3-Dimensional Spatial Analysis of Parking Lot Wall Scratch Using Mobile Point Cloud Data by Y. Li, C. Ye, Y. Zhang, Z. Kang

“…A novel approach integrating YOLOv10 object detection and PTv3 point cloud processing algorithms is developed to detect and localize scratches, while spatial analysis evaluates design factors affecting scratch distribution. …”
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Artificial intelligence and robotic surgery in clinical medicine: progress, challenges, and future directions by Salih Beyaz, Alaaddin Levent Özgözen, Necmettin Turgut, Hakkı Can Ölke

“…However, limitations such as algorithmic opacity, legal-ethical uncertainties, and fragmented digital infrastructures continue to hinder broader implementation. …”
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Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…Traditional machine learning algorithms perform quite well in general, with SVM giving a best accuracy of around 95% with academic data, while training and testing the model without academic data still gives a good performance of 93%. …”
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Multimodal Video Analysis for Crowd Anomaly Detection Using Open Access Tourism Cameras by Alejandro Dionis-Ros, Joan Vila-Francés, Rafael Magdalena-Benedito, Fernando Mateo, Antonio J. Serrano-López

“…Through pattern recognition algorithms and segmentation, informative measures of the number of people and image occupancy are extracted at regular intervals, which are then analyzed to obtain trends and anomalous behaviors. …”
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Advances in UAV Path Planning: A Comprehensive Review of Methods, Challenges, and Future Directions by Wenlong Meng, Xuegang Zhang, Lvzhuoyu Zhou, Hangyu Guo, Xin Hu

“…A fundamental aspect of UAV autonomy lies in route optimization, which determines efficient paths while considering factors like mission goals, safety, and power consumption. …”
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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. To optimize computational efficiency, window parameters are determined through an energy concentration maximization criterion, enabling rapid extraction of discriminative features from diverse PQ disturbances (e.g., voltage sags and transient interruptions). …”
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A Logarithmic Compression Method for Magnitude-Rich Data: The LPPIE Approach by Vasileios Alevizos, Zongliang Yue, Sabrina Edralin, Clark Xu, Nikitas Gerolimos, George A. Papakostas

“…This study introduces Logarithmic Positional Partition Interval Encoding (LPPIE), a novel lossless compression methodology employing iterative logarithmic transformations to drastically reduce data size. While conventional dictionary-based algorithms rely on repeated sequences, LPPIE translates numeric data sequences into highly compact logarithmic representations. …”
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Merging Multiple System Perspectives: The Key to Effective Inland Shipping Emission-Reduction Policy Design by Solange van der Werff, Fedor Baart, Mark van Koningsveld

“…Policymakers in the maritime sector face the challenge of designing and implementing decarbonization policies while maintaining safe navigation. Herein, the inland sector serves as a promising stepping stone due to the possibility of creating a dense energy supply infrastructure and shorter distances compared to marine shipping. …”
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Raw dataset of tensile tests in a 3D-printed nylon reinforced with oriented short carbon fibersMendeley Data by Ênio H. Pires, João V. Barreto Netto, Marcelo L. Ribeiro

“…Mechanical test data were collected using an Instron universal testing machine, while SEM images were captured to examine microstructural features and fracture surfaces, both before and after testing. …”
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Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling by Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi

“…Simulation analysis demonstrates that the new method can decrease energy consumption and average delay much lower than Round-Robin and threshold-based algorithms. The feature of temperature adaptation within Boltzmann further guarantees the achievement of the optimal scheduling actions while ensuring flexibility in the case or altering load percentages. …”
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Innovative Driver Monitoring Systems and On-Board-Vehicle Devices in a Smart-Road Scenario Based on the Internet of Vehicle Paradigm: A Literature and Commercial Solutions Overview by Paolo Visconti, Giuseppe Rausa, Carolina Del-Valle-Soto, Ramiro Velázquez, Donato Cafagna, Roberto De Fazio

“…The paper describes vehicle condition monitoring architectures, including diagnostic solutions for identifying anomalies, malfunctions, and instability while driving on slippery or wet roads. It also covers systems for classifying driving style, as well as tire and emissions monitoring. …”
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Reliable QoE Prediction in IMVCAs Using an LMM-Based Agent by Michael Sidorov, Tamir Berger, Jonathan Sterenson, Raz Birman, Ofer Hadar

