Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation by Lalitha Krishnasamy, Siva C, Rajesh Kumar Dhanaraj, Mahmoud Ahmad Al-Khasawneh, Taher Al-Shehari, Nasser A. Alsadhan, Shitharth Selvarajan

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HoloGaussian Digital Twin: Reconstructing 3D Scenes with Gaussian Splatting for Tabletop Hologram Visualization of Real Environments by Tam Le Phuc Do, Jinwon Choi, Viet Quoc Le, Philippe Gentet, Leehwan Hwang, Seunghyun Lee

“…Recent advancements in Gaussian splatting algorithms allow for real-time spatial data collection of a higher quality compared to photogrammetry and neural radiance fields. …”
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Potential of Multi-Source Multispectral vs. Hyperspectral Remote Sensing for Winter Wheat Nitrogen Monitoring by Xiaokai Chen, Yuxin Miao, Krzysztof Kusnierek, Fenling Li, Chao Wang, Botai Shi, Fei Wu, Qingrui Chang, Kang Yu

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Enhancing Security in Industrial IoT Networks: Machine Learning Solutions for Feature Selection and Reduction by Ahmad Houkan, Ashwin Kumar Sahoo, Sarada Prasad Gochhayat, Prabodh Kumar Sahoo, Haipeng Liu, Syed Ghufran Khalid, Prince Jain

“…The article emphasizes the critical role of feature engineering, with a specific focus on feature selection and reduction, and elaborates on applying MRMR and PCA algorithms to various feature sets. By comparing these methods, it showcases their influence on both model performance and complexity, leading to the development of more efficient and precise intrusion detection systems for Industrial IoT networks. …”
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Health economics evaluation of diagnostic strategies for gastro-oesophageal reflux disease with reflux symptoms in China: a modelling study by Yang Chen, Feng Xie, Hongda Chen, Dong Wu, Xiaoqing Li, Xiaxiao Yan, Meiduo Ouzhu, Ziqi Guo, Chengzhen Lyu, Daiyu Yang

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Improving Pulsar Timing Precision with Single Pulse Fluence Clustering by Sofia V. Sosa Fiscella, Michael T. Lam, Maura A. McLaughlin

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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…This necessitates in-depth research and innovation to ensure that human action recognition technology adapts to the diverse communication environments of the future. …”
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EcoNicheS: enhancing ecological niche modeling, niche overlap and connectivity analysis using the shiny dashboard and R package by Armando Sunny, Clere Marmolejo, Rodrigo Vidal-López, Fredy A. Falconi-Briones, Ángela P. Cuervo-Robayo, René Bolom-Huet

“…EcoNicheS integrates innovative workflows with dynamic output visualizations while emphasizing reproducibility and comparability across statistical methods. Its practical applications span diverse research fields, including biogeography, epidemiology, evolutionary studies, climate change impacts, landscape connectivity, and biodiversity conservation. …”
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Continuous Speech for Improved Learning Pathological Voice Disorders by Syu-Siang Wang, Chi-Te Wang, Chih-Chung Lai, Yu Tsao, Shih-Hau Fang

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Leveraging SARs and Advanced Deep Learning Techniques for Oil Spill Detection in UAE by M. Alkhalifa, A. Alowais, A. Manousakis, A. Manousakis

“…Our proposed approach illustrated a high level of performance compared to other Convolutional Neural Network architectures used in similar cases. …”
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Routing Protocols Performance on 6LoWPAN IoT Networks by Pei Siang Chia, Noor Hisham Kamis, Siti Fatimah Abdul Razak, Sumendra Yogarayan, Warusia Yassin, Mohd Faizal Abdollah

“…This result is valuable to further implement these protocols in the testbed as well as provide an idea of the algorithmic enhancements.…”
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Authenticity Detection of Egg White Powder Using Near-Infrared Spectroscopy Based on Improved One-Dimensional Convolutional Neural Network Model by ZHU Zhihui, LI Wolin, HAN Yutong, JIN Yongtao, YE Wenjie, WANG Qiaohua, MA Meihu

“…The average time spent (AATS) for the detection was 0.004 4 seconds. Compared with traditional 1D-CNN network structure and other improved algorithms, the EG-1D-CNN model exhibited higher accuracy, faster detection speed, and smaller model footprint, thus making it more suitable for deployment on embedded devices. …”
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How to Learn More? Exploring Kolmogorov–Arnold Networks for Hyperspectral Image Classification by Ali Jamali, Swalpa Kumar Roy, Danfeng Hong, Bing Lu, Pedram Ghamisi

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Autonomous detection of nail disorders using a hybrid capsule CNN: a novel deep learning approach for early diagnosis by Gunjan Shandilya, Sheifali Gupta, Salil Bharany, Ateeq Ur Rehman, Upinder Kaur, Hafizan Mat Som, Seada Hussen

“…The purpose of this research is to offer novel deep-learning algorithms that target the autonomous categorization of six forms of nail disorders by employing images: Blue Finger, Clubbing, Pitting, Onychogryphosis, Acral Lentiginous Melanoma, and Normal Nail or Healthy Nail Appearance. …”
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A novel infrared thermography image analysis for transformer condition monitoring by Rupali Balabantaraya, Ashwin Kumar Sahoo, Prabodh Kumar Sahoo, Chayan Mondal Abir, Manoj Kumar Panda

“…To find the best performing machine learning model, different techniques are compared here in terms of their accuracy and stability. …”
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Innovative Expert-Based Tools for Spatiotemporal Shallow Landslides Mapping: Field Validation of the GOGIRA System and Ex-MAD Framework in Western Greece by Michele Licata, Francesco Seitone, Efthimios Karymbalis, Konstantinos Tsanakas, Giandomenico Fubelli

“…Upgrades to GOGIRA’s hardware and algorithms were carried out to improve its mapping accuracy. …”
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Enhancing Vehicle Location Prediction Accuracy with Road-Aware Rectification for Multi-Access Edge Computing Applications by Asif Mehmood, Afaq Muhammad, Faisal Mehmood, Wang-Cheol Song

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A framework for predicting zoonotic hosts using pseudo-absences: the case of Echinococcus multilocularis by Andrea Simoncini, Dimitri Giunchi, Marta Marcucci, Alessandro Massolo

“…To train the models, we defined pseudo-absences based on the bias in research effort. We compared the two algorithms and selected GLM as the most effective, using it to map potentially susceptible rodent species across phylogeny and geographic space. …”
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Among Artificial Intelligence/Machine Learning Methods, Automated Gradient-Boosting Models Accurately Score Intraoral Plaque in Non-Standardized Images by Eric Coy, William Santo, Bonnie Jue, Helen Betts, Francisco Ramos-Gomez, Stuart A. Gansky

“…Area-under-the-curve receiver operating characteristic (AUC-ROC) curve and R2 determined the best classification and regression models, respectively, compared to calibrated dentist researcher ratings. …”
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Critical review of OCT in clinical practice for the assessment of oral lesions by Fariba Esperouz, Domenico Ciavarella, Mauro Lorusso, Andrea Santarelli, Lorenzo Lo Muzio, Giuseppina Campisi, Lucio Lo Russo

“…This is further complicated by the introduction and increased trend to adopt artificial intelligence (AI) algorithms in imaging evaluation. Machine learning and deep learning algorithms have shown superior diagnostic sensitivity and accuracy compared to clinician judgment. …”
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