Morais

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The Choice of Training Data and the Generalizability of Machine Learning Models for Network Intrusion Detection Systems by Marcin Iwanowski, Dominik Olszewski, Waldemar Graniszewski, Jacek Krupski, Franciszek Pelc

“…Network Intrusion Detection Systems (NIDS) driven by Machine Learning (ML) algorithms are usually trained using publicly available datasets consisting of labeled traffic samples, where labels refer to traffic classes, usually one benign and multiple harmful. …”
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Similarity and wavelet transform based data partitioning and parameter learning for fuzzy neural network by Pramoda Patro, Krishna Kumar, G. Suresh Kumar, Gandharba Swain

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Exploring Learning and Unlearning (II): Effective Study Methods for the Individual Practice of Professional Singers by Cristina RADU

“…The future belongs to those who will never stop learning[1] - this modern mindset is like a motto for my articles on learning and unlearning. …”
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Deep and hybrid learning of MRI diagnosis for early detection of the progression stages in Alzheimer’s disease by Ibrahim Abunadi

“…The second proposed system is to classify the data set using two deep learning models – ResNet-18 and AlexNet – that are pre-trained based on deep feature map extraction. …”
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