Ethics of Sensor-Based Surveillance of People with Dementia in Clinical Practice by Jacob Lahr, Nicole Schulze, Larissa N. Wüst, Claus Beisbart, Lena C. Bruhin, Marcello Ienca, Tobias Nef, Manuel Trachsel, Stefan Klöppel

“…We identify intrusion into privacy and the complex interaction between stakeholders as the biggest challenges. …”
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Subcarrier Index-Power Modulated-Optical OFDM With Dual Superposition Multiplexing for Directly Modulated DFB-Based IMDD PON Systems by Lin Chen, Fadi Halabi, Roger Philip Giddings, Junjie Zhang, Jianming Tang

“…A low-signal-modulation format-enabled highly spectrally efficient new transmission technique termed subcarrier index-power modulated optical OFDM with dual superposition multiplexing (SIPM-OOFDM-DSPM) is proposed and investigated, for the first time, in intensity modulation and direct detection (IMDD) passive optical network (PON) systems incorporating directly modulated DFB lasers (DMLs). …”
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Joined Spatial and Spectral Segmentation of Hyperspectral Datasets on Historical Art Objects by Lingxi Liu, Aurore Malmert, Emeline Pouyet, Silvia Mirri, Giovanni Delnevo

“…Spatial features excel in spatially contextualised data like urban planning and object detection, capturing adjacent pixel relationships. …”
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Automated Arrhythmia Classification System: Proof-of-Concept With Lightweight Model on an Ultra-Edge Device by Namho Kim, Seongjae Lee, Seungmin Kim, Sung-Min Park

“…The efficiency of the lightweight model and edge-computing system was evaluated regarding arrhythmia classification performance and computational complexity. …”
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A Multiscale Vision Transformer-Based Multimodal GeoAI Model for Mapping Arctic Permafrost Thaw by Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Zhining Gu, Yili Yang, Brendan M. Rogers, Anna Liljedahl

“…However, their small scale compared to other landform features, vague boundaries, and spatiotemporal variation pose significant challenges for accurate detection. In this article, we extend a state-of-the-art deep learning model to delineate RTS features across the Arctic in a multimodal setting. …”
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Eddy-induced underwater acoustic field reconstruction and computation based on sound speed classification and B-spline surface fitting by Luochuan Xu, Jian Xu, Xuegang Zhang, Anmin Zhang, Yi Liu, Dan Chen, Linglong Chen, Zhongpeng Wu

“…As a result, underwater acoustic detection has emerged as an effective approach for observing complex oceanic physical phenomena in these environments. …”
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Multimodal integration strategies for clinical application in oncology by Baoyi Zhang, Zhuoya Wan, Yige Luo, Xi Zhao, Josue Samayoa, Weilong Zhao, Si Wu

“…Artificial intelligence (AI) methods, adept at handling complex data structures, offer a powerful approach to efficiently integrate multimodal data. …”
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Advanced Diagnosis of Cardiac and Respiratory Diseases from Chest X-Ray Imagery Using Deep Learning Ensembles by Hemal Nakrani, Essa Q. Shahra, Shadi Basurra, Rasheed Mohammad, Edlira Vakaj, Waheb A. Jabbar

“…Despite the strengths of individual models, the ensemble meta-model achieved the best overall performance, with a Hamming Loss of 0.1408 and consistently higher ROC-AUC values across multiple diseases, demonstrating its superior capability to handle complex classification tasks. This robust ensemble learning framework underscores its potential for reliable and precise disease detection, offering significant improvements over traditional methods. …”
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A Novel Phenology-Based Index for Plastic-Mulched Farmland Extraction and Its Application in a Typical Agricultural Region of China Using Sentinel-2 Imagery and Google Earth Engine by Xinyu Dong, Jiaguo Li, Ning Xu, Junjie Lei, Zhen He, Limin Zhao

“…Plastic-mulching technology has a crucial role to play in modern agriculture by optimizing crop growth environments and enhancing yields. Accurately detecting and mapping the distribution of plastic-mulched farmlands (PMFs) is essential for improving both agricultural management and production efficiency. …”
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Compact classification using the biomimetic properties of ultrafast spiking microlaser neurons by Gibaek Kim, Matthieu Dubernard, Sami V El-Nakouzi, Amir-Hossein Masominia, Sylvain Barbay, Laurie E Calvet

“…This enables the training of a compact, energy efficient spiking photonic architecture that takes advantage of biomimetic properties to detect important features of the data. …”
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Advancing the Contemporary Multidisciplinary Heart Valve Team: Update on Priorities for Clinicians and Programs by Sandra B. Lauck, PhD, Connie Clark, MSN, Sophie Offen, MD, PhD, Erin Tang, MSN, Stephanie Sellers, PhD

“…For patients with aortic stenosis, the concept of the MDT must expand to address the significant barriers to timely detection, diagnosis, and referral and leverage its expertise to increase program capacity to accelerate access to care. …”
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Evaluating pedestrian crossing safety: Implementing and evaluating a convolutional neural network model trained on paired aerial and subjective perspective images by Dylan Russon, Antoine Guennec, Juan Naredo-Turrado, Binbin Xu, Cédric Boussuge, Valérie Battaglia, Benoit Hiron, Emmanuel Lagarde

“…With pedestrian crossings implicated in a significant proportion of vehicle-pedestrian accidents and the French government's initiatives to improve pedestrian safety, there is a pressing need for efficient, large-scale evaluation of pedestrian crossings. …”
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Estimating the Spectral Response of Eight-Band MSFA One-Shot Cameras Using Deep Learning by Pierre Gouton, Kacoutchy Jean Ayikpa, Diarra Mamadou

“…These models learn the complex relationship between 8-band multispectral data from the camera and 31-band multispectral data from the multi-object database, enabling accurate and efficient conversion. …”
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Estimating canopy height in tropical forests: Integrating airborne LiDAR and multi-spectral optical data with machine learning by Brianna J. Pickstone, Hugh A. Graham, Andrew M. Cunliffe

“…We suggest using RF due to its ease in model building, computational time, and efficient feature selection for predicting canopy height. …”
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Leveraging Digital Twin for operational resilience in the oil and gas industry by Giovanni Mazzuto, Ilaria Pietrangeli, Marco Ortenzi, Filippo Emanuele Ciarapica, Maurizio Bevilacqua

“…Future work: Future improvements will focus on refining the air flow modelling and expanding the dataset to improve predictive performance in extreme conditions providing an efficient anomaly detection system based on the DT prediction.…”
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Context-Aware Markov Sensors and Finite Mixture Models for Adaptive Stochastic Dynamics Analysis of Tourist Behavior by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong, Zhengchun Song

“…The proposed method addresses this limitation by introducing virtual sensors that dynamically detect contextual anomalies and trigger regime switches in real-time. …”
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Edge–Cloud Intelligence for Sustainable Wind Turbine Blade Transportation: Machine-Vision-Driven Safety Monitoring in Renewable Energy Systems by Yajun Wang, Xiaodan Wang, Yihai Wang, Shibiao Fang

“…These risks arise from collision hazards, complex terrain, and the difficulty of real-time monitoring under adverse environmental conditions. …”
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Mobile Mapping System for Urban Infrastructure Monitoring: Digital Twin Implementation in Road Asset Management by Vittorio Scolamiero, Piero Boccardo, Luigi La Riccia

“…The goal of urban digitalization is to provide a digital representation of physical infrastructure, data, information, and procedures for the management of complex anthropogenic systems. To meet this new goal, one must be able to understand the urban system through the integrated use of different methods in a multi-level approach. …”
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Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment by Vikas K. Soman, V. Natarajan

“…Traditional encryption algorithms are often inadequate in protecting confidential data, especially digital images, from complex cyberattacks. The increasing reliance on cloud storage and transmission of digital images has made it essential to develop strong security measures to stop unauthorized access and guarantee the integrity of sensitive information. …”
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Machine vision approach for monitoring and quantifying fish school migration by Feng Lin, Jicheng Zhu, Aiju You, Lei Hua

“…This design enables DVE-YOLO to capture dynamic object features, reveal correlations of detected objects across frames, and facilitate efficient tracking and detection. …”
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