FedDSL: A Novel Client Selection Method to Handle Statistical Heterogeneity in Cross-Silo Federated Learning Using Flower Framework by Vineetha Pais, Santhosha Rao, Balachandra Muniyal

“…The model is applied with various aggregation algorithms, including FedAvg, FedProx, and FedAdam. …”
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Reservoir Computing-Based Digital Self-Interference Cancellation for In-Band Full-Duplex Radios by Zhikai Liu, Haifeng Luo, Tharmalingam Ratnarajah

“…Our results reveal that the RC-DSIC scheme attains 99.84% of the performance offered by PL-based DSIC algorithms while requiring only 1.51% of the computational demand. …”
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Biological and Biosimilar Medicines in Contemporary Pharmacotherapy for Metabolic Syndrome by Wiktoria Górecka, Daria Berezovska, Monika Mrozińska, Grażyna Nowicka, Monika E. Czerwińska

“…Although treatment algorithms are generally well established and primarily based on synthetic pharmaceuticals, they are increasingly being supplemented by biological and biosimilar agents. …”
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Advancing Particle Tracking: Self-Organizing Map Hyperparameter Study and Long Short-Term Memory-Based Outlier Detection by Max Klein, Niklas Dormagen, Lukas Wimmer, Markus H. Thoma, Mike Schwarz

“…Particle tracking velocimetry (PTV) forms the basis for many fluid dynamic experiments, in which individual particles are tracked across multiple successive images. …”
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ML-Based Control Strategy for PHEV Under Predictive Vehicle Usage Behaviour by Aleksandr Doikin, Aleksandr Korsunovs, Felician Campean, Oscar García-Afonso, Enrico Agostinelli

“…This paper introduces a novel strategy for an intelligent plug-in hybrid electric vehicle (PHEV) energy optimization strategy based on machine learning (ML) prediction of the upcoming journey, without recourse to navigation or other external data, which underpins many of the existing approaches. This study, based on extended real-world data (journeys history from 10 vehicles over 12 months), shows that trip patterns can be learnt quite effectively using classic ML classification algorithms. …”
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Development and Validation of DIANA (Diabetes Novel Subgroup Assessment tool): A web-based precision medicine tool to determine type 2 diabetes endotype membership and predict indi... by Viswanathan Baskar, Mani Arun Vignesh, Sumanth C Raman, Arun Jijo, Bhavadharini Balaji, Nico Steckhan, Lena Maria Klara Roth, Moneeza K Siddiqui, Saravanan Jebarani, Ranjit Unnikrishnan, Viswanathan Mohan, Ranjit Mohan Anjana

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PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY by F. B. Adeleke, A. S Odetoye, E. E. Akerele, O. S. Folorunso, A. A. Bashiru

“…However, barriers such as high implementation expenses, insufficient technical expertise, and algorithmic biases continue to impede widespread adoption. …”
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Time‐of‐Arrival of Coronal Mass Ejections: A Two‐Phase Kinematics Approach Based on Heliospheric Imaging Observations by Evangelos Paouris, Angelos Vourlidas

“…The main physical reason is our incomplete understanding of CME propagation in the inner heliosphere. Therefore, many ToA forecasting algorithms rely on simple empirical relations to represent the interplanetary propagation phase using, mostly, kinematic information from coronagraphic observations below 30 solar radii (Rs) and a couple rather simplifying assumptions of constant direction and speed for the transient. …”
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3D Reconstruction of the Human Colon From Capsule Endoscope Video by Pal Anders Floor, Ivar Farup, Marius Pedersen

“…As capsule endoscope images contain distortion and artifacts non-ideal for many 3D reconstruction algorithms, the problem is challenging. …”
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Clinical Utility of Bladder Cancer Biomarkers by Laura Maria Krabbe, Georgios Gakis, Yair Lotan

“…Prognostic and predictive biomarkers have the potential to fundamentally change bladder cancer treatment algorithms, which may result in improved patient comfort and oncological outcomes and may also decrease the socioeconomic burden of the disease. …”
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Petri graph neural networks advance learning higher order multimodal complex interactions in graph structured data by Alma Ademovic Tahirovic, David Angeli, Adnan Tahirovic, Goran Strbac

“…The work opens new directions in learning over complex structures, transcending transformer-based and traditional hypergraph-based algorithms. We validate results through theoretical analysis and real-world experiments, while demonstrating superior performance in, e.g., stock market prediction.…”
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Resolving Covid-19 with Blockchain and AI by Suyogita Singh, Satya Bhushan Verma

“…Blockchain technology was anticipated to be crucial in the effort to contain the COVID-19 pandemic. In that review, many potential blockchain applications were discovered; however, the majority of them were still in their infancy, and it couldn’t yet be predicted how they could contribute to the fight against COVID-19 through the use of platforms, access kinds, and consensus algorithms. …”
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Predicting tuberculosis drug properties using extended energy based topological indices via a python driven QSPR approach by Kiran Naz, Hafiz Muhammad Bilal, Muhammad Kamran Siddiqui, Sarfraz Ahmad, Mustafa Ahmed Ali

“…All the calculations are done using Python, and the rigorous algorithmic implementation in the form of matrix formulation and computation of the eigenvalue is also given for reproducibility. …”
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Improve the Accuracy of Support Vector Machine Using Chi Square Statistic and Term Frequency Inverse Document Frequency on Movie Review Sentiment Analysis by Ukhti Ikhsani Larasati, Much Aziz Muslim, Riza Arifudin, Alamsyah Alamsyah

“…Support vector machine is one of the classification algorithms that can be used for sentiment analysis. …”
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USE OF HIGH-DEFINITION IMAGING FLOW CYTOMETRY AND A.I. TO ENUMERATE AND CHARACTERISE CIRCULATING TUMOUR CELLS

“… The last decade has shone a spotlight on the field of liquid biopsies, a minimally invasive, yet data-rich approach for cancer diagnosis and management. There are many types of liquid biopsies including cerebrospinal fluid, blood, urine, saliva or pleural effusion. …”
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CPR-Induced Consciousness during Ventricular Fibrillation: Case Report and Literature Review by Xiaoqing Zhou, Boru Sun

“…It is crucial to develop clear algorithms that focus not only on identifying this phenomenon but also on determining the best approaches to manage it. …”
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Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina by Džana Bašić-Čičak, Jasminka Hasić Telalović, Lejla Pašić

“…Background/Objectives: The study of microbiome composition shows positive indications for application in the diagnosis and treatment of many conditions and diseases. One such condition is autism spectrum disorder (ASD). …”
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Inference of population structure using dense haplotype data. by Daniel John Lawson, Garrett Hellenthal, Simon Myers, Daniel Falush

“…In parallel, we have developed an efficient model-based approach to identify discrete populations using this matrix, which offers advantages over PCA in terms of interpretability and over existing clustering algorithms in terms of speed, number of separable populations, and sensitivity to subtle population structure. …”
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The Use of Wearable Sensors and Machine Learning Methods to Estimate Biomechanical Characteristics During Standing Posture or Locomotion: A Systematic Review by Isabelle J. Museck, Daniel L. Brinton, Jesse C. Dean

“…Overall, this review can help guide the future development of ML algorithms and wearable sensor technologies to estimate postural mechanics.…”
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Barriers, Drivers, and Social Considerations for AI Adoption in Supply Chain Management: A Tertiary Study by Johannes Hangl, Viktoria Joy Behrens, Simon Krause

“…<i>Results</i>: As a summary of the results, the main areas of AI in SCM were algorithms, followed by the Internet of Things (IoT). …”
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