Distributed Acoustic Sensing of Sounds in Audible Spectrum in Realistic Optical Cable Infrastructure by Petr Dejdar, Ondrej Mokry, Petr Munster, Tomas Horvath, Jiri Schimmel

“…The dataset offers the possibility to develop and test algorithms aimed at enhancing signal-to-noise ratio (SNR), detecting anomalies, and improving speech intelligibility. …”
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Bean leaf image dataset annotated with leaf dimensions, segmentation masks, and camera calibrationMendeley Data by Karla Gabriele Florentino da Silva, Paulo Victor de Magalhães Rozatto, Kaio de Oliveira e Sousa, Lucas Dias Hudson, Artur Welerson Sott Meyer, Alemilson Fabiano Silva, Igor Tibiriçá Mendes, Alex Rodrigues Borges, Leandro Elias Morais, Luiz Maurílio da Silva Maciel, Saulo Moraes Villela, Helio Pedrini, Marcelo Bernardes Vieira

“…This dataset can be useful for developing deep learning algorithms for leaf dimensioning and related problems. …”
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FedEasy : Federated learning with ease by Majid Kundroo, Ghani Haider, Nguyen Khoa, Abdul Wahab Mamond, Taehong Kim

“…However, existing FL frameworks often require extensive code modifications, creating challenges for researchers. In this paper, we introduce FedEasy, a user-friendly and scalable FL framework built on Flower and PyTorch. …”
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Teledentistry in the detection of oral potentially malignant disorders and oral cancer in the Latin American region: a review of literature with current possibilities by Caique Mariano Pedroso, Saman Warnakulasuriya, Alan Roger Santos-Silva

“…Moreover, it examined the integration of artificial intelligence algorithms and teledentistry for enhancing diagnostic accuracy, thereby optimizing resource allocation and improving patient outcomes. …”
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Measurement-Driven Iterated Correction GM-PHD Filter for Passive Tracking With Hardware-in-the-Loop Simulation by Runle Du, Jizhe Wang, Di Zhou, Xinguang Zou, Jiaqi Liu

“…Finally, a hardware-in-the-loop (HIL) simulation system is implemented to verify the validity of the designed multiple target tracking (MTT) algorithms.…”
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Combating Antimicrobial Resistance: Spectroscopy Meets Machine Learning by Dimple Saikia, Ritam Dadhara, Cebajel Tanan, Prajwal Avati, Tushar Verma, Rishikesh Pandey, Surya Pratap Singh

“…There are various steps that have been taken by researchers and organizations to identify, cure, and prevent this urgent issue. …”
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Development and Implementation of a Machine Learning‐Based Flood Forecasting System in Kasese District, Uganda by Edward Miiro, Ismael Kato, Zuhra Nantege, Samuel Ssendi, Khasim Bassajjalaba

“…ABSTRACT This study aimed to develop a proof‐of‐concept prototype of a machine learning system to forecast and mitigate the effect of floods in Kasese District. The researchers used a participatory design science approach. …”
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scMoMtF: An interpretable multitask learning framework for single-cell multi-omics data analysis. by Wei Lan, Tongsheng Ling, Qingfeng Chen, Ruiqing Zheng, Min Li, Yi Pan

“…The experimental results shows that scMoMtF outperforms current state-of-the-art algorithms on these tasks. In addition, scMoMtF has interpretability which allowing researchers to gain a reliable understanding of potential biological features and mechanisms in single-cell multi-omics data.…”
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Evolving techniques in sentiment analysis: a comprehensive review by Mahander Kumar, Lal Khan, Hsien-Tsung Chang

“…With the rapid expansion of social media and e-commerce platforms, an unprecedented volume of user-generated content has emerged, offering organizations, governments, and researchers invaluable insights into public sentiment. …”
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Practical Introduction to Benchmarking and Characterization of Quantum Computers by Akel Hashim, Long B. Nguyen, Noah Goss, Brian Marinelli, Ravi K. Naik, Trevor Chistolini, Jordan Hines, J.P. Marceaux, Yosep Kim, Pranav Gokhale, Teague Tomesh, Senrui Chen, Liang Jiang, Samuele Ferracin, Kenneth Rudinger, Timothy Proctor, Kevin C. Young, Irfan Siddiqi, Robin Blume-Kohout

