Wearing WHOOP More Frequently Is Associated with Better Biometrics and Healthier Sleep and Activity Patterns by Gregory J. Grosicki, Finnbarr Fielding, Jeongeun Kim, Christopher J. Chapman, Maria Olaru, William von Hippel, Kristen E. Holmes

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Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Personalization and adaptability emerge as key themes, particularly in multi-occupant contexts, while multi-sensor data fusion promises to enhance detection stability and reduce false positives. …”
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Real-Time Cloth Simulation in Extended Reality: Comparative Study Between Unity Cloth Model and Position-Based Dynamics Model with GPU by Taeheon Kim, Jun Ma, Min Hong

“…To overcome the limitations of traditional CPU-based physics simulations, we designed and optimized highly parallelized algorithms utilizing Unity’s Compute Shader framework. …”
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Explore potential immune-related targets of leeches in the treatment of type 2 diabetes based on network pharmacology and machine learning by Tairan Hu, Zhaohui Fang

“…The objective of this study was to predict potential therapeutic targets of leeches in the treatment of T2DM.MethodsWe collected active components and targets associated with leeches from four online databases, while disease-related targets were sourced from the GeneCards and OMIM databases. …”
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K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain by Vivek Kumar, Diego Reforgiato Recupero, Rim Helaoui, Daniele Riboni

“…The use of superior algorithms and complex architectures in language models have successfully imparted human-like abilities to machines for specific tasks. …”
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Face Anti-spoofing Detection Based on Novel Encoder Convolutional Neural Network and Texture’s Grayscale Structural Information by Marwa Radad, Amira E. Enab, Salah S. Elagooz, Nawal A. El-Fishawy, Mohamed A. El-Rashidy

“…Traditional face anti-spoofing detection techniques often rely on grey texture elements while disregarding RGB color intensity features in face images, which lead to a loss of certain facial information. …”
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Instances for the problem of pre-positioning emergency supplies by Renata Turkeš, Kenneth Sörensen

“…In addition, the authors developed a tool to algorithmically generate arbitrarily many diverse random instances of any size. …”
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Application of Quantitative Interpretability to Evaluate CNN-Based Models for Medical Image Classification by Nuan Cui, Yingjie Wu, Guojiang Xin, Jiaze Wu, Liqin Zhong, Hao Liang

“…Class Activation Mapping (CAM) algorithms generated heatmaps visualizing influential regions. …”
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Evaluation of Machine Learning Models for Sentiment Analysis in the South Sumatra Governor Election Using Data Balancing Techniques by Febriyanti Panjaitan, Win Ce, Hery Oktafiandi, Ghanim Kanugrahan, Yudi Ramdhani, Vito Hafizh Cahaya Putra

“…This study compares five machine learning algorithms (SVM, Naïve Bayes, KNN, Decision Tree, and Random Forest) and examines the impact of data balancing on their performance. …”
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UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework by Biyao Che, Zixiao Wang, Ying Chen, Liang Guo, Yuan Liu, Yuan Tian, Jizhuang Zhao

“…However, data encryption can significantly increase computing time, limiting its large-scale deployment. While hardware acceleration can be an effective solution, existing research has largely focused on a single hardware type, which hinders the acceleration of FL across the various heterogeneous hardware of the participants. …”
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Advancing Arabic Word Embeddings: A Multi-Corpora Approach with Optimized Hyperparameters and Custom Evaluation by Azzah Allahim, Asma Cherif

“…For sentiment analysis, vocabulary size was critical, while in similarity scoring, the FastText models achieved the highest scores, particularly with smaller window and vector sizes. …”
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Neighborhood Information Aggregation and Multi-View Feature Extraction-Based Contrastive Graph Clustering by Liulong Yao, Jinrong Cui, Yazi Xie, Chengli Sun

“…Extensive experiments on five benchmark datasets show that our proposed method outperforms most other clustering algorithms.…”
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Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

“…DeepMol's predefined configurations and customizable objective functions make it accessible to users at all skill levels while enabling efficient and reproducible workflows. …”
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Dynamic Response Prediction of Railway Bridges Considering Train Load Duration Using the Deep LSTM Network by Sui Tan, Xiandong Ke, Zhenhao Pang, Jianxiao Mao

“…Therefore, this study develops a novel framework, combining the train–bridge coupling mechanism and deep learning algorithms to efficiently predict the train-induced bridge responses while considering train load duration. …”
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Multi-Feature Lightweight DeeplabV3+ Network for Polarimetric SAR Image Classification with Attention Mechanism by Junfei Shi, Shanshan Ji, Haiyan Jin, Yuanlin Zhang, Maoguo Gong, Weisi Lin

“…Besides, multiple features can provide more complementary information, while feature selection is crucial for classification. …”
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Design and Analysis of a Serial Manipulator for Pick and Drop Objects for Material Handling at Uiri Metal Forming Workshop. by Behangana, Abert

“…Future recommendations include refining control algorithms, integrating advanced safety features, and exploring innovative materials to improve performance. …”
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Implications of machine learning techniques for prediction of motor health disorders in Saudi Arabia by Ehab M. Almetwally, I. Elbatal, Mohammed Elgarhy, Amr R. Kamel

“…The dataset was partitioned into a training set comprising 70 % of the data and a testing set containing 30 % of the data using the ML algorithms. The results of the implemented algorithms demonstrated that the RF technique attained an accuracy of 100 %, while the DT technique scored an accuracy of 63 %, the NB approach scored an accuracy of 69 %, the K-NN technique scored an accuracy of 76 %, and the SVM technique scored an accuracy of 90 %. …”
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High-Quality Multispectral Image Reconstruction for the Spectral Camera Based on Ghost Imaging via Sparsity Constraints Using CoT-Unet by Tao Hu, Jianxia Chen, Shu Wang, Jianrong Wu, Ziyan Chen, Zhifu Tian, Ruipeng Ma, Di Wu

“…Compared with conventional algorithms such as DGI and CS, our method significantly improves the quality of reconstructed images. …”
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Multi-slice electron ptychographic tomography for three-dimensional phase-contrast microscopy beyond the depth of focus limits by Andrey Romanov, Min Gee Cho, Mary Cooper Scott, Philipp Pelz

“…We discuss further experimental and algorithmic improvements necessary to also resolve single weakly scattering atoms in 3D.…”
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Unraveling the co-morbidity between COVID-19 and neurodegenerative diseases through multi-scale graph analysis: A systematic investigation of biological databases and text mining by Negin Sadat Babaiha, Stefan Geissler, Vincent Nibart, Heval Atas Güvenilir, Vinay Srinivas Bharadhwaj, Alpha Tom Kodamullil, Juergen Klein, Marc Jacobs, Martin Hofmann-Apitius

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