“…We apply four Machine Learning (ML) algorithms and a Large Multimodal Model (LMM)-based agent, achieving mean errors of 4.61%, 5.36%, and 13.24% for three popular QoE metrics: BRISQUE, PIQE, and FPS, respectively.…”
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ecochange: An R‐package to derive ecosystem change indicators from freely available earth observation products by Wilson Lara, Maria C. Londoño, Ivan Gonzalez, Victor H. Gutierrez‐Velez

“…Abstract Spatial resources accessible for the derivation of biodiversity indicators of the class ecosystem structure are sparse and disparate, and their integration into computer algorithms for biodiversity monitoring remains problematic. …”
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Instruments for assessing healthcare professionals’ knowledge, attitudes and practices regarding deprescribing: a scoping review protocol by Luciane Cruz Lopes, Jardel Corrêa de Oliveira, Luis Phillipe Nagem Lopes, Mariana Del Grossi Moura, Ana Carolina Figueiredo Modesto, Laís Lessa Neiva Pantuzza

“…Studies focusing on deprescribing algorithms will be excluded. Studies in any healthcare setting will be included. …”
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Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. by Nicole A Doria-Rose, Han R Altae-Tran, Ryan S Roark, Stephen D Schmidt, Matthew S Sutton, Mark K Louder, Gwo-Yu Chuang, Robert T Bailer, Valerie Cortez, Rui Kong, Krisha McKee, Sijy O'Dell, Felicia Wang, Salim S Abdool Karim, James M Binley, Mark Connors, Barton F Haynes, Malcolm A Martin, David C Montefiori, Lynn Morris, Julie Overbaugh, Peter D Kwong, John R Mascola, Ivelin S Georgiev

“…Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. …”
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Inhibition mediated by group III metabotropic glutamate receptors regulates habenula activity and defensive behaviors by Anna Maria Ostenrath, Nicholas Faturos, Yağnur Işık Çiftci Çobanoğlu, Bram Serneels, Inyoung Jeong, Ekin Dongel Dayanc, Anja Enz, Francisca Hinrichsen, Aytac Kadir Mutlu, Ricarda Bardenhewer, Suresh Kumar Jetti, Stephan C. F. Neuhauss, Nathalie Jurisch-Yaksi, Emre Yaksi

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AI-assisted Pattern Generator for Garment Design by Michael Danner, Elena Brake, Gabriela Kosel, Yordan Kyosev, Katharina Rose, Matthias Rätsch, Holger Cebulla

“…The process uses advanced AI algorithms to facilitate the conversion of 3D scans into usable patterns. …”
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Regression Model Employing Spiking Neural Network for Bio-Signal Analysis With Hardware Integration by Choongseop Lee, Geunbo Yang, Jaewoo Baek, Yuntae Park, Mingyu Cheon, Jongkil Park, Cheolsoo Park

“…Spiking neural networks, known for mimicking the brain’s functionality resulting in efficient algorithms, are gaining attention across various problems and applications. …”
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Artificial intelligence: clinical applications and future advancement in gastrointestinal cancers by Abolfazl Akbari, Maryam Adabi, Mohsen Masoodi, Abolfazl Namazi, Abolfazl Namazi, Fatemeh Mansouri, Seidamir Pasha Tabaeian, Seidamir Pasha Tabaeian, Zahra Shokati Eshkiki

“…There are encouraging signs that the advent of artificial intelligence could enhance the treatment of gastrointestinal issues with this data. Deep learning algorithms can swiftly and effectively analyze unstructured, high-dimensional data, including texts, images, and waveforms, while advanced machine learning approaches could reveal new insights into disease risk factors and phenotypes. …”
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Pavement performance model for road maintenance and repair planning: a review of predictive techniques by Krishna Singh Basnet, Jagat Kumar Shrestha, Rabindra Nath Shrestha

“…It explores the implications of these limitations on accuracy and application, while also discussing how advanced predictive analytics can address these challenges. …”
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