The Application of Reinforcement Learning to Pumps—A Systematic Literature Review by Adetoye Ayokunle Aribisala, Usama Ali Salahuddin Ghori, Cristiano A. V. Cavalcante

“…Finally, ideas for developing a practical reinforcement learning-bundled software for the industry are presented to create an effective system that includes a comprehensive reinforcement learning framework application.…”
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Unsupervised Clustering and Ensemble Learning for Classifying Lip Articulation in Fingerspelling by Nurzada Amangeldy, Nazerke Gazizova, Marek Milosz, Bekbolat Kurmetbek, Aizhan Nazyrova, Akmaral Kassymova

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Changes caused by fatherhood as a source of the need for lifelong learning by Zorica B. Milošević, Petar D. Živojinović

“…In our research, and some research results will be presented in this paper, we tried to determine what changes fatherhood brings to personal, individual development of fathers. …”
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Contrastive representation learning with transformers for robust auditory EEG decoding by Lies Bollens, Bernd Accou, Hugo Van hamme, Tom Francart

“…This study explores the application of contrastive learning, a self-supervised learning technique, to learn robust latent representations of EEG signals. …”
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Machine learning and partial differential equations: benchmark, simplify, and discover by Petros Koumoutsakos

“…Algorithmic alloys of scientific computing and ML present a disruptive potential for the reliable and robust forecasting of complex systems. …”
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An optimal federated learning-based intrusion detection for IoT environment by A. Karunamurthy, K. Vijayan, Pravin R. Kshirsagar, Kuan Tak Tan

“…Analyzing and detecting intrusions by analyzing diverse attack patterns is complex for machine learning algorithms. To overcome this, a federated learning-based intrusion detection approach is presented in this research work that trains deep learning classifiers in IoT networks through federated learning and detects different attacks. …”
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The Line Pressure Detection for Autonomous Vehicles Based on Deep Learning by Xuexi Zhang, Ying Li, Ruidian Zhan, Jiayang Chen, Junxian Li

“…Nowadays, vehicle line pressure detection is an important function of an intelligent transportation system. At present, the line pressure detection algorithms mainly include algorithms based on traditional features and models and algorithms based on deep learning. …”
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The ubiquity of selective attention in the processing of feedback during category learning. by Katerina Dolguikh, Tyrus Tracey, Mark R Blair

“…The present work looks at eye tracking data from six category learning datasets covering a variety of category complexities and types. …”
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Evaluation of Machine Learning Models for Enhancing Sustainability in Additive Manufacturing by Waqar Shehbaz, Qingjin Peng

“…Additive manufacturing (AM) presents significant opportunities for advancing sustainability through optimized process control and material utilization. …”
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Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning by Yasser Abduallah, Jason T. L. Wang, Prianka Bose, Genwei Zhang, Firas Gerges, Haimin Wang

“…A negative Dst value means that the Earth's magnetic field is weakened, which happens during storms. In this paper, we present a novel deep learning method, called the Dst Transformer, to perform short-term, 1-6 hour ahead, forecasting of the Dst index based on the solar wind parameters provided by the NASA Space Science Data Coordinated Archive. …”
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Supervised Learning for Suicidal Ideation Detection in Online User Content by Shaoxiong Ji, Celina Ping Yu, Sai-fu Fung, Shirui Pan, Guodong Long

“…Online communication channels are becoming a new way for people to express their suicidal tendencies. This paper presents an approach to understand suicidal ideation through online user-generated content with the goal of early detection via supervised learning. …”
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Subliminal Cues While Teaching: HCI Technique for Enhanced Learning by Pierre Chalfoun, Claude Frasson

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Medical image classification by incorporating clinical variables and learned features by Jiahui Liu, Xiaohao Cai, Mahesan Niranjan

“…Medical image classification plays an important role in medical imaging. In this work, we present a novel approach to enhance deep learning models in medical image classification by incorporating clinical variables without overwhelming the information. …”
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A survey on multi-agent reinforcement learning and its application by Zepeng Ning, Lihua Xie

“…Multi-agent reinforcement learning (MARL) has been a rapidly evolving field. …”
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Advancing deep learning for expressive music composition and performance modeling by Man Zhang

“…This study presents a comparative analysis of three leading deep learning architectures: Long Short-Term Memory (LSTM) networks, Transformer models, and Generative Adversarial Networks (GANs), for AI-generated music composition and transcription using the MAESTRO dataset. …”
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A virtual reality game for older adults’ immersive learning by Lee Cheng, Wing Yan Jasman Pang, Anthony Kong

“…Abstract This article presents a feasibility study that assessed the effectiveness of a virtual reality (VR) game in training older adults’ cognitive and independent living skills. …”
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A simplified approach for efficiency analysis of machine learning algorithms by Muthuramalingam Sivakumar, Sudhaman Parthasarathy, Thiyagarajan Padmapriya

“…The efficiency of machine learning (ML) algorithms plays a critical role in their deployment across various applications, particularly those with resource constraints or real-time requirements. …”
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From Words to Ratings: Machine Learning and NLP for Wine Reviews by Iliana Ilieva, Margarita Terziyska, Teofana Dimitrova

“…Wine production is an important sector of the food industry in Bulgaria, contributing to both economic development and cultural heritage. The present study aims to show how natural language processing (NLP) and machine learning methods can be applied to analyze expert-written Bulgarian wine descriptions and to extract patterns related to wine quality and style. …”
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SegmentR: Deep learning for automated segmentation with an R interface by James D. Boyko

“…Manual image segmentation is time-consuming and can be subjective, while existing automated solutions often require extensive coding experience or utilize coding languages not typically used by practicing ecologists and evolutionary biologists. Here, I present SegmentR, a user-friendly software package that leverages two state-of-the-art deep learning models – GroundinDINO and an efficient version of the Segment Anything Model (SAM). …”
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Materialese as Border Thinking: The Multimodal Voice of Bilingual Learning Materials by Yeraldine Aldana

“… This paper discusses the emerging and multidimensional category in a study about the development of a didactic material for Spanish learning in bilingual and multimodal settings. Since didactic materials for L2 education seemed to rely on geopolitics of linguistic knowledge and on second generation-based interaction in distance learning, this study aimed at creating a bilingual didactic resource for learning in a hybrid and intercultural environment. …”
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