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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Deep learning and georeferenced RGB-D imaging for hydroponic strawberry yield mapping by Camilo Pardo-Beainy, Carlos Parra, Leonardo Solaque, Won Suk Lee

“…This study evaluates four instance segmentation algorithms: YOLOv8n, YOLOv8s, YOLOv8m, and YOLOv8l, along with a low-cost GNSS RTK system to detect and count strawberries in a hydroponic environment. …”
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Production monitoring and machine tracking in underground mines based on a collision avoidance system: A case study by Artur Skoczylas, Natalia Duda-Mróz, Wioletta Koperska, Paweł Stefaniak, Paweł Śliwiński

“…Consequently, the development of validation algorithms, including error correction and adaptive filtering, was imperative. …”
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Analysis of potential molecular targets and mechanisms of brominated flame retardants in causing osteoarthritis using network toxicology, machine learning, SHAP analysis, and molec... by Yu Liu, Guohang Shen, Zidong Xia, Ruoyan Wang, Yupei Dai

“…Subsequently, a comprehensive machine learning workflow involving 113 different algorithms was used to identify 10 core target genes as potential mediators of BDE-47-induced osteoarthritis. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. Notably, compared to Hourglass, HRNet, and HigherHRNet, YOLORM reduced parameters by 99.3%, 92.9%, and 96.8%, and computational cost by 98.8%, 90.2%, and 95.3%, respectively, while concurrently improving precision and recall. …”
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Carrying out entrance control of “Informatics” students’ knowledge with use of specialized computer system by L. V. Larina

“…The models of integer linear programming and algorithms of discrete optimization for solving problems of forming optimum tests, offered earlier by the author are used in the system. …”
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Comparison of Cuff Leak Test, Laryngeal Ultrasonography, and Videolaryngoscopy for the prediction of post-extubation stridor by Rubina Khullar Mahajan, Apoorva Gupta, Parshotam Lal Gautam, Gunchan Paul, Vikalp Khatri

“…VL scale >2 predicted a significantly higher (p=0.001) risk of PES, (sensitivity 52.1%, specificity 92.98%, PPV 75%, NPV 82.81%, accuracy 81.25%). Conclusions An algorithmic approach should be adopted. All patients should undergo CLT before extubation. …”
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Access and benefit sharing biological materials for machines: Artificial intelligence, machine learning and deep learning by Charles Lawson, Elizabeth Englezos, Michelle Rourke

“…Building in ‘explainability’ to the AI algorithms may be a solution, at least in part, to delivering on fair and equitable ABS. …”
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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

“…Particular attention is paid to data-driven methods, including probabilistic models such as Hidden Markov Models (HMMs), classical machine learning algorithms such as Support Vector Machines (SVMs) and K-Nearest Neighbors (KNN), and deep learning architectures such as Convolutional Neural Networks (CNNs), all of which have demonstrated high accuracy in both laboratory and real-world settings. …”
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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

“…Finally, we employed LASSO regression, SVM-RFE, XGBoost, and random forest algorithms to further predict potential targets, followed by validation through molecular docking.ResultsLeeches may influence cellular immunity by modulating immune receptor activity, particularly through the activation of RGS10, CAPS2, and OPA1, thereby impacting the pathology of Type 2 Diabetes Mellitus (T2DM).DiscussionHowever, it is important to note that our results lack experimental validation; therefore, further research is warranted to substantiate these findings.…”
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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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Remote Sensing Techniques for Assessing Snow Avalanche Formation Factors and Building Hazard Monitoring Systems by Natalya Denissova, Serik Nurakynov, Olga Petrova, Daniker Chepashev, Gulzhan Daumova, Alena Yelisseyeva

“…Key data sources included satellite platforms such as Sentinel-1, Sentinel-2, TerraSAR-X, and Landsat-8, combined with machine learning, data fusion, and change detection algorithms to process and interpret the data. The review found that remote sensing significantly improves avalanche monitoring by providing continuous, large-scale coverage of snowpack stability and terrain features. …”
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Contributon-Informed Approach to RPV Irradiation Study Using Hybrid Shielding Methodology by Mario Matijević, Krešimir Trontl, Dubravko Pevec

“…The complex design of a typical PWR is posing a deep penetration shielding problem for which an elaborate simulation model is needed, not only in geometrical aspects but also in efficient computational algorithms for solving particle transport. This paper presents such a hybrid shielding approach of FW-CADIS for characterization of the reactor pressure vessel (RPV) irradiation using SCALE6.2.4 code package. …”
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Investigating the Impact of Earnings Management and Internal Control on the Financial Performance of Banks Using a Spatial Artificial Intelligence Approach by Wisam Fadhil Hanoon, Parviz Piri, Ali Ashtab

“…Deep neural networks identified different patterns in the two countries and deep learning algorithms determined the relative importance of the variables. …”
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A dataset for classifying phrases and sentences into statements, questions, or exclamations based on sound pitchMendeley Data. by Ayub Othman Abdulrahman, Shanga Ismail Othman, Gazo Badran Yasin, Meer Salam Ali

“…The dataset offered has significant advantages for formulating and testing pitch-based speech classification algorithms, furthers the work on pronunciation modelling for languages lacking sufficient resources. …”
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PaleAle 6.0: Prediction of Protein Relative Solvent Accessibility by Leveraging Pre-Trained Language Models (PLMs) by Wafa Alanazi, Di Meng, Gianluca Pollastri

“…In particular, recent breakthroughs in deep learning—driven by the integration of natural language processing (NLP) algorithms—have significantly advanced the field of protein research. …”
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Breaking Down Walls: A Literature Review on the Power of Artificial Intelligence in Enhancing Universal Language Connection by Sheida Jamalnia, Zahra Karimian

“…However, challenges such as translation inaccuracies, algorithmic biases, and ethical concerns necessitate continuous improvement and human oversight.Conclusion: AI is revolutionizing global communication by overcoming linguistic barriers and fostering inclusive interactions. …”
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Numerical Modeling Tools and S-derivatives by Anatoly Nikolaevich Morozov

“…The constructions are algorithmic in nature and can be applied in numerically computer research of various relevant models.…”
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Smart deep learning model for enhanced IoT intrusion detection by Faisal S. Alsubaei

“…This paper addresses these limitations with large preprocessing steps followed by hyperparameter tuning of machine learning XGBoost and deep learning Sequential Neural Network (OSNN) algorithms through Grid Search for their best values to improve multiclass intrusion detection across varied datasets. …”
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