Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability by Danish Raza, Hong Shu, Muhsan Ehsan, Hong Fan, Kamal Abdelrahman, Hasnat Aslam, Abdul Quddoos, Rana Waqar Aslam, Majid Nazeer, Mohammed S. Fnais, Azeem Sardar

“…First, by incorporating more than three decades of satellite data (1990–2022) and different Landsat missions with machine learning algorithms, high-confidence classes were defined for different land features, including cropland. …”
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Incorporation of Histogram Intersection and Semantic Information into Non-Negative Local Laplacian Sparse Coding for Image Classification by Ying Shi, Yuan Wan, Xinjian Wang, Huanhuan Li

“…Experimental results on four standard and three maritime image datasets demonstrate superior performance compared to the previous six algorithms. Specifically, the classification accuracy of our approach improved by 5% to 19% compared to the previous six methods. …”
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ClassWise-SAM-Adapter: Parameter-Efficient Fine-Tuning Adapts Segment Anything to SAR Domain for Semantic Segmentation by Xinyang Pu, Hecheng Jia, Linghao Zheng, Feng Wang, Feng Xu

“…Compared to conventional state-of-the-art semantic segmentation algorithms by extensive experiments, CWSAM showcases enhanced performance with fewer computing resources, highlighting the potential of leveraging foundational models such as SAM for specific downstream tasks in the SAR domain.…”
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The influence of digital platforms on gig workers: A systematic literature review by Farah Diba Almayanda Alauddin, Aini Aman, Mohd Fahmi Ghazali, Sity Daud

“…However, gig workers face significant challenges, such as a lack of social protections, algorithmic control, intense competition, and downward pressure on wages. …”
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Real-Time Hardware-in-the-Loop Laboratory Testing for Multisensor Sense and Avoid Systems by Giancarmine Fasano, Domenico Accardo, Lidia Forlenza, Alfredo Renga, Giancarlo Rufino, Urbano Tancredi, Antonio Moccia

“…This paper focuses on a hardware-in-the-loop facility aimed at real-time testing of architectures and algorithms of multisensor sense and avoid systems. It was developed within a research project aimed at flight demonstration of autonomous non-cooperative collision avoidance for Unmanned Aircraft Systems. …”
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Development and Prospects of National Intelligent System for Testing General Language Competencies Deployed Through Neural Network Solutions by E. M. Bazanova, A. V. Gorizontova, N. N. Gribova, T. M. Chikake, A. V. Samosyuk

“…The process of ISTOK development implied, apart from writing test items, putting together databases of writing and speaking assignments marked by professional assessors and assessment criteria for productive skills, as well as algorithms to identify various types of mistakes with the help of artificial intelligence. …”
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Field-Programmable Gate Array (FPGA)-Based Lock-In Amplifier System with Signal Enhancement: A Comprehensive Review on the Design for Advanced Measurement Applications by Jose Alejandro Galaviz-Aguilar, Cesar Vargas-Rosales, Francisco Falcone, Carlos Aguilar-Avelar

“…Advances in signal processing algorithms and hardware synthesis have enabled accurate signal extraction, even in extremely noisy environments, making LIAs indispensable in sensor applications for healthcare, industry, and other services. …”
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Gas permeability, diffusivity, and solubility in polymers: Simulation-experiment data fusion and multi-task machine learning by Brandon K. Phan, Kuan-Hsuan Shen, Rishi Gurnani, Huan Tran, Ryan Lively, Rampi Ramprasad

“…To address this challenge, we present a multi-tiered multi-task learning framework empowered with advanced machine-crafted polymer fingerprinting algorithms and data fusion techniques. This framework combines scarce “high-fidelity” experimental data with abundant diverse “low-fidelity” simulation or synthetic data, resulting in predictive models that display a high level of generalizability across novel chemical spaces. …”
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Smart interfaces to assist the operator in the context of industry 4.0 with a 5S human-centric approach by Mario Rojas, Javier Maldonado-Romo, Juana Isabel Mendez, Pedro Ponce, Arturo Molina