“…Breakthroughs in quantum algorithms, quantum simulations, and quantum error correction are bringing useful quantum computation closer to fruition. …”
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Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Health Analytics by Félix Camirand Lemyre, Simon Lévesque, Marie-Pier Domingue, Klaus Herrmann, Jean-François Ethier

“…Although distributed algorithms offer alternatives, they may not always be suitable for health frameworks. …”
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Enabling scalable single-cell transcriptomic analysis through distributed computing with Apache spark by Asif Adil, Namrata Bhattacharya, Aadam, Naveed Jeelani Khan, Mohammed Asger

“…We demonstrate the utility of our framework and algorithms through a series of experiments on real-world scRNA-seq data. …”
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Water-Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP-Hard Problems by Fernando Rubio, Ismael Rodríguez

“…Despite the strong similarities of these methods in terms of their underlying natural metaphors (most of them emulate, in some way or another, how drops collaboratively form paths down to the sea), in general the resulting algorithms are quite different in terms of their searching approach or their solution construction approach. …”
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Selective Reviews of Bandit Problems in AI via a Statistical View by Pengjie Zhou, Haoyu Wei, Huiming Zhang

“…Reinforcement Learning (RL) is a widely researched area in artificial intelligence that focuses on teaching agents decision-making through interactions with their environment. …”
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opstool: A Python library for OpenSeesPy analysis automation, streamlined pre- and post-processing, and enhanced data visualization by Yexiang Yan, Yazhou Xie

“…In addition, it integrates adaptive iteration algorithms to improve convergence issues in nonlinear static and dynamic response analyses. …”
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Sample Weighting Methods for Compensating Class Imbalance in Elephant Flow Classification by Piotr Jurkiewicz, Robert Wojcik, Jerzy Domzal

“…Analysis reveals that one of our proposed methods based on square root weighting significantly outperforms standard class balancing, offering up to 72% gains in flow operations reduction metric across multiple algorithms. These findings provide valuable insights for researchers and practitioners working on flow classification problem, contributing to more efficient network traffic management systems.…”
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A Novel Approximation Method for Solving Ordinary Differential Equations Using the Representation of Ball Curves by Abdul Hadi Bhatti, Sharmila Karim, Ala Amourah, Ali Fareed Jameel, Feras Yousef, Nidal Anakira

“…To achieve minimal error and higher accuracy in approximate solutions, researchers have focused on developing algorithms using various numerical techniques. …”
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Dataset for estimating reinforcement, width and penetration of the weld bead in the GMAW process using thermographic informationfigshare by Bruno Mota de Souza, Guillermo Alvarez Bestard, Sadek C. Absi Alfaro

“…The dataset can be a valuable resource for researchers seeking to develop and test advanced control algorithms and dynamic models of the GMAW welding process. …”
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SPL-PlaneTR: Lightweight and Generalizable Indoor Plane Segmentation Based on Prompt Learning by Zhongchen Deng, Yuanlong Ge, Xiatian Qi, Kai Sun, Ruixi Wan, Bingxu Zhang, Shenman Zhang, Xun Zhang, Yan Meng

“…It has garnered significant attention from researchers and remains one of the most advanced algorithms in this field. …”
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Isfahan Artificial Intelligence Event 2023: Macular Pathology Detection Competition by Farnaz Sedighin, Maryam Monemian, Zahra Zojaji, Ahmadreza Montazerolghaem, Mohammad Amin Asadinia, Seyed Mojtaba Mirghaderi, Seyed Amin Naji Esfahani, Mohammad Kazemi, Reza Mokhtari, Maryam Mohammadi, Mohadese Ramezani, Mahnoosh Tajmirriahi, Hossein Rabbani

“…The aim of this challenge was to maximize the performance measures for the test labels. Researchers tested their algorithms and competed for the best classification results. …”
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