Deep context-attentive transformer transfer learning for financial forecasting by Ling Feng, Ananta Sinchai

“…This study presents 2CAT (CNN-Correlation-based Attention Transformer), a deep learning model for financial time-series forecasting. …”
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Role of Social Partners for Work-Based Learning: Results of Surveys by Buligina Ilze, Sloka Biruta, Kantāne Ināra, Līce Anita

“…Introduction of work-based learning (WBL) in Latvia has required new approaches in decision making of different stakeholders. …”
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When money is not enough: awareness, success, and variability in motor learning. by Harry Manley, Peter Dayan, Jörn Diedrichsen

“…Without such awareness, learning was only present when extrinsic noise was added to the feedback, but not when task success or variability was manipulated in isolation; learning was also much slower. …”
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A neural network model for the evolution of reconstructive social learning by Jacob Chisausky, Inès Marguerite Daras, Franz J. Weissing, Magdalena Kozielska

“…To represent the reconstructive nature of social learning, we present a modelling framework that incorporates the evolution of a neural network and a simple yet biologically realistic learning mechanism. …”
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Improving the Efficiency of Photovoltaic Panels Using Machine Learning Approach by Rashmita Khilar, G. Merlin Suba, T. Sathesh Kumar, J. Samson Isaac, Santaji Krishna Shinde, S. Ramya, V. Prabhu, Kuma Gowwomsa Erko

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Improving the Quality of Learning in Law Schools by Improving Student Assessment by Nicolette Rogers

“…Whilst it is essential when considering how to encourage students to adopt qualitative learning approaches to consider the effect of all elements in the learning “eco-system” on the student, it is my thesis that student assessment plays not only an important, but a critical role in influencing their approaches to learning tasks. …”
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Shuffle Model of Differential Privacy: Numerical Composition for Federated Learning by Shaowei Wang, Sufen Zeng, Jin Li, Shaozheng Huang, Yuyang Chen

“…., in mobile edge computing or IoT environments), the shuffle model has recently emerged as a promising paradigm for differentially private federated learning. Despite many efforts of privacy accounting for federated learning with many sequential rounds in the shuffle model, they suffer from generality and tightness. …”
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Efficient Learning of Hyperrectangular Invariant Sets Using Gaussian Processes by Michael Enqi Cao, Matthieu Bloch, Samuel Coogan

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Narrative portraits: affirmative approaches to understanding learning disability in the everyday by Tom Ryan

“…Considering the ‘joy deficit’ within disability research this paper highlights the disruptive potential narrative portraits bring to family sociology and disability studies. This paper presents a narrative portrait as a case study, taken from research carried out with 14 siblings of people with learning disabilities from the UK. …”
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Deep Learning for Recognition of Digital Modulations: A Detailed Study by MohammadMohsen Jadidi, Abbas Mohammadi

“…In the recent years, deep learning techniques have received much attention due to their excellent performance in signal, audio, image and video processing. …”
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Emotion on the edge: An evaluation of feature representations and machine learning models by James Thomas Black, Muhammad Zeeshan Shakir

“…This paper presents a comprehensive analysis of textual emotion classification, employing a tweet-based dataset to classify emotions such as surprise, love, fear, anger, sadness, and joy. …”
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Review on Deep Learning and Neural Network Implementation for Emotions Recognition by Renas Rajab Asaad

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Multilingualism as a Learning Resource in Map-Based Geography Lessons by Neli Heidari, Johannes Heuzeroth

“… • Pedagogical implications of the present study to empower teachers to integrate multilingualism. …”
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Dynamical systems-inspired machine learning methods for drought prediction by Andrew Watford, Chris T. Bauch, Madhur Anand

“…We conclude by proposing more sophisticated extensions to the methods presented here, both with and without the availability of precipitation data, that draw on the existing dynamical systems and machine learning literature to enable better quantitative predictions of key drought indicators.…”
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Interpretable Machine Learning Techniques for an Advanced Crop Recommendation Model by Mohamed Bouni, Badr Hssina, Khadija Douzi, Samira Douzi

“…Our research addresses this critical imperative by introducing an innovative predictive model that refines crop recommendation systems through advanced machine learning techniques, specifically random forest and SHapley Additive exPlanations (SHAP). …”
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An improved multi-object instance segmentation based on deep learning by Nawaf Alshdaifat, Mohd Azam Osman, Abdullah Zawawi Talib

“… Given the recent breakthroughs in recent years, Deep learning (DL) networks have attracted growing interest and attention by researchers and scholars alike due to its importance in detecting and instance segmentation of objects in an image. …”
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Personalized pedagogical learning of highly qualified residents and postgraduate students by A. I. Artyukhina, V. M. Chizhova, V. I. Chumakov

“…The study involved 106 residents and 166 full­time and part-time postgraduate students.Results. The presented system of training of highly qualified residents and postgraduate students is based on psychological and pedagogical diagnostics of students, ensures the continuity of professional and pedagogical development, integrates the following characteristics inherent in personalized learning: motivation, joint creation, self­knowledge and social construction. …”
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Enhancing breast cancer diagnosis through machine learning algorithms by Javad Amraei, Aboulfazl Mirzapoor, Kiomars Motarjem, Mohammad Abdolahad

“…Bearing in mind that there are more than 100 types of cancer, each presenting different symptoms, its early detection is indeed a big challenge. …”
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Identifying Cocoa Flower Visitors: A Deep Learning Dataset by Wenxiu Xu, Saba Ghorbani Barzegar, Dong Sheng, Manuel Toledo-Hernández, ZhenZhong Lan, Thomas Cherico Wanger

“…Overall, this dataset is useful to compare the performance of deep learning model architectures on images with low contrast images and difficult detection targets. …”
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Interracial contact shapes racial bias in the learning of person-knowledge by Margaret Welte, Tzipporah P. Dang, Shaina Rosenblum, Jennifer T. Kubota, Jasmin Cloutier

“…To better understand how perceived race can bias person memory, the present study examined how self-identified White perceivers’ interracial contact impacts learning of perceptual cues and person-knowledge about perceived Black and White others over five sessions of training. …”
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