Auditory steady state response can predict declining EF in healthy elderly individuals by Xiaopeng Mao, Xiaopeng Mao, Nelly Shenton, Sadasivan Puthusserypady, Martin Johannes Lauritzen, Krisztina Benedek

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Raw-Data Driven Functional Data Analysis with Multi-Adaptive Functional Neural Networks for Ergonomic Risk Classification Using Facial and Bio-Signal Time-Series Data by Suyeon Kim, Afrooz Shakeri, Seyed Shayan Darabi, Eunsik Kim, Kyongwon Kim

“…To overcome these challenges, this paper proposes a Multi-Adaptive Functional Neural Network (Multi-AdaFNN), a novel method that integrates functional data analysis with deep learning techniques. …”
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THEOREMS ON THE NUMBER OF ROOTS OF A CUBIC EQUATION AND THEIR LOCATION AS A MEANS OF DEVELOPING STUDENTS' VISUAL THINKING by Шойра Абдієва, Ріскелді Тургунбаєв

“…The study of graphs of a cubic function helps to build and prove hypotheses about the number of real roots of a cubic equation and their location, and makes it possible to clearly demonstrate the use of visual thinking. …”
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SGCL-LncLoc: An Interpretable Deep Learning Model for Improving lncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning by Min Li, Baoying Zhao, Yiming Li, Pingjian Ding, Rui Yin, Shichao Kan, Min Zeng

“…In the study, we develope SGCL-LncLoc, a novel interpretable deep learning model based on supervised graph contrastive learning. …”
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Application Of ArtifiCial Intelligence in E-Governance: A Comparative Study of Supervised Machine Learning and Ensemble Learning Algorithms on Crime Prediction. by Niyonzima, Ivan, Muhaise, Hussein, Akankwasa, Aureri

“…The use of Artificial Intelligence has the potential to ameliorate several existing structural inefficiencies in the discharge of governmental functions. Machine learning, a subfield of artificial intelligence, has been used by government agencies in developed countries in crime analysis and predictions. …”
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Stability Analysis of Learning Algorithms for Ontology Similarity Computation by Wei Gao, Tianwei Xu

“…Through studying a training sample, such a function can be learned. It contains a subset of vertices of the ontology graph. …”
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Information-Theoretic Generalization Bounds for Batch Reinforcement Learning by Xingtu Liu

“…We analyze the generalization properties of batch reinforcement learning (batch RL) with value function approximation from an information-theoretic perspective. …”
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Research on the Style of Art Works based on Deep Learning by Shulin Liu

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An Empirical Study of Self-Supervised Learning with Wasserstein Distance by Makoto Yamada, Yuki Takezawa, Guillaume Houry, Kira Michaela Düsterwald, Deborah Sulem, Han Zhao, Yao-Hung Tsai

“…In SSL methods, the cosine similarity is often utilized as an objective function; however, it has not been well studied when utilizing the Wasserstein distance. …”
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Quantum-data-driven dynamical transition in quantum learning by Bingzhi Zhang, Junyu Liu, Liang Jiang, Quntao Zhuang

“…Abstract Quantum neural networks, parameterized quantum circuits optimized under a specific cost function, provide a paradigm for achieving near-term quantum advantage in quantum information processing. …”
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Pulmonary Disease Classification on Electrocardiograms Using Machine Learning by Aboubacar Abdoulaye Soumana, Prajwol Lamichhane, Mehlam Shabbir, Xudong Liu, Mona Nasseri, Scott Helgeson

“…., lung auscultation) and objective measurement of lung function with pulmonary function testing (PFT). These extensive tests, however, can be inaccessible to many patients due to limited resources and availability. …”
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Design Principles for Reinforcement Learning in Congestion Control Environments by Lincoln Kamau Kiarie, Mahsa Derakhshani, Konstantinos G. Kyriakopoulos

“…We assess the impact of various action spaces on learning and investigate how the reward function influences network performance in different scenarios. …”
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CLASSIFYING LIVER DISEASE WITH BOOSTING MACHINE LEARNING APPROACHES by Erol Özçekiç, Ümit Yılmaz

“…Liver diseases pose a significant global health challenge due to their impact on metabolic function and the difficulty of early detection. Traditional diagnostic methods such as liver biopsy have limitations due to their invasive nature and high costs. …”
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Audiovisual Translation and Language Learning: The Promotion of Intralingual Subtitles by Annamaria Caimi

“…The double function of intralingual subtitles as accessibility and didactic aids is considered from a linguistic and cultural perspective, in order to highlight the importance of intralingual subtitled videos as language learning tools. …”
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COVID-19 detection using federated machine learning. by Mustafa Abdul Salam, Sanaa Taha, Mohamed Ramadan

“…During the model training stage, we tried to identify which factors affect model prediction accuracy and loss like activation function, model optimizer, learning rate, number of rounds, and data Size, we kept recording and plotting the model loss and prediction accuracy per each training round, to identify which factors affect the model performance, and we found that softmax activation function and SGD optimizer give better prediction accuracy and loss, changing the number of rounds and learning rate has slightly effect on model prediction accuracy and prediction loss but increasing the data size did not have any effect on model prediction accuracy and prediction loss. finally, we build a comparison between the proposed models' loss, accuracy, and performance speed, the results demonstrate that the federated machine learning model has a better prediction accuracy and loss but higher performance time than the traditional machine learning model.…”
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Risk Assessment of Hip Fracture Based on Machine Learning by Alessio Galassi, José D. Martín-Guerrero, Eduardo Villamor, Carlos Monserrat, María José Rupérez

“…During a training process, ML models learn a function that maps inputs and outputs without previous knowledge of the problem. …”
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Deep Learning-Based Diagnosis Algorithm for Alzheimer’s Disease by Zhenhao Jin, Junjie Gong, Minghui Deng, Piaoyi Zheng, Guiping Li

“…In the segmentation network, the backbone network was simplified, the activation function and loss function were replaced, and the 3D GAM attention mechanism was introduced. …”
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USING REINFORCEMENT LEARNING ALGORITHMS FOR UAV FLIGHT OPTIMIZATION by O. Dutsiak, V. Yuzevych

“…In this work, the main attention was focused on the study of a sub-method of machine learning, which is called learning with emphasis, with a view to optimizing the flight of a UAV by optimizing the process of constructing its path. …”
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Learning the optimal control of coordinated eye and head movements. by Sohrab Saeb, Cornelius Weber, Jochen Triesch

“…At the same time, researchers have suggested several neural models to underly the generation of saccades, but these do not include online learning as a mechanism of optimization. Here, we suggest an open-loop neural controller with a local adaptation mechanism that minimizes a proposed cost function. …”
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Learning from Surprising Observations in Management – Longitudinal Accounts by Jönsson Sten, Jönsson Richard

“…Accounts can be understood as “repair of problematic situations”, which, in turn, may be seen as inference to the best explanation of a surprising observation. We analyse “learning events” as told by prominent Swedish industrial leaders in two sets of interviews with 30 years between them. …”
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