Enhancing Visual–Inertial Odometry Robustness and Accuracy in Challenging Environments by Alessandro Minervini, Adrian Carrio, Giorgio Guglieri

“…Visual–Inertial Odometry (VIO) algorithms are widely adopted for autonomous drone navigation in GNSS-denied environments. …”
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A Machine Learning Dataset of Artificial Inner Ring Damage on Cylindrical Roller Bearings Measured Under Varying Cross-Influences by Christopher Schnur, Payman Goodarzi, Yannick Robin, Julian Schauer, Andreas Schütze

“…In practical machine learning (ML) applications, covariate shifts and dependencies can significantly impact model robustness and prediction quality, leading to performance degradation under distribution shifts. …”
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New opportunities and trends in international investment driven by machine learning by Li Chang, Cai Linxin, Lin Qinni, Huang Yujie

“…In this regard, after understanding the new opportunities and challenges of international investment in the era of big data, this paper mainly studies the decentralized portfolio selection model with machine learning algorithm as the core, and verifies the application effect of various algorithms combined with experiments. …”
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On the effect of sampling frequency on the electricity theft detection performance by Fatemeh Soleimani Nasab, Foad Ghaderi

“…To investigate the effect of sampling frequency on the performance of detection methods, we designed a processing framework to evaluate different classification algorithms on versions of a challenging dataset obtained by down‐sampling the original data at various rates. …”
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Vehicle Detection and Shape Refinement Based on LiDAR by YU An, HU Dongfang, WANG Xuepeng, ZHANG Jin, ZHOU Yan, XIE Guotao, QIN Xiaohui, HU Manjiang

“…Accurate vehicle detection and shape estimation can provide accurate static information for follow-up tracking and prediction. Although the existing vehicle detection algorithm based on lidar can accurately detect and classify each target vehicle, there is a problem of unstable estimation when the vehicle point cloud contour is partially obscured in an "L" shape. …”
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Artificial intelligence-driven metabolic engineering is applied to the development of active ingredients in Traditional Chinese Medicine by Zhang Guoqi, Wang Juan

“…In this paper, we introduce AI-driven machine learning algorithms in prediction models, and also review recent research progress on AI-assisted metabolic engineering design and production of high-value compounds, focusing on how to use AI methods to achieve directed evolution of strains.…”
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On PTV definition for glioblastoma based on fiber tracking of diffusion tensor imaging data. by Barbara Witulla, Nicole Goerig, Florian Putz, Benjamin Frey, Tobias Engelhorn, Arnd Dörfler, Michael Uder, Rainer Fietkau, Christoph Bert, Frederik Bernd Laun

“…It depended strongly on the used tracking algorithm and the used tracking parameters whether a connection was observed. …”
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AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

“…Furthermore, our integration of these algorithms into a user-friendly MATLAB R2024b application ensures easy access for medical professionals, facilitating timely diagnosis and treatment. …”
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Hybrid Laminar Flow Control Optimizations for Infinite Swept Wings by Yayun Shi, Xiayu Lan, Tihao Yang

“…The Reynolds-averaged Navier-Stokes (RANS) solver coupled with the linear stability theory is applied for the laminar-turbulent transition prediction, and the traditional optimization method based on evolutionary algorithms is applied for laminar flow wing optimization. …”
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Traffic weaver: Semi-synthetic time-varying traffic generator based on averaged time series by Piotr Lechowicz, Aleksandra Knapińska, Adam Włodarczyk, Krzysztof Walkowiak

“…The primary motivation behind Traffic Weaver is to furnish semi-synthetic time-varying traffic in telecommunication networks, facilitating the development and validation of traffic prediction models, as well as aiding in the deployment of network optimization algorithms tailored for time-varying traffic.…”
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A new numerical method for processing longitudinal data: clinical applications by Ilaria Stura, Emma Perracchione, Giuseppe Migliaretti, Franco Cavallo

“…In particular, our mixed model, that uses Radial Basis Functions (RBFs) combined with Stochastic Optimization Algorithms (SOMs), is here presented and tested on clinical data. …”
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Charactering Neural Spiking Activity Evoked by Acupuncture Through Coupling Generalized Linear Model by Qing Qin, Kaiyue Zhang, Yanqiu Che, Chunxiao Han, Yingmei Qin, Shanshan Li

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Secure K-Means Clustering Scheme for Confidential Data Based on Paillier Cryptosystem by Zhengqi Zhang, Zixin Xiong, Jun Ye

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Advances in optical biosensors as alternative diagnostics for clinical determination of ESKAPE bacteria by Maargavi Singh, Sreelakshmi C․S․, Chiranjay Mukhopadhyay, Sajan D. George, Pooja Nag, Kapil Sadani

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A Golden Jackal based optimal operation and optimization of a virtual power plant involving renewable resources by Anubhav Kumar Pandey, Chaima Mansour, Nandini K. K., Vinay Kumar Jadoun, Jayalakshmi N. S.

“…In particular, there is a reduction in cost by 2.1% and 0.62% when compared with the salp swarm algorithm and beluga whale algorithm followed by 2.12% and 1.18% in emission. …”
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Evaluation of the BronchiolitisMAD protocol in the out-of-hospital emergency services of the Community of Madrid by Beatriz Jiménez-Sánchez Carpio, Laura Sánchez-García, Itziar Marsinyach-Ros, Joaquín Antonio Rendo-Murillo, Víctor Quesada-Cubo, Marina Gómez-Morán Quintana, Jorge Lorente-Romero, María Isabel Sánchez-Sáenz, Ana María Cintora-Sanz, Cristina Horrillo-García

“…It provides detailed algorithms and checklists for treatment and transfer decisions. …”
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A Heuristic Approach to Competitive Facility Location via Multi-View K-Means Clustering with Co-Regularization and Customer Behavior by Thanathorn Phoka, Praeploy Poonprapan, Pornpimon Boriwan

“…An empirical evaluation on a real-world dataset from San Francisco demonstrates that the proposed approach, using optimal co-regularization parameters, achieves a total runtime of approximately 4.00 s—representing a 99.34% reduction compared to the full CFLBP-CB model (608.58 s) and a 99.32% reduction compared to a genetic algorithm (585.20 s). …”
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Quantitative assessment and Kirschner-wire fixation of an isolated sustentaculum tali fracture in a 7-year-old girl—a case report by Fengyong Mao, Lei Ni, Li Ju

“…Surgical management consisted of ORIF utilizing two 1.5 mm K-wires to achieve anatomic reduction. The postoperative protocol included 6 weeks of cast immobilization followed by a structured rehabilitation program. …”
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Improving accuracy of self-reported diagnoses of rheumatoid arthritis in the French prospective E3N-EPIC cohort: a validation study by Marie-Christine Boutron-Ruault, Yann Nguyen, Carine Salliot, Gaëlle Gusto, Elise Descamps

“…These algorithms were then applied to the whole cohort to ascertain RA cases.Results Of the 98 995 participants, 2692 self-reported RA. …”
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A multimodal approach for enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models and targeted spraying technology by Rohit ANAND, Roaf Ahmad PARRAY, Indra MANI, Tapan Kumar KHURA, Harilal KUSHWAHA, Brij Bihari SHARMA, Susheel SARKAR, Samarth GODARA, Shideh MOJERLOU, Hasan MIRZAKHANINAFCHI

“…The spectral data sets were analyzed using decision tree and support vector machine (SVM) algorithms to identify the most accurate model for distinguishing diseased and healthy plants. …”
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