“…However, challenges related to realistic hand-object interactions and algorithmic enhancements were identified. The study underscores the importance of continuous improvement and cross-disciplinary collaboration to advance the usability and effectiveness of these technologies. …”
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Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology by Anand E. Rajesh, Abraham Olvera-Barrios, Alasdair N. Warwick, Yue Wu, Kelsey V. Stuart, Mahantesh I. Biradar, Chuin Ying Ung, Anthony P. Khawaja, Robert Luben, Paul J. Foster, Charles R. Cleland, William U. Makupa, Alastair K. Denniston, Matthew J. Burton, Andrew Bastawrous, Pearse A. Keane, Mark A. Chia, Angus W. Turner, Cecilia S. Lee, Adnan Tufail, Aaron Y. Lee, Catherine Egan, UK Biobank Eye and Vision Consortium

“…RPS may serve as a useful metric to quantify the diversity of the training, validation, and testing datasets used in the development of AI algorithms to ensure adequate inclusion and explainability of the model performance, critical in evaluating all currently deployed AI models. …”
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National Exposed Sediment Search and Inventory (NESSI): Utilizing Satellite Imagery and Machine Learning to Identify Dredged Sediment Placement Site Recovery by Thomas P. Huff, Emily R. Russ, Todd M. Swannack

“…A combination of satellite imagery data obtained and processed using Google Earth Engine and machine learning algorithms were applied at known dredged material placement sites to develop a time series of dredged material placement events and subsequent site recovery. …”
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SCoralDet: Efficient real-time underwater soft coral detection with YOLO by Zhaoxuan Lu, Lyuchao Liao, Xingang Xie, Hui Yuan

“…However, underwater coral detection presents unique challenges, including low image contrast, complex coral structures, and dense coral growth, which limit the effectiveness of general object detection algorithms. To address these challenges, we propose SCoralDet, a soft coral detection model based on the YOLO architecture. …”
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Dental bur detection system based on asymmetric double convolution and adaptive feature fusion by HongLing Hou, Ao Yang, Xiangyao Li, Kangkai Zhu, Yandi Zhao, Zhiqiang Wu

“…Our approach outperforms current detection algorithms in terms of detection capability and efficiency, presenting a new method for the precise detection and counting of elongated objects such as dental burs.…”
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E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review by Abed Mutemi, Fernando Bacao

“…Existing reviews provide broad overviews but fail to grasp the intricacies of ML algorithms in the e-commerce context. To bridge this gap, our study conducts a systematic literature review using the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) methodology. …”
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A SYSTEMATIC ANALYSIS OF AI-EMPOWERED EDUCATIONAL TOOLS DEVELOPED IN INDIA FOR DISABLED PEOPLE by Shivani, Monika Gupta, Satinder Bal Gupta

“…The Notebook platform utilizes Machine Learning algorithms that provide students with a personalized learning experience. …”
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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

“…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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The relationship between the individual biomechanical properties of the eye and the intraocular pressure measurements based on modern methods of ocular tonometry by M.D. Kats

“…In addition, various clinical algorithms have been proposed for adjusting these indicators and thus to ensure an adequate interpretation of IOP measurements. …”
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CohortDiagnostics: Phenotype evaluation across a network of observational data sources using population-level characterization. by Gowtham A Rao, Azza Shoaibi, Rupa Makadia, Jill Hardin, Joel Swerdel, James Weaver, Erica A Voss, Mitchell M Conover, Stephen Fortin, Anthony G Sena, Chris Knoll, Nigel Hughes, James P Gilbert, Clair Blacketer, Alan Andryc, Frank DeFalco, Anthony Molinaro, Jenna Reps, Martijn J Schuemie, Patrick B Ryan

“…<h4>Objective</h4>This paper introduces a novel framework for evaluating phenotype algorithms (PAs) using the open-source tool, Cohort Diagnostics.…”
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Evaluation of machine learning techniques for real-time prediction of implanted lower limb mechanics by Chase Maag, Clare K. Fitzpatrick, Paul J. Rullkoetter

“…Several predictive algorithms were explored, including linear regression (LRM), multilayer perceptron (MLP), bi-directional long short-term memory (biLSTM), convolutional neural network (CNN), and transformer-based approaches. …”
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High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”
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