A novel data representation framework based on nonnegative manifold regularisation by Yan Jiang, Wei Liang, Jintian Tang, Hongbo Zhou, Kuan-Ching Li, Jean-Luc Gaudiot

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Applications of machine learning in gravitational-wave research with current interferometric detectors by Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

“…In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. …”
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Exploring the typhoon intensity forecasting through integrating AI weather forecasting with regional numerical weather model by Hongxiong Xu, Yang Zhao, Zhao Dajun, Yihong Duan, Xiangde Xu

“…Abstract Recent advancements in artificial intelligence (AI) have notably enhanced global weather forecasting, yet accurately predicting typhoon intensity remains challenging. This is largely due to constraints inherent in regression algorithm properties including deep neural networks and inability of coarse resolution to capture the finer-scale weather processes. …”
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Lightweight CNC digital process twin framework: IIoT integration with open62541 OPC UA protocol by Arivazhagan Anbalagan, Waqir Yusuf Zanhar, Shone George, Marcos Kauffman, Tengfei Long

“…A novel “match-rule” algorithm is also introduced linking GM codes with sensor data, enhancing traceability. …”
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Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program by Adrian H. Zai, Jeremiah G. Ronquillo, Regina Nieves, Henry C. Chueh, Joseph C. Kvedar, Kamal Jethwani

“…The purpose of this study was to validate a previously developed heart failure readmission predictive algorithm based on psychosocial factors, develop a new model based on patient-reported symptoms from a telemonitoring program, and assess the impact of weight fluctuations and other factors on hospital readmission. …”
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CLASSIFICATION OF AUDIO SOURCE CHANNELS USING TIME-FREQUENCY ANALYSIS AND DECISION TREE CLASSIFIER by Sagir Lawan, Ashraf A. Ahmad, Amina Jibril, Idrisu Mohammed, Kulu Ahmad Amalo

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Classification of periodontitis stage and grade using natural language processing techniques. by Nazila Ameli, Tahereh Firoozi, Monica Gibson, Hollis Lai

“…Our proposed BERT model predicted the patients' stage and grade with 77% and 75% accuracy, respectively. …”
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Application of Neural Network Models for Analyzing the Impact of Flight Speed and Angle of Attack on Flow Parameter Non-Uniformity in a Turbofan Engine Inlet Duct by Adam Kozakiewicz, Maciej Adamczyk, Rafał Kieszek

“…The ANN was trained using the CFG algorithm, and the predictive accuracy was assessed through the determination coefficients computed by comparing ANN-based estimates with numerical simulation results. …”
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A localization strategy combined with transfer learning for image annotation. by Zhiqiang Chen, Leelavathi Rajamanickam, Jianfang Cao, Aidi Zhao, Xiaohui Hu

“…The optimal K value is obtained experimentally and used to determine the number of predicted labels, thereby solving the empty label set problem that occurs when the predicted label values of images are below a fixed threshold. …”
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Implicit Is Not Enough: Explicitly Enforcing Anatomical Priors inside Landmark Localization Models by Simon Johannes Joham, Arnela Hadzic, Martin Urschler

“…Currently, Anatomical Landmark Localization (ALL) is mainly solved by deep-learning methods, which cannot guarantee robust ALL predictions; there may always be outlier predictions that are far from their ground truth locations due to out-of-distribution inputs. …”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

“…We employed radial basis function (RBF) and multilayer perceptron (MLP) algorithms for ANN modeling. The optimal MLP configuration, utilizing the Levenberg–Marquardt (Trainlm) algorithm, consisted of three hidden layers with 20, 17, and 9 neurons, respectively, while the optimal RBF network contained 43 neurons. …”
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Hull form optimization of fully parameterized small ships using characteristic curves and deep neural networks by Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo

“…To address this issue, this paper proposes an approach that involves defining a range of hull forms with characteristic curves, predicting their performance using Deep Neural Networks (DNNs), and subsequently determining the optimal hull form based on these predictions. …”
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SPINE: SParse eIgengene NEtwork linking gene expression clusters in Dehalococcoides mccartyi to perturbations in experimental conditions. by Cresten B Mansfeldt, Benjamin A Logsdon, Garrett E Debs, Ruth E Richardson

“…Based on the model predictions, we discovered new response mechanisms for DMC, notably when the bacterium is exposed to solvent toxicity. …”
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Interventions to improve referrals from primary care to outpatient specialist services for chronic conditions: a systematic review and framework synthesis update by Layla Bolton Saghdaoui, Smaragda Lampridou, Sara Tavares, Rachael Lear, Alun Huw Davies, Mary Wells, Sarah Onida

“…When used alone, referral algorithms and staff education were less effective at improving referral rates or appropriateness. …”
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Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study. by Alpha Forna, Ilaria Dorigatti, Pierre Nouvellet, Christl A Donnelly

“…<h4>Background</h4>Machine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. …”
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Acute Coronary Syndrome in Patients With 2 Type Diabetes Mellitus (Review of Literature; Description of the Clinical Case) by Bilous Z., Abrahamovych О., Mazur N., Ryabokon S., Ilenkiv N., Bevza N.

“…The effect of each individual pathogenic marker on the clinical course and complications of these patients remains undetermined; therefore, the study of the clinical course of ACS with comorbid type 2 diabetes mellitus and the prediction of complications are important for improving the prognosis in these patients. …”
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Interactive map «Patient Enquiry» as a teaching method for medical students by I. A. Koroleva, N. V. Efremova, N. I. Slashcheva, L. A. Fedotova

“…Medical students must structure, present and remember the algorithm for questioning the patient. The creation of such texts provides favorable conditions for the implementation of the principles of visibility and communication. …”
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Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review by Khalid H. Arar, Hamit Özen, Gülşah Polat, Selahattin Turan

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DNN-Based ADNMPC of an Industrial Pickling Cold-Rolled Titanium Process via Field Enhancement Heat Exchange by Biao Yang, Jinhui Peng, Wei Li, Youling Li, Huilong Luo, Zhuming Zhang, Shenghui Guo, Shimin Zhang, Hezhou Su, Yaming Shi

“…The identifier of the direct adaptive nonlinear model identification and the controller of the adaptive nonlinear model predictive control are designed based on series-parallel dynamic neural network training by RLS algorithm with variable incremental factor, gain, and forgetting factor. …”
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Needle detection and localisation for robot‐assisted subretinal injection using deep learning by Mingchuan Zhou, Xiangyu Guo, Matthias Grimm, Elias Lochner, Zhongliang Jiang, Abouzar Eslami, Juan Ye, Nassir Navab, Alois Knoll, Mohammad Ali Nasseri

“…When evaluated on ex‐vivo pig eyes, the top performing network successfully detected all needles in the dataset and localised them with an Intersection over Union value of 0.55. The algorithm was evaluated by comparing the depth of the top and bottom edge of the predicted bounding box to the ground truth. …”
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