Ultra-High Spatial Resolution Clinical Positron Emission Tomography (PET) Systems by Myungheon Chin, Muhammad Nasir Ullah, Derek Innes, Craig S. Levin

“…A key strategy involves organ-specific, or loco-regional, scanner configurations that optimize photon detection efficiency (PDE) while balancing the trade-off between spatial resolution and image signal-to-noise ratio (SNR). …”
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Investigation on Beamspace Multiple-Input Multiple-Output Synthetic Aperture Radar Data Imaging by Hongbo Mo, Wei Xu, Zhimin Zeng

“…Afterwards, the resulting MIMO-SAR raw data could be equivalent to the raw data of the single-channel burst mode, and classical burst mode imaging algorithms could be adopted to obtain final focused SAR images. …”
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STUDY OF ROBUST TOA DISCRIMINATORS FOR SPACE-BASED RADAR ALTIMETER by D. S. Borovitsky, A. E. Zhesterev, V. P. Ipatov, R. M. Mamchur

“…In the  robust  algorithms TOA-measuring  is performed without  using  any  echo  physical  model.  …”
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Industrial-scale prediction of cement clinker phases using machine learning by Sheikh Junaid Fayaz, Néstor Montiel-Bohórquez, Shashank Bishnoi, Matteo Romano, Manuele Gatti, N. M. Anoop Krishnan

“…Through post hoc explainable algorithms, we interpret the hierarchical relationships between clinker oxides and phase formation, providing insights into the functioning of an otherwise black-box model. …”
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Ecotoxicity prediction of chemical compounds using machine learning and different molecular structure representations by Michał Marek, Rafał Kurczab

“…Advancements in computational tools have facilitated interdisciplinary approaches in toxicology, enabling chemists to explore the toxicity and ecotoxicity of chemical compounds while minimizing ethically questionable or hazardous methods. …”
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GCN-based weakly-supervised community detection with updated structure centres selection by Liping Deng, Bing Guo, Wen Zheng

“…Semi-supervised network learning requires a certain amount of known samples, while sample annotation is time-consuming and laborious. …”
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Un enfoque de machine learning para apoyar la identificación de la deuda técnica en arquitectura by Boris Rainiero Pérez-Gutiérrez, Darío Ernesto Correal, Fredy Humberto Vera-Rivera

“…Conclusions: The data used to train the model, while appropriate, is susceptible to further improvement. …”
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Reinforced Residual Encoder–Decoder Network for Image Denoising via Deeper Encoding and Balanced Skip Connections by Ismail Boucherit, Hamza Kheddar

“…Traditional image denoising algorithms often struggle with real-world complexities such as spatially correlated noise, varying illumination conditions, sensor-specific noise patterns, motion blur, and structural distortions. …”
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A Summary of the Existing Data on Cleft Surgical Outcomes: What Do We Not Know? by Priyanka Naidu, MBChB, MS, Alexander T. Plonkowski, MBBS, MRes, Caroline A. Yao, MD, MS, William P. Magee, III, MD, DDS

“…These protocols all aim to achieve optimal aesthetic appearance and speech outcomes while limiting significant complications such as velopharyngeal insufficiency and midface hypoplasia. …”
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Rolling Cargo Management Using a Deep Reinforcement Learning Approach by Rachid Oucheikh, Tuwe Löfström, Ernst Ahlberg, Lars Carlsson

“…In this paper, we apply state-of-the-art deep reinforcement learning algorithms to automate these operations in a complex and real environment. …”
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Routing Protocols for Vehicular Delay Tolerant Networks: A Survey by Hyunwoo Kang, Syed Hassan Ahmed, Dongkyun Kim, Yun-Su Chung

“…However, the choice of routing algorithms in VDTNs is still under study. The main objective of routing protocols in VDTNs is to maximize the probability of delivery at the destination while minimizing the end-to-end delay. …”
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Wearable sensing in eating episode monitoring: an updated systematic review protocol by Jiaying Zhou, Mingzhu Cai, Mayue Shi

“…Studies that focus solely on the development of algorithms or applications for these sensors will be excluded. …”
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Outside the social making of interoperability: Problematizing the absence of civil society in border security R&D programmes by Clemens Binder, Bruno Oliveira Martins, Lise Endregard Hemat

“…Big data-based governance requires both compatible modes of computing data and interoperable databases. While interoperability is often portrayed as a logical imperative, we understand it as socially co-produced within a political choice for algorithmic governance. …”
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The contingencies of platform power and risk management in the gig economy by Niels van Doorn

“…What do we miss about the daily operations of platform power, and about power dynamics in the gig economy more broadly, when focusing on algorithmic management as the primary source of subordination and precarity in the workplace? …”
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Key predictors of student proficiency in quantum computing by Shabnam Sodagari

“…Multiple regression analysis revealed that general understanding, exposure to topics, and qubit knowledge significantly contribute to proficiency, while topics such as quantum algorithms and teleportation were negatively associated, suggesting areas of greater instructional difficulty. …”
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Bounds on the initial macroporosity of sea ice pressure ridges by Sönke Maus

“…One important property of sea ice ridges is the macroporosity or void fraction. While macroporosity has been observed in field and laboratory studies, data are sparse and a concise theory of its evolution is lacking. …”
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Computed tomography—current status and future directions for arthritis imaging by Sevtap Tugce Ulas, Torsten Diekhoff

“…Technological innovations such as low-dose CT and state-of-the-art reconstruction algorithms reduce radiation exposure while maintaining image quality and short acquisition times. …”
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Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

“…This study utilizes a range of machine learning algorithms, including linear regression, decision tree, random forest, gradient boosting, K-nearest neighbour, Support Vector Regression, LightGBM and CatBoost, to analyse their effectiveness in predicting pavement performance. …”
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Two Power Allocation and Beamforming Strategies for Active IRS-aided Wireless Network via Machine Learning by Q. Cheng, J. Bai, X. Wang, B. Shi, W. Gao, F. Shu

“…The former has a better rate performance, while the latter has a lower computational complexity. …”
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Drone-assisted climate-smart agriculture (DACSA): A spatially-based outcome prediction model as an initial approach to track yield changes in shallot planting areas

“…The challenge of meeting the world's food demands while protecting the environment is an urgent concern. …”